Can supervise: YES
McGregor, C & Bonnis, B 2017, 'New Approaches for Integration: Integration of Haptic Garments, Big Data Analytics, and Serious Games for Extreme Environments', IEEE Consumer Electronics Magazine, vol. 6, no. 4, pp. 92-96.View/Download from: Publisher's site
© 2012 IEEE. Haptic garments present new opportunities to increase realism in gaming. As Real As It Gets (ARAIG) is a new form of haptic garment that uses muscle stimulation, vibration, and 7.1 surround sound to provide a new level of realism in gaming. The integration of new haptic garments like ARAIG with big data analytics and serious games presents new opportunities for more realistic virtual training that has application in many domains. In particular, there is great potential to support repeatable virtual training for extreme environments. In 2016, the IEEE Life Sciences Technical Community worked across the IEEE Societies to demonstrate this interdisciplinary nature, with a focus on solving life science problems in extreme environments. This article is based on our keynote address at the International Conference on Consumer Electronics (ICCE)-Berlin in 2016. It provides an example of this interdisciplinary case study research in action.
Physiological data is derived from electrodes attached directly to patients. Modern patient monitors are capable of sampling data at frequencies in the range of several million bits every hour. Hence the potential for cognitive threat arising from information overload and diminished situational awareness becomes increasingly relevant. A systematic review was conducted to identify novel visual representations of physiologic data that address cognitive, analytic, and monitoring requirements in critical care environments.The aims of this review were to identify knowledge pertaining to (1) support for conveying event information via tri-event parameters; (2) identification of the use of visual variables across all physiologic representations; (3) aspects of effective design principles and methodology; (4) frequency of expert consultations; (5) support for user engagement and identifying heuristics for future developments.A review was completed of papers published as of August 2016. Titles were first collected and analyzed using an inclusion criteria. Abstracts resulting from the first pass were then analyzed to produce a final set of full papers. Each full paper was passed through a data extraction form eliciting data for comparative analysis.In total, 39 full papers met all criteria and were selected for full review. Results revealed great diversity in visual representations of physiological data. Visual representations spanned 4 groups including tabular, graph-based, object-based, and metaphoric displays. The metaphoric display was the most popular (n=19), followed by waveform displays typical to the single-sensor-single-indicator paradigm (n=18), and finally object displays (n=9) that utilized spatiotemporal elements to highlight changes in physiologic status. Results obtained from experiments and evaluations suggest specifics related to the optimal use of visual variables, such as color, shape, size, and texture have not been fully understood. Relationships betwe...
Kamaleswaran, R, Collins, C, James, A & McGregor, C 2016, 'PhysioEx: Visual Analysis of Physiological Event Streams', COMPUTER GRAPHICS FORUM, vol. 35, no. 3, pp. 331-340.View/Download from: Publisher's site
There is a significant trend toward implementing health information technology to reduce administrative costs and improve patient care. Unfortunately, little awareness exists of the challenges of integrating information systems with existing clinical practice. The systematic integration of clinical processes with information system and health information technology can benefit the patients, staff, and the delivery of care.This paper presents a comparison of the degree of understandability of patient journey models. In particular, the authors demonstrate the value of a relatively new patient journey modeling technique called the Patient Journey Modeling Architecture (PaJMa) when compared with traditional manufacturing based process modeling tools. The paper also presents results from a small pilot case study that compared the usability of 5 modeling approaches in a mental health care environment.Five business process modeling techniques were used to represent a selected patient journey. A mix of both qualitative and quantitative methods was used to evaluate these models. Techniques included a focus group and survey to measure usability of the various models.The preliminary evaluation of the usability of the 5 modeling techniques has shown increased staff understanding of the representation of their processes and activities when presented with the models. Improved individual role identification throughout the models was also observed. The extended version of the PaJMa methodology provided the most clarity of information flows for clinicians.The extended version of PaJMa provided a significant improvement in the ease of interpretation for clinicians and increased the engagement with the modeling process. The use of color and its effectiveness in distinguishing the representation of roles was a key feature of the framework not present in other modeling approaches. Future research should focus on extending the pilot case study to a more diversified group of clinicians...
Hayes, G, Khazaei, H, El-Khatib, K, McGregor, C & Eklund, JM 2015, 'Design and Analytical Model of a Platform-as-a-Service Cloud for Healthcare', JOURNAL OF INTERNET TECHNOLOGY, vol. 16, no. 1, pp. 139-149.View/Download from: Publisher's site
Kamaleswaran, R, Wehbe, RR, Edward Pugh, J, Nacke, L, McGregor, C & James, A 2015, 'Collaborative multi-touch clinical handover system for the neonatal intensive care unit', Electronic Journal of Health Informatics, vol. 9, no. 1.
© by the authors. Background: A critically ill infant admitted to a neonatal intensive care unit requires complex, critical, and coordinated care performed by multidisciplinary healthcare teams. Since the infant's care is not provided by a single, individual physician during the infant's hospital stay, clinical handover is essential to enable the transfer of health information between physicians involved in the infant's care. Objective: Handover at present is largely conducted in an informal and ad hoc way. A study of clinical handover is required to inform the development of automated intelligent systems that facilitate communication and collaboration between critical care health providers. Methods: A qualitative study in a quaternary neonatal intensive care unit, at The Hospital for Sick Children was undertaken to understand clinical handover and derive usability requirements. This is then used to inform a high level design of a multi-touch tabletop application for handover the design was then evaluated against senior neonatologists and neonatal fellows using rapid prototyping methods. Results: The results of the qualitative study showed that an effective handover application should at minimum include: tight integration with workflow and the physical environment, intuitive and simplicity, and minimalistic design following the 'less is more' philosophy. Conclusion: There is a need to optimize handover such that the information transferred is standardized, and the loss of information and/or misinformation is minimized. We argue that natural user interface design employed in the proposed design will result in improved care and less information loss during clinical handover.
Khazaei, H, McGregor, C, Eklund, JM & El-Khatib, K 2015, 'Real-Time and Retrospective Health-Analytics-as-a-Service: A Novel Framework.', JMIR medical informatics, vol. 3, no. 4, p. e36.View/Download from: Publisher's site
Analytics-as-a-service (AaaS) is one of the latest provisions emerging from the cloud services family. Utilizing this paradigm of computing in health informatics will beneﬁt patients, care providers, and governments signiﬁcantly. This work is a novel approach to realize health analytics as services in critical care units in particular.To design, implement, evaluate, and deploy an extendable big-data compatible framework for health-analytics-as-a-service that offers both real-time and retrospective analysis.We present a novel framework that can realize health data analytics-as-a-service. The framework is flexible and conﬁgurable for different scenarios by utilizing the latest technologies and best practices for data acquisition, transformation, storage, analytics, knowledge extraction, and visualization. We have instantiated the proposed method, through the Artemis project, that is, a customization of the framework for live monitoring and retrospective research on premature babies and ill term infants in neonatal intensive care units (NICUs).We demonstrated the proposed framework in this paper for monitoring NICUs and refer to it as the Artemis-In-Cloud (Artemis-IC) project. A pilot of Artemis has been deployed in the SickKids hospital NICU. By infusing the output of this pilot set up to an analytical model, we predict important performance measures for the ﬁnal deployment of Artemis-IC. This process can be carried out for other hospitals following the same steps with minimal effort. SickKids' NICU has 36 beds and can classify the patients generally into 5 different types including surgical and premature babies. The arrival rate is estimated as 4.5 patients per day, and the average length of stay was calculated as 16 days. Mean number of medical monitoring algorithms per patient is 9, which renders 311 live algorithms for the whole NICU running on the framework. The memory and computation power required for Artemis-IC to handle the SickKids NICU will be 32 GB and ...
Khazaei, H, Mench-Bressan, N, McGregor, C & Pugh, JE 2015, 'Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective', IEEE Journal of Translational Engineering in Health and Medicine, vol. 3.View/Download from: Publisher's site
ï¿½ 2013 IEEE. The effective use of data within intensive care units (ICUs) has great potential to create new cloud-based health analytics solutions for disease prevention or earlier condition onset detection. The Artemis project aims to achieve the above goals in the area of neonatal ICUs (NICU). In this paper, we proposed an analytical model for the Artemis cloud project which will be deployed at McMaster Children's Hospital in Hamilton. We collect not only physiological data but also the infusion pumps data that are attached to NICU beds. Using the proposed analytical model, we predict the amount of storage, memory, and computation power required for the system. Capacity planning and tradeoff analysis would be more accurate and systematic by applying the proposed analytical model in this paper. Numerical results are obtained using real inputs acquired from McMaster Children's Hospital and a pilot deployment of the system at The Hospital for Sick Children (SickKids) in Toronto.
Percival, J, McGregor, C, Percival, N & James, A 2015, 'Enabling the integration of clinical event and physiological data for real-time and retrospective analysis', INFORMATION SYSTEMS AND E-BUSINESS MANAGEMENT, vol. 13, no. 4, pp. 693-711.View/Download from: Publisher's site
McGregor, C 2014, 'Riding the medical technology wave to empower your career in medicine', University of Toronto Medical Journal, vol. 92, no. 1, pp. 5-6.
Bressan, N, James, A, Lecce, L & McGregor, C 2013, 'Cardiorespiratory physiological data as an indicator of fentanyl pharmacokinetics and pharmacodynamics in critically ill newborn infants: A case report', Journal of Critical Care, vol. 28, no. 6, pp. e30-e31.View/Download from: Publisher's site
Choi, Y, Bressan, N, James, A, Pugh, E & McGregor, C 2013, 'Design of temporal analysis of neonatal vagal spells at different gestational ages using the artemis' framework', Journal of Critical Care, vol. 28, no. 1, pp. e4-e5.View/Download from: Publisher's site
Cirelli, J, McGregor, C, Graydon, B & James, A 2013, 'Analysis of continuous oxygen saturation data for accurate representation of retinal exposure to oxygen in the preterm infant', Studies in Health Technology and Informatics, vol. 183, pp. 126-131.View/Download from: Publisher's site
Maintaining blood oxygen saturation within the intended target range for preterm infants receiving neonatal intensive care is challenging. Supplemental oxygen is believed to lead to increased risk of retinopathy of prematurity and hence managing the level of oxygen within this population is important within their care. Current quality improvement activities use coarse hourly spot readings to measure supplemental oxygen levels as associated with targeted ranges that vary based on gestational age. In this research we use Artemis, a real-time online healthcare analytics platform to ascertain if the collection of second by second data provides a better representation of retinal exposure to oxygen than an infrequent, intermittent spot reading. We show that Artemis is capable of producing more accurate information from the higher frequency data, as it includes all the episodic events in the activity of the hour, which provides a better understanding of oxygen fluctuation ranges which affect the physiological status of the infant.. © 2013 ITCH 2013 Steering Committee and IOS Press. All rights reserved.
McGregor, C, Catley, C, Padbury, J & James, A 2013, 'Late onset neonatal sepsis detection in newborn infants via multiple physiological streams', Journal of Critical Care, vol. 28, no. 1, pp. e11-e12.View/Download from: Publisher's site
McGregor, C, Steadman, A, Percival, J & James, A 2013, 'Modelling health informatics capacity for neonatal intensive care patient journeys supported by interprofessional teams', International Journal of Biomedical Engineering and Technology, vol. 11, no. 3, pp. 301-317.View/Download from: Publisher's site
Neonatal intensive care is a highly complex area of healthcare requiring coordinated care between multiple healthcare professionals; as a result, information flow within the Neonatal Intensive Care Unit (NICU) can be very complex and impact quality of care. This paper presents initial research findings based on the use of the patient journey modelling technique known as PaJMa to audit the current state of health informatics within NICUs in Canada. In this paper, a case study including three Ontario NICUs is utilised and their 'Investigations' processes are modelled using PaJMa. Copyright © 2013 Inderscience Enterprises Ltd.
Naik, T, Bressan, N, James, A & McGregor, C 2013, 'Design of temporal analysis for a novel premature infant pain profile using artemis', Journal of Critical Care, vol. 28, no. 1, pp. e4-e4.View/Download from: Publisher's site
Nizami, S, Green, JR & McGregor, C 2013, 'Implementation of artifact detection in critical care: A methodological review', IEEE Reviews in Biomedical Engineering, vol. 6, pp. 127-142.View/Download from: Publisher's site
Artifact detection (AD) techniques minimize the impact of artifacts on physiologic data acquired in critical care units (CCU) by assessing quality of data prior to clinical event detection (CED) and parameter derivation (PD). This methodological review introduces unique taxonomies to synthesize over 80 AD algorithms based on these six themes: 1) CCU; 2) physiologic data source; 3) harvested data; 4) data analysis; 5) clinical evaluation; and 6) clinical implementation. Review results show that most published algorithms: a) are designed for one specific type of CCU; b) are validated on data harvested only from one OEM monitor; c) generate signal quality indicators (SQI) that are not yet formalized for useful integration in clinical workflows; d) operate either in standalone mode or coupled with CED or PD applications; e) are rarely evaluated in real-time; and f) are not implemented in clinical practice. In conclusion, it is recommended that AD algorithms conform to generic input and output interfaces with commonly defined data: 1) type; 2) frequency; 3) length; and 4) SQIs. This shall promote: a) reusability of algorithms across different CCU domains; b) evaluation on different OEM monitor data; c) fair comparison through formalized SQIs; d) meaningful integration with other AD, CED and PD algorithms; and e) real-time implementation in clinical workflows. © 2008-2011 IEEE.
Pugh, E, Thommandram, A, Ng, E, Mcgregor, C, Eklund, M, Narang, I, Belik, J & James, A 2013, 'Classifying neonatal spells using real-time temporal analysis of physiological data streams—algorithm development', Journal of Critical Care, vol. 28, no. 1, pp. e9-e9.View/Download from: Publisher's site
Pugh, JE, Thommandram, A, McGregor, C, Eklund, M & James, A 2013, 'Classifying neonatal spells using real-time temporal analysis of physiological data streams—verification tests', Journal of Critical Care, vol. 28, no. 6, pp. e40-e41.View/Download from: Publisher's site
Bressan, N, McGregor, C, Blount, M, Ebling, M, Sow, D & James, A 2012, '1618 Identification of Noxious Events for Newborn Infants with a Neural Network', Archives of Disease in Childhood, vol. 97, no. Suppl 2, pp. A458-A458.View/Download from: Publisher's site
Kamaleswaran, R & McGregor, C 2012, 'Integrating Complex Business Processes for Knowledge-driven Clinical Decision Support Systems', 2012 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), pp. 1306-1309.
Catley, C, Smith, K, McGregor, C, James, A & Eklund, JM 2011, 'A Framework for Multidimensional Real-Time Data Analysis', International Journal of Computational Models and Algorithms in Medicine, vol. 2, no. 1, pp. 16-37.View/Download from: Publisher's site
In this paper, the authors present a framework to support multidimensional analysis of real-time physiological data streams and clinical data. The clinical context for the case study demonstration is neonatal intensive care, focusing specifically on the detection of episodes of central apnoea, a clinically significant problem. The model accounts for the multidimensional and real-time nature of apnoea of prematurity and the associated clinical rules. The framework demonstration includes: 1) defining rules that quantify concurrent behaviours between multiple synchronous data streams and asynchronous data values; 2) designing UML models to define present practice event processing for episodes of apnoea; 3) translating the model in SPADE to enable the deployment within the real-time processing layer of the Artemis platform, which utilizes IBM’s InfoSphere Streams; 4) demonstrating knowledge discovery with simple and complex temporal abstractions of the data streams; and 5) presenting results for early detection of episodes of apnoea across multiple physiological data streams.
Nizami, S, Green, JR & McGregor, C 2011, 'Service Oriented Architecture to Support Real-Time Implementation of Artifact Detection in Critical Care Monitoring', 2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), pp. 4925-4928.
Seely, AJE, Kauffman, SA, Bates, JHT, Macklem, PT, Suki, B, Marshall, JC, Batchinsky, AI, Perez-Velazquez, JL, Seiver, A, McGregor, C, Maksym, G, Eng, MVKP, Similowski, T, Buchman, TG, Letellier, C, Filoche, M, Frasch, MG, Straus, C, Glass, L, Godin, PJ, Morris, JA, Sow, D, Nenadovic, V, Arnold, RC, Norris, P & Moorman, JR 2011, 'Proceedings from the Montebello Round Table Discussion. Second annual conference on Complexity and Variability discusses research that brings innovation to the bedside', JOURNAL OF CRITICAL CARE, vol. 26, no. 3, pp. 325-327.View/Download from: Publisher's site
Blount, M, Ebling, MR, Eklund, JM, James, AG, McGregor, C, Percival, N, Smith, KP & Sow, D 2010, 'Real-Time Analysis for Intensive Care Development and Deployment of the Artemis Analytic System', IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE, vol. 29, no. 2, pp. 110-118.View/Download from: Publisher's site
MacDougall, C, McGregor, C & Percival, J 2010, 'The fusion of clinical guidelines with technology: Trends & challenges', Electronic Journal of Health Informatics, vol. 5, no. 2.
The use of Health Information Technology (HIT) within the healthcare setting can be a great resource to contribute to improved patient care. Clinical guidelines are developed to aid in the decision making process of healthcare professionals and contain the leading edge of best patient practice. There is an abundance of evidence presenting the benefits that HIT contain; however, its use is rarely incorporated in today's clinical guidelines. Although, research suggests that the benefits of HIT are enough to integrate their use in clinical guidelines, there are a number of challenges that interfere with its implementation, such as, cultural diversity, interdisciplinary nature, lack of HIT knowledge for workers, evolution of technology, heavy clinical workload and lack of medical background in developers of HIT. The purpose of this research project is to present a literature review to further understand the trends and challenges of implementing HIT use within clinical guidelines. A modelling system, PaJMa is also introduced to visually depict a patient's journey and the methods of documentation. PaJMa can aid in discovering gaps in healthcare documentation and closing those gaps through HIT use within clinical guidelines. Further research revealed that there are models and approaches supporting the process and creation of clinical guidelines but none of these enable the inclusion of what technology will be used to support the implementation of these procedures. The research project concludes with ideas for future research in the area of clinical guideline development and HIT implementation. © of articles is retained by authors.
McGregor, C & Eklund, JM 2010, 'Next generation remote critical care through service-oriented architectures: Challenges and opportunities', Service Oriented Computing and Applications, vol. 4, no. 1, pp. 33-43.View/Download from: Publisher's site
Health care providers and governments are under pressure to maintain and improve the quality of care to an increasing volume of critical care patients at either end of the life cycle, namely premature and ill term babies together with the elderly. The provision of a service of critical care utilizing real time service-oriented architectures has the potential to enable clinicians to be supported in the care of a greater number patients that are, perhaps more importantly, located elsewhere to their intensive care units. This paper presents a review of recent research in the application of computing and IT to support the service of critical care and determines the trends and challenges for the application of real time service-oriented architectures within the domain. It then presents some case study-based research on the design of a service-oriented architecture-based approach to support two aspects of critical care namely elderly care and neonatal intensive care to provide further context to trends and opportunities. © 2010 Springer-Verlag London Limited.
Seely, AJE, Macklem, PT, Suki, B, Goldberger, A, Godin, P, Batchinsky, AI, Longtin, A, Jones, G, Seiver, A, McGregor, C, Norris, P, Maksym, G, Lake, D, Costa, MD, Marshall, JC, Morris, JA, Moorman, JR, Arnold, RC, Perez-Velazquez, JL & Nenadovic, V 2010, 'The Wakefield roundtable discussion on complexity and variability at the bedside Introduction', JOURNAL OF CRITICAL CARE, vol. 25, no. 3, pp. 536-537.View/Download from: Publisher's site
Eklund, JM & McGregor, C 2009, 'Standards for physiological data transmission and archiving for the support of the service of critical care', ACM SIGBED Review, vol. 6, no. 2, pp. 1-6.View/Download from: Publisher's site
McGregor, C & Maeder, A 2009, 'eHealth and services computing in healthcare', Journal of Theoretical and Applied Electronic Commerce Research, vol. 4, no. 2.
Percival, J, Catley, C, Mcgregor, C & James, A 2009, 'A design for modelling the impact of information and communication technologies on patient journeys in neonatal intensive care units', Studies in Computational Intelligence, vol. 189, pp. 147-169.View/Download from: Publisher's site
This paper presents the conceptual model of a survey and knowledge translation methodology to enable the assessment of the implementation of technology in neonatal intensive care units (NICUs) in order to determine the impact of information technology (IT) on information flows and patient care. Survey data, will be completed by healthcare practitioners from multiple roles, for various patient care scenarios, levels of care, and hospitals, and will then be translated using a structured data modelling approach into patient journey models. The data model is defined such that users can develop queries to generate patient journey models based on a pre-defined Patient Journey Model Architecture (PaJMa). PaJMa models will then be analyzed to build a visual representation of information flows and the use of IT in the NICU. The models will offer a sophisticated view of health informatics usage, providing not only details of what IT solutions a hospital utilizes, but also the impact that the IT solutions have when integrated into the patient journey, how they support the patient information flow, and why they improve the patient journey. © 2009 Springer-Verlag Berlin Heidelberg.
Catley, C, McGregor, C, Percival, J, Curry, J & James, A 2008, 'Multi-dimensional Knowledge Translation: Enabling Health Informatics Capacity Audits Using Patient Journey Models', 2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8, pp. 1502-+.View/Download from: Publisher's site
McGregor, C, Percival, J, Curry, J, Foster, D, Anstey, E & Churchill, D 2008, 'A Structured Approach to Requirements Gathering Creation Using PaJMa Models', 2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8, pp. 1506-+.View/Download from: Publisher's site
Curry, JM, McGregor, C & Tracy, S 2007, 'A systems development life cycle approach to patient journey modeling projects', Studies in Health Technology and Informatics, vol. 129, pp. 905-909.
Patient Journey Modeling, a relatively recent innovation in healthcare quality improvement, models the patient's movement through a Health Care Organisation (HCO) by viewing it from a patient centric perspective. A Systems Development Life Cycle (SDLC) provides a standard project management framework that can improve the quality of information systems. The concept of following a consistent project management framework to boost quality outcomes can be applied equally to healthcare improvement. This paper describes a SDLC designed specifically for the health care domain and in particular patient journey modeling projects. It goes on to suggest that such a framework can be used to compliment the dominant healthcare improvement method, the Model for Improvement. The key contribution of this paper is the introduction of a project management framework in the form of an SDLC that can be used by non-professional computer developers (ie: health care staff), to improve the consistency and quality of outcomes for patient journey redesign projects. Experiences of applying the SDLC in a midwife-led primary-care maternity services environment are discussed. The project team found the steps logical and easy to follow and produced demonstrable improvement results along with ongoing goal-focused action plans. © 2007 The authors. All rights reserved.
Mcgregor, C 2007, 'A Framework for the Design of Web Service Based Clinical Management Systems to Support Inter and Intra Organizational Patient Journeys', International Journal of Healthcare Information Systems and Informatics (IJHISI), vol. 2, no. 2, pp. 21-35.View/Download from: Publisher's site
The clinical management of premature and ill term babies is challenged by the necessity of several inter and intra organizational patient journeys. Premature and ill-term babies born in regional Australia and Canada must be moved to another hospital with Neonatal Intensive Care Unit (NICU) facilities. NICU babies requiring surgery must be moved to a Level IV NICU for surgery. Current clinical management supports the transfer of limited patient data via paper or telephone exchange. In this article a framework for the design of Web-service-based clinical management systems to support inter and intra organizational patient journeys is presented. A series of Web services are described and integrated and coordinated through BPEL processes enabling greater support for inter- and intra-organizational transfer of patient data. This framework is demonstrated through a NICU case study. A key benefit of this framework is that it enables the establishment of “on demand” patient journeys eliminating the need to establish permanent point-to-point connections. © 2007, IGI Global. All rights reserved.
McGregor, C, Kneale, B & Tracy, M 2007, 'On-demand virtual neonatal intensive care units supporting rural, remote and urban healthcare with bush babies broadband', JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, vol. 30, no. 4, pp. 1309-1323.View/Download from: Publisher's site
Stacey, M & McGregor, C 2007, 'Temporal abstraction in intelligent clinical data analysis: A survey', ARTIFICIAL INTELLIGENCE IN MEDICINE, vol. 39, no. 1, pp. 1-24.View/Download from: Publisher's site
Curry, J, McGregor, C & Tracy, S 2006, 'A communication tool to improve the patient journey modeling process', Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, pp. 4726-4730.View/Download from: Publisher's site
Quality improvement is high on the agenda of Health Care Organisations (HCO) worldwide. Patient Journey Modeling is a relatively recent innovation in healthcare quality improvement that models the patient's movement through the HCO by viewing it from a patient centric perspective. Critical to the success of the redesigning care process is the involvement of all stakeholders and their commitment to actively participate in the process. Tools which promote this type of communication are a critical enabler that can significantly affect the overall process redesign outcomes. Such a tool must also be able to incorporate additional factors such as relevant policies and procedures, staff roles, system usage and measurements such as process time and cost. This paper presents a graphically based communication tool that can be used as part of the patient journey modeling process to promote stakeholder involvement, commitment and ownership as well highlighting the relationship of other relevant variables that contribute to the patient's journey. Examples of how the tool has been used and the framework employed are demonstrated via a midwife-led primary care case study. A key contribution of this research is the provision of a graphical communication framework that is simple to use, is easily understood by a diverse range of stakeholders and enables ready recognition of patient journey issues. Results include strong stakeholder buy-in and significant enhancement to the overall design of the future patient journey. Initial results indicate that the use of such a communication tool can improve the patient journey modeling process and the overall quality improvement outcomes. © 2006 IEEE.
McGregor, C, Schiefer, J & zur Muehlen, M 2006, 'A shareable web service-based intelligent decision support system for on-demand business process management', International Journal of Business Process Integration and Management, vol. 1, no. 3, pp. 156-174.View/Download from: Publisher's site
The monitoring of business processes for performance measurement is challenged by the variety of inter and intra organisational units and information systems involved in the execution of these processes. In this paper we present a shareable, web service-based Intelligent Decision Support System (IDSS) for on-demand business process management, that we call the Solution Manager Service (SMS). The SMS allows organisations to outsource the collection, accumulation and transformation of information about their business processes from multiple distributed systems across multiple organisations in a centralised repository and share them among authorised parties, such as supply chain partners, clients or government agencies. Copyright © 2006 Inderscience Enterprises Ltd.
McGregor, C & Schiefer, J 2004, 'A Web-Service based framework for analyzing and measuring business performance', Information Systems and e-Business Management, vol. 2, no. 1.View/Download from: Publisher's site
Bastwadkar, M, McGregor, C & Balaji, S, 'Trends and Opportunities in Health Analytics as a Service and Implications for Use in Low Resource Settings: A Literature Review Abstract (Preprint)'.View/Download from: Publisher's site
This paper presents a systematic literature review of existing remote health monitoring systems with special reference to neonatal intensive care (NICU). Articles on NICU clinical decision support systems (CDSSs) which used cloud computing and big data analytics were surveyed.
The aim of this study is to review technologies used to provide NICU CDSS. The literature review highlights the gaps within frameworks providing HAaaS paradigm for big data analytics
Literature searches were performed in Google Scholar, IEEE Digital Library, JMIR Medical Informatics, JMIR Human Factors and JMIR mHealth and only English articles published on and after 2015 were included. The overall search strategy was to retrieve articles that included terms that were related to “health analytics” and “as a service” or “internet of things” / ”IoT” and “neonatal intensive care unit” / ”NICU”. Title and abstracts were reviewed to assess relevance.
In total, 17 full papers met all criteria and were selected for full review. Results showed that in most cases bedside medical devices like pulse oximeters have been used as the sensor device. Results revealed a great diversity in data acquisition techniques used however in most cases the same physiological data (heart rate, respiratory rate, blood pressure, blood oxygen saturation) was acquired. Results obtained have shown that in most cases data analytics involved data mining classification techniques, fuzzy logic-NICU decision support systems (DSS) etc where as big ...
Hayes, G, El-Khatib, K & McGregor, C 2014, 'Supporting Health Informatics with Platform-as-a-Service Cloud Computing' in Lecture Notes in Electrical Engineering, Springer Netherlands, pp. 1149-1158.View/Download from: Publisher's site
McGregor, C 2008, 'A framework for the design of web service based clinical management systems to support inter and intra organizational patient journeys' in Medical Informatics: Concepts, Methodologies, Tools, and Applications, pp. 411-426.View/Download from: Publisher's site
© 2009 by IGI Global. All rights reserved. The clinical management of premature and ill term babies is challenged by the necessity of several inter and intra organizational patient journeys. Premature and ill-term babies born in regional Australia and Canada must be moved to another hospital with Neonatal Intensive Care Unit (NICU) facilities. NICU babies requiring surgery must be moved to a Level IV NICU for surgery. Current clinical management supports the transfer of limited patient data via paper or telephone exchange. In this article a framework for the design of Web-service-based clinical management systems to support inter and intra organizational patient journeys is presented. A series of Web services are described and integrated and coordinated through BPEL processes enabling greater support for inter- and intra-organizational transfer of patient data. This framework is demonstrated through a NICU case study. A key benefit of this framework is that it enables the establishment of "on demand" patient journeys eliminating the need to establish permanent point-to-point connections.
McGregor, C 2008, 'Mobility in healthcare for remote intensive care unit clinical management' in Medical Informatics: Concepts, Methodologies, Tools, and Applications, pp. 740-752.View/Download from: Publisher's site
© 2009 by IGI Global. All rights reserved. This chapter reviews current research directions in healthcare mobility and assesses its impact on the provision of remote intensive care unit (ICU) clinical management. Intensive care units boast a range of state of the art medical monitoring devices to monitor a patient's physiological parameters. They also have devices such as ventilators to offer mechanical life support. Computing and IT support within ICUs has focused on monitoring the patients and delivering corresponding alarms to care providers. However many intensive care unit admissions are via intra and inter health care facility transfer, requiring receiving care providers to have access to patient information prior to the patient's arrival. This indicates that opportunities exist for mobile gadgets, such as personal digital assistants (PDAs) to substantially increase the efficiency and effectiveness of processes surrounding healthcare in the ICUs. The challenge is to transcend the use of these mobile devices beyond the current usage for personal information management and static medical applications; also to overcome the challenges of screen size and memory limitations. Finally, the deployment of mobile-enabled solutions within the healthcare domain is hindered by privacy, cost and security considerations and a lack of standards. These are some of the significant topics discussed in this chapter.
Groulx, A & McGregor, C 2018, 'A Social Media Tax Data Warehouse to Manage the Underground Economy', Proceedings - 20th International Conference on High Performance Computing and Communications, 16th International Conference on Smart City and 4th International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018, International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE International Conference on Data Science and Systems, IEEE, Exeter, United Kingdom, pp. 1599-1606.View/Download from: Publisher's site
© 2018 IEEE. Social media can provide a wealth of information valuable to tax administrators in managing the underground economy. This paper proposes a data warehouse design to integrate social media data into tax analytics processes. The warehouse is designed to support modern tax administration strategies that encourage self-regulation and voluntary compliance by shaping public opinion, improving services and developing inclusive tax policies. The warehouse also incorporates the use of social media analytics to support tax evasion detection and enforcement activities such as compliance risk assessment, audits, inspections and investigations.
Inibhunu, C, Jalali, R, Doyle, I, Gates, A, Madill, J & McGregor, C 2019, 'Adaptive API for Real-Time Streaming Analytics as a Service.', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Berlin, Germany, pp. 3472-3477.View/Download from: Publisher's site
A significant amount of physiological data is generated from bedside monitors and sensors in neonatal intensive units (NICU) every second, however facilitating the ingestion of such data into multiple analytical processes in a real time streaming architecture remains a central challenge for systems that seek effective scaling of real-time data streams. In this paper we demonstrate an adaptive streaming application program interface (API) that provides real time streams of data for consumption by multiple analytics services enabling real-time exploration and knowledge discovery from live data streams. We have designed, developed and evaluated an adaptive API with multiple ingestion of data streamed out of bedside monitors that is passed to a middleware for standardization and structuring and finally distributed as a service for multiple analytical services to consume and perform further processing. This approach allows, (a) multiple applications to process the same data streams using multiple algorithms, (b) easy scalability to manage diverse data streams, (c) processing of analytics for each patient monitored at the NICU, (d) ability to integrate analytics that seek to evaluate multiple patients at the same point in time, and (e) a robust automated process with no manual interruptions that effectively adapts to changing data volumes when bedside monitors increases or the amount of data emitted by a monitor changes. The proposed architecture has been instantiated within the Artemis Platform which provides a framework for real-time high speed physiological data collection from multiple and diverse bed side monitors and sensors in NICUs from multiple hospitals. Results indicate this is a robust approach that can scale effectively as data volumes increase or data sources change.
McGregor, C & Majola, PX 2019, 'Opportunities for a cloud based health analytics as a service for eastern cape initiation schools in South Africa', Proceedings - IEEE Symposium on Computer-Based Medical Systems, International Symposium on Computer-Based Medical Systems, IEEE, Cordoba, Spain, pp. 531-534.View/Download from: Publisher's site
© 2019 IEEE. Traditional male circumcision in the contemporary South Africa has become the focus of the government and media due to the large number of initiates severely injured or dying during the initiation period, which happens twice a year. Deaths and penile amputations are a feature of every circumcision season, as a result of sepsis, gangrene and dehydration amongst other diseases. This paper proposes a Cloud based Health Analytics as a Service for Eastern Cape initiation schools in South Africa to assist in saving lives and preserving the customs. The proposed Artemis platform will assist in acquiring physiological data of initiates before and during initiation to provide early insights of many conditions that can develop during initiation. Big data analytics based on Clinical Decision Support System such as Artemis provides real-time online analytics with knowledge extraction component that supports data mining and enables clinical research of various conditions. Conversely, Artemis has challenges for lower resource settings, which will be explored in this paper.
Prysyazhnyuk, A, McGregor, C, Chernikova, A & Rusanov, V 2019, 'A sliding window real-time processing approach for analysis of heart rate variability during spaceflight', Proceedings of the International Astronautical Congress, IAC.
Copyright © 2019 by the International Astronautical Federation (IAF). All rights reserved. The paradigm of technological disruption continues to pave the way for innovative technology that has the capacity to acquire comprehensive real-time physiological and environmental data and present endless opportunities to study physiological processes and mechanisms, aid clinical discovery and advance the field of preventative and corrective medicine both on Earth and during spaceflight. Missions of increased distance and duration, as well as ad-hoc emergency situations that render the space crew to remain in space for long periods of time with reduced number of team members necessitate deployment of comprehensive clinical-decision support systems aboard the space station, to preserve and maintain the well-being of the crew, and ensure successful execution of mission objectives and safe return to Earth. In prior work, we presented the use of Artemis, big-data analytics platform for real-time analysis of adaption to conditions of spaceflight, to assess the levels of stress imposed on the human body and identify the state of well-being and any deviation from the norm that becomes apparent prior to onset of clinical symptoms. Conventional methods of adaption assessment were limited to 5-minute windows of data, which were historically averaged to a single hourly and daily value. The capability of Artemis to support analysis of high-frequency, high-volume and high-velocity data present new opportunities for analysis of heart rate variability during spaceflight. As such, we propose the use of a 5-minute sliding window-based analysis of heart rate variability for assessment of adaption during spaceflight. This method would support investigation of stressor-induced responses (i.e. physical load, task activity, environmental) to help identify the exact onset of the highest strain of regulatory mechanisms and assess activity of various components of the autonomic nervous system. In...
Yeung, J & McGregor, C 2019, 'Analyzing countermeasure effectiveness utilizing big data analytics for space medicine decision support: A case study', Proceedings of the International Astronautical Congress, IAC, International Astronautical Congress, Washington D.C.
Copyright © 2019 by the International Astronautical Federation (IAF). All rights reserved. The physiological health and wellbeing of every individual crew member is critical to the success of any long duration space mission. In the most predominant space travel in recent years that are the expeditions aboard the International Space Station (ISS), astronaut's physiological data, psychological surveyed data, and the spacecraft's habitable environmental data are periodically monitored by Mission Control, while also providing a range of data for retrospective research studies. This has led to the optimization of onboard environmental control and life support systems, countermeasure exercise programs, and preventive measures, extending human space travel capacities from 90 minutes in 1961 to 180 days or even a year for current day ISS expeditions. Although current methodologies help minimize health impacts for the astronauts pre-flight, during, and post-flight, these impacts are not detected in real-time and there is much that remain unknown for longer duration missions that will last 2-3 years, such as one to Mars. Acquired physiological data from existing onboard equipment is still monitored retrospectively and issues such as intracranial pressure resulting in vision changes for astronauts during spaceflight and post-flight still prevail. Behavioural health and psychological effects due to the isolation, confinement, and social impacts with other astronauts in the spacecraft for periods longer than current expeditions also still remain. Such health and well-being implications are critical for the astronauts themselves to comprehend given the autonomous nature of every mission into space, therefore Autonomous Medical Care development is critical. In recent research, advanced prognostic health management enabled by the online analytics platform, Artemis, has demonstrated its potential in determining health states of astronauts utilizing heart rate variability (HRV) da...
Inibhunu, C & Am, CMG 2018, 'State based hidden markov models for temporal pattern discovery in critical care', 2018 IEEE Life Sciences Conference, LSC 2018, pp. 77-80.View/Download from: Publisher's site
© 2018 IEEE. We are studying the challenge of finding a good set of features that represent well the temporal aspects in time series data. We argue that discovery of such features could be crucial to understanding hidden relationships in data. In particular, in critical care where time oriented data is generated every second on patients physiological features, discovery of any hidden relationships could aid in discovery of unknown and potentially life threatening conditions before they happen. Additionally, this discovery could help in better dissemination of healthcare services leading to better outcomes and experiences for patients. To facilitate this process, this research explores two research questions; (a) can discovery of temporal relationships in data help in learning hidden aspects in differing patient cohort and (b) with respect to elderly patients receiving telehealth services, can detection of abnormal patterns help in identifying patients at risk of adverse events before they happen. In this paper, we introduce a model for temporal pattern mining by; (1) applying principles from finite state machines augmented with hidden markov models and temporal abstraction for identifying temporal relations in data, (2) generating temporal patterns by augmenting similar relationships, (3) formulating a process for mining frequently occurring temporal patterns and (4) using the resulting mined patterns to build a temporal classification system. Such a classification system can be effective at characterizing normal and abnormal behaviors in patients data and flag when a patient is at risk of a potential adverse event.
Inibhunu, C & McGregor, C 2018, 'Fusing dimension reduction and classification for mining interesting frequent patterns in patients data', Machine Learning and Data Mining in Pattern Recognition (LNAI), International Conference on Machine Learning and Data Mining in Pattern Recognition, Springer, New York, NY, USA, pp. 1-15.View/Download from: Publisher's site
© Springer International Publishing AG, part of Springer Nature 2018. Vast amounts of data are collected about elderly patients diagnosed with chronic conditions and receiving care in telehealth services. The potential to discover hidden patterns in the collected data can be crucial in making effective decisions on dissemination of services and lead to improved quality of care for patients. In this research, we investigate a knowledge discovery method that applies a fusion of dimension reduction and classification algorithms to discover interesting patterns in patient data. The research premise is that discovery of such patterns could help explain unique features about patients who are likely or unlikely to have an adverse event. This is a unique and innovative technique that utilizes the best of probability, rules, random trees and association algorithms for; (a) feature selection, (b) predictive modelling and (c) frequent pattern mining. The proposed method has been applied in a case study context to discover interesting patterns and features in patients participating in telehealth services. The results of the models developed shows that identification of best feature set can lead to accurate predictors of adverse events as well as effective in generation of frequent patterns and discovery of interesting features in varying patient cohort.
Prysyazhnyuk, A & McGregor, C 2018, 'Spatio-temporal visualisation of big data analytics during spaceflight', Proceedings of the International Astronautical Congress, IAC.
Copyright © 2018 by the International Astronautical Federation (IAF). All rights reserved. Technological advancements continue to extend the capacity of clinical decision support aboard the spacecraft, while improve physiological monitoring practices, presenting new opportunities for clinical discovery and early detection monitoring. Preservation of health and performance of astronauts remains paramount for the success of the mission and safety of the entire crew. Increasing scientific evidence demonstrates effectiveness of the use of big data analytics to support provision of medical care in space, providing the necessary tools for development of an autonomous comprehensive clinical decision support system. In prior work, the big data analytics framework, known as the Artemis, was presented, demonstrating its capacity to analyse large volumes of physiological data streams, which could be effectively combined with other relevant clinical and environmental data. Preliminary studies focused on re-engineering of algorithms assessing adaption to enable them to run within an Online Analytics component of the Artemis platform, to assess the level of wellness and tolerance of adaptation mechanisms to the conditions of spaceflight, in real-time. Conventional data visualisation methods limited representation of data to 2-dimensional scatter graphs, which depicted the dynamicity of functional states, yet provided no task-specific or temporal detail, hindering the ability to understand the trajectory of changes that occur in response to changing physiological and environmental conditions. The ability of the Artemis platform to support real-time analytics has necessitated exploration of new data visualization techniques, to enable accurate representation of the functional state of the body, while depicting the trajectory of movement, signifying deviation from the norm and the risk of development of pathology. A spatio-temporal visualization technique for representation of bi...
Prysyazhnyuk, A, Mcgregor, C, Bersenev, E & Slonov, AV 2018, 'Investigation of adaptation mechanisms during five-day dry immersion utilizing big-data analytics', 2018 IEEE Life Sciences Conference, LSC 2018, IEEE Life Sciences Conference, IEEE, Montreal, QC, Canada, pp. 247-250.View/Download from: Publisher's site
© 2018 IEEE. Emerging technology continues to redefine the concept of health and human capacity to adapt to various extreme environments on Earth, as well as in space, while preserving performance and alleviating adverse effects on the human body. Technological advancements enable effective modeling of extreme environmental conditions in terrestrial facilities, demonstrating great potential for scientific discovery, modernization of available countermeasure systems and development of comprehensive software tools for clinical decision support. To date, a vast amount of knowledge has been accumulated on physiological deconditioning in response to spaceflight environment. The underlying conditions are often closely associated with maladaptation, supported by changes in heart rate variability parameters. However, existing methods do not support real-time data acquisition, processing and analytics, thereby limiting the usability of physiological data to inform clinical decision making and timely introduction of countermeasure systems. The proposed extension of Artemis, big data analytics platform and modernization of the wellness algorithm, demonstrate great potential to address limitations of existing methods, while significantly improve the provision of medical care in space or in terrestrial environments for individuals working and/or living under conditions of chronic stress. Current study demonstrates application of the proposed big-data analytics framework in a 5-day dry immersion experiment.
Vyas, K & Mcgregor, C 2018, 'The use of heart rate for the assessment of firefighter resilience: A literature review', 2018 IEEE Life Sciences Conference, LSC 2018, pp. 259-262.View/Download from: Publisher's site
© 2018 IEEE. Heart rate monitoring of the firefighters have begun to be used for job stress level assessment or firefighting training. However, resilience assessment and heart rate variability monitoring is not widely utilized on firefighters with limited feedback available through wearables. This paper presents an initial exploratory study that considers heart rate responses from firefighters in real life like emergency scenarios.
Yeung, J & Mcgregor, C 2018, 'Countermeasure data integration within autonomous space medicine: An extension to artemis in space', 2018 IEEE Life Sciences Conference, LSC 2018, pp. 251-254.View/Download from: Publisher's site
© 2018 IEEE. Health effects of space mission crewmembers due to microgravity have historically been acceptable and reversible, yet the effect of longer duration missions remain largely unknown. Expected communication blocks between the spacecraft and Mission Control on Earth preventing crew members from consulting with Earth-based doctors immediately should a medical problem arise onboard presents the potential to integrate a health analytics platform for real-time physiological monitoring. This paper proposes a design for the data integration of current medical support and countermeasure equipment that collect physiological data from astronauts onboard the ISS with an existing platform to enable predictive and diagnostic analytic provisions.
Balaji, S, Patil, M & McGregor, C 2017, 'A Cloud Based Big Data Based Online Health Analytics for Rural NICUs and PICUs in India: Opportunities and Challenges', Proceedings - IEEE Symposium on Computer-Based Medical Systems, pp. 385-390.View/Download from: Publisher's site
© 2017 IEEE. High frequency physiological data has great potential to provide new insights for many conditions patients can develop in critical care when utilized by Big Data Analytics based Clinical Decision Support Systems, such as Artemis. Artemis was deployed in NICU at SickKids Hospital in Toronto in August 2009. It employs all the potentiality of big data. Both original data together with newly generated analytics is stored in the data persistence component of Artemis. Real-time analytics is performed in the Online Analytics component. The knowledge extraction component of the system takes care of data mining which is enabled to support clinical research for various conditions. Artemis to date has been utilized in three different implementations. However the use of Artemis still holds many challenges for lower resource settings. This research demonstrates the challenges and opportunities to use Artemis cloud as a cloud computing based Health Analytics-as-a-Service approach for the provision of remote real-time patient monitoring for low resource settings. We present case study research to demonstrate the implications, opportunities and challenges of utilizing Artemis in a low resource setting for small and remote pediatric critical care units viz NICU/PICU in India. Utilizing potentiality of big data within pediatric intensive care units has great potential to improve healthcare in these low resource settings.
Choi, Y & McGregor, C 2017, 'A Flexible Parental Engaged Consent Model for the Secondary Use of Their Infant's Physiological Data in the Neonatal Intensive Care Context', Proceedings - 2017 IEEE International Conference on Healthcare Informatics, ICHI 2017, IEEE International Conference on Healthcare Informatics, IEEE, Park City, UT, USA, pp. 502-507.View/Download from: Publisher's site
© 2017 IEEE. The secondary use of health data, especially the use of physiological data for research holds many opportunities for improving the current understanding of neonatal conditions. As a neonate is unable to provide their consent regarding participation in research studies, a substitute decision maker (SDM) must provide parental or legal guardian consent. However it has been well documented that there are many emotional, mental and physical challenges associated with the parental consent process in the neonatal intensive care unit (NICU). It is proposed that a flexible parental engaged consent model could help alleviate some of these issues by providing parents with the ability to choose and change their clinical engagement level preference for their infant's participation in research at their convenience at any point in time. In this paper, an extension to Service based Multidimensional Temporal Data Mining Framework (STDMn0) to allow for the functionality of flexible patient or surrogate consent is presented based on the use of a flexible consent model initially proposed by Heath . This functionality is demonstrated via an example implementation for a generic retrospective research study in the NICU setting.
Fernando, KES, Mcgregor, C & James, AG 2017, 'CRISP-TDM0for standardized knowledge discovery from physiological data streams: Retinopathy of prematurity and blood oxygen saturation case study', Proceedings of the 2017 IEEE Life Sciences Conference, LSC 2017, IEEE Life Sciences Conference, IEEE, Sydney, NSW, Australia, pp. 226-229.View/Download from: Publisher's site
© 2017 IEEE. The CRoss Industry Standard Process for Temporal Data Mining (CRISP-TDM) that supports physiological stream temporal data mining and CRISP-DM0 that supports null hypothesis driven confirmatory data mining in combination was proposed by prior research. This combined CRISP-TDM0 is utilised as the standardised approach to managing, reporting and performing retrospective clinical research and is designed to solve the limitation in knowledge discovery amongst physiological data streams . The temporal abstractions (TA) of high fidelity blood oxygenation saturation (SpO2) levels of nine premature neonates are analysed using data collected by the Artemis Platform that complies with the Big Data concept  and correlated with Retinopathy of Prematurity (ROP) data. The hourly SpO2, TA pattern visualisation manifested three clusters and this is further supported by mathematical review of time percentage spent in target, below and over oxygenation. Clustering based on ROP stage and gestational age identified probable association within these three clusters. However known risk factors showed no association with ROP.
Inibhunu, C, Schauer, A, Redwood, O, Clifford, P & Mcgregor, C 2017, 'Predicting hospital admissions and emergency room visits using remote home monitoring data', 2017 IEEE Life Sciences Conference, LSC 2017, IEEE Life Sciences Conference, pp. 282-285.View/Download from: Publisher's site
© 2017 IEEE. The costs of lengthy hospital admissions (HA) and multiple emergency room visits (ER Visits) from patients with conditions such as heart failure (HF) and chronic obstructive pulmonary disease (COPD) can place a significant burden on healthcare systems. Understanding the various factors contributing to hospitalization and ER visits could aid cost-effective management in the delivery of services leading to potential improvement on quality of life for patients. This can be facilitated by collecting data using remoting patient monitoring (RPM) services and using analytics to discover important factors about patients. This paper presents our research that utilizes predictive modeling to determine key factors that are significant determinant to hospitalization and multiple ER Visits. The results shows that gender, past medical history and vital status are key factors to hospital admissions and ER Visits. Additionally, when a factor to indicate the period before, during and after an ER Visits was included, the resulting model shows a very high likelihood ratio and improved p values on all vital status. Our results shows that more research is needed to fully understand the temporal patterns among variables during hospitalization or ER visit.
Inibhunu, C, Schauer, A, Redwood, O, Clifford, P & Mcgregor, C 2017, 'The impact of gender, medical history and vital status on emergency visits and hospital admissions: A remote patient monitoring case study', 2017 IEEE Life Sciences Conference, LSC 2017, IEEE Life Sciences Conference, IEEE, Sydney, NSW, Australia, pp. 278-281.View/Download from: Publisher's site
© 2017 IEEE. Remote Program Monitoring (RPM) is considered to have potential to improve the quality of life on patients diagnosed with cardiac conditions such as heart failure (HF) and chronic obstructive pulmonary disease (COPD). Remote collection and analysis of patients data could aid in effective decision making on necessary care needed by patients monitored. This could lead to reduction on healthcare costs as well as improved outcomes for the patients. As a component of our predictive analytics research, this paper presents results of remote patient monitoring study of patients from the Cardiac Clinic of Southlake Regional Health Centre who were referred to WeCare for home based monitoring. Results indicate statistically significant evidence on impact of gender, medical history and vital status as risk factors for subsequent hospitalization and multiple emergency room visits.
McGregor, C, Bonnis, B, Stanfield, B & Stanfield, M 2017, 'Integrating Big Data analytics, virtual reality, and ARAIG to support resilience assessment and development in tactical training', 2017 IEEE 5th International Conference on Serious Games and Applications for Health, SeGAH 2017.View/Download from: Publisher's site
© 2017 IEEE. Combat tactical training activities utilising virtual reality environments are being used increasingly to create training scenarios to promote resilience against stressors and to enable standardized training scenarios to allow trainees to learn techniques for various stressors. Resilience is an important component for mental health. However, assessment of the trainees' response to these training activities has either been limited to various pre and post training assessment metrics or collected in parallel during experiments and analysed after collection rather than in real-time. New Big Data approaches have the potential to provide real-time analytics. We have created a Big Data analytics platform, Athena, that in real-time acquires data from a first person shooter military combat simulation game, ArmA 3, as well as the data ArmA 3 sends to the muscle stimulation component of a multisensory garment, ARAIG that provides on the body feedback to the wearer for communications, weapon fire and being hit and integrates that data with physiological response data such as heart rate, breathing behaviour and blood oxygen saturation. We present results from our initial pilot study from an ethics approved equipment integration study. Our approach is equally applicable for Virtual Reality Graded Exposure Therapy with physiological monitoring.
McGregor, C, Orlov, O, Baevsky, R, Chernikova, A & Rusanov, V 2917, 'Big data analytics for continuous assessment of astronaut health risk and its application to human-in-the-loop (HITL) related aerospace', Proceedings of the 19th AIAA Non-Deterministic Approaches Conference, 2017, AIAA Non-Deterministic Approaches Conference, ARC, Grapevine, Texas.View/Download from: Publisher's site
© 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. The man-instrumentation-equipment-vehicle-environment ecosystem is complex in aerospace missions. Health status of the individual has important implications on decision making and performance that should be factored into assessments for probability of success/risk of failure both in offline and real-time models. To date probabilistic models have not considered the dynamic nature of health status. Big Data analytics is enabling new forms of analytics to assess health status in real-time. There is great potential to integrate dynamic health status information with platforms assessing risk and the probability of success for dynamic individualized real-time probabilistic predictive risk assessment. In this research we present an approach utilizing Big Data analytics to enable continuous assessment of astronaut health risk and show its implications for integration with HITL related aerospace mission.
Naik, T, Mcgregor, C & James, A 2017, 'Automated partial premature infant pain profile scoring using big data analytics', 2017 IEEE Life Sciences Conference, LSC 2017, IEEE Life Sciences Conference, IEEE, Sydney, NSW, Australia, pp. 246-249.View/Download from: Publisher's site
© 2017 IEEE. Lack of valid and reliable pain assessment in the neonatal population has become a significant challenge in the Neonatal Intensive Care Unit (NICU). In an attempt to forego the manual pain scoring system, this paper presents an initial framework to automate a partial pain score for newborn infants using big data analytics that automates the analysis of high speed physiological data. An ethically approved retrospective clinical research study was performed to calculate Artemis Premature Infant Pain Profile (APIPP) scores from premature infant data collected from the Artemis platform. Using the Premature Infant Pain Profile (PIPP) as the gold standard scale, scoring techniques were automated to create data abstractions from gestational age and the physiological streams of Heart Rate (HR) and Oxygen Saturation (SpO2). These were then brought together to compute an automated partial pain score. APIPP was retrospectively compared with the PIPP which was manually scored by nursing staff at The Hospital for Sick Children, Toronto. Differences within both the scales were evaluated and analysed by creating a data model. Future research will focus on the clinical validation of this work by implementing this work into a clinical decision support system (CDSS) named Artemis.
Orlov, O, McGregor, C, Baevsky, R, Chernikova, A, Prysyazhnyuk, A & Rusanov, V 2017, 'Perspective use of the technologies for big data analysis in manned space flights on the international space station', Proceedings of the International Astronautical Congress, IAC, pp. 1951-1960.
Copyright © 2017 by the International Astronautical Federation (IAF). All rights reserved. Recent technologies in the area of Big Data analytics which provide fast and effective review of various and diverse files of information arriving from different sources are being developed increasingly. Various new software are being proposed to provide useful results in this area. Such technologies are the important stimulus of modern scientific and technical progress, in particular in the field of development of piloted space flights. In this publication we present the prospects of the use of Big Data analytics technology in a system of medical control of crews of the International space station (ISS). Today there is an active accumulation of experience of piloted space flights on ISS where the international scientific and technical cooperation actively develops. An important step withm this direction is the organisation of a new joint Russian-Canadian space experiment "Cosmocard 2018" It will build on the Russian experiment "Cosmocard" which is currently being carried out on the ISS since September, 2014. In this project we have begun work for the modernisation of the software for the onboard computer which will enable the estimation in real-time of a mode of state of health of members of the crew. The Artemis platform, a Big Data analytics platform proposed by McGregor for the analysis of great volumes of physiological and other environmental data, will be used for this purpose. We have begun to reengrneer algorithms for definition of a functional condition of an organism and risk of development of diseases developed previously by the Institute of Biomedical Problems of the Russian Academy of Sciences to run in real-time within the structure of the new software for the onboard computer that is based on Artemis. These new algorithms will be tested, in the beginning, during simulation experiments with long isolation using the same "Cosmocard" physiological monitoring dev...
Prysyazhnyuk, A, Baevsky, R, Berseneva, A, Chernikova, A, Luchitskaya, E, Rusanov, V & Mcgregor, C 2017, 'Big data analytics for enhanced clinical decision support systems during spaceflight', 2017 IEEE Life Sciences Conference, LSC 2017, IEEE Life Sciences Conference, IEEE, Sydney, NSW, Australia, pp. 296-299.View/Download from: Publisher's site
© 2017 IEEE. Recent advancements in the field of space medicine and technology have extended the boundaries of space travel, presenting humankind with the ability to explore undiscovered habitats. As humans embark on long range missions, adaptation mechanisms will be put to the test, challenging provision of medical care in space. To date, a vast amount of knowledge has been accumulated through a series of experiments, both in terrestrial simulation environments and space missions on the ISS. As a result, functional health state algorithm has been developed and validated by IBMP, to identify transitional states between health and disease. Significant limitations on provision of medical care in space are imposed due to retrospective data processing and analysis techniques. Some of these limitations can be addressed by the proposed instantiation of the functional state algorithm within the Online Analytics component of the Artemis platform, to enhance clinical decision support systems during spaceflight.
Hollmén, J, Spiliopoulou, M, Kane, B, Marshall, A, Soda, P, Antani, S & McGregor, C 2016, 'Preface', Proceedings - IEEE Symposium on Computer-Based Medical Systems, pp. xiii-xiv.View/Download from: Publisher's site
Inibhunu, C & McGregor, C 2016, 'Machine learning model for temporal pattern recognition', 2016 IEEE EMBS International Student Conference: Expanding the Boundaries of Biomedical Engineering and Healthcare, ISC 2016 - Proceedings.View/Download from: Publisher's site
© 2016 IEEE. Temporal abstraction and data mining are two research fields that have tried to synthesis time oriented data and bring out an understanding on the hidden relationships that may exist between time oriented events. In clinical settings, having the ability to know the hidden relationships on patient data as they unfold could help save a life by aiding in detection of conditions that are not obvious to clinicians and healthcare workers. Understanding the hidden patterns is a huge challenge due to the exponential search space unique to time-series data. In this paper, we propose a temporal pattern recognition model based on dimension reduction and similarity measures thereby maintaining the temporal nature of the raw data.
Izaddoost, A & McGregor, C 2016, 'Enhance Network Communications in a Cloud-based Real-time Health Analytics Platform Using SDN', 2016 IEEE INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI), IEEE International Conference on Healthcare Informatics (ICHI), IEEE, Chicago, IL, pp. 388-391.View/Download from: Publisher's site
Jalali, R, Dauda, A, El-Khatib, K, McGregor, C & Surti, C 2016, 'An architecture for health data collection using off-the-shelf health sensors', 2016 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2016 - Proceedings.View/Download from: Publisher's site
© 2016 IEEE. Nowadays, many people, and not only the ones with health problems are being more health conscious. With the advent of sensor based technologies, it has become possible to create wearable wireless biometric sensor networks, known as Body Sensor Networks (BSNs) which allow people to collect their health data and send it remotely for further analysis and storage. Research has shown that the use of BSNs enables remote wireless diagnosis of various health conditions. In this paper, we propose a novel layered architecture for smart healthcare system where health community service providers, patients, doctors and hospitals have access to real time data which has been gathered using various sensory mechanisms. An experimental case study has been implemented for evaluation. Early results show benefits of this system in improving the quality of health care.
Kamaleswaran, R, James, A, Collins, C & McGregor, C 2016, 'CoRAD: Visual Analytics for Cohort Analysis', 2016 IEEE INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI), IEEE International Conference on Healthcare Informatics (ICHI), IEEE, Chicago, IL, pp. 517-526.View/Download from: Publisher's site
McGregor, C & Bonnis, B 2016, 'Big Data Analytics for Resilience Assessment and Development in Tactical Training Serious Games', 2016 IEEE 29TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), 29th IEEE International Symposium on Computer-Based Medical Systems (CBMS), IEEE, NORTH IRELAND, pp. 158-162.View/Download from: Publisher's site
McGregor, C, Bonnis, B, Stanfield, B & Stanfield, M 2016, 'Design of the ARAIG haptic garment for enhanced resilience assessment and development in tactical training serious games', IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin, pp. 214-217.View/Download from: Publisher's site
© 2016 IEEE. First person shooter virtual reality games have begun to be used for serious games for military or civilian tactical training for new approaches for resilience assessment and development as part of new approaches for mental health training. However, sensory stimulation has been largely constrained to visual and auditory sensations with limited tactile feedback through haptic controllers. This paper presents a design for the ARAIG haptic garment for enhanced resilience assessment and development in tactical training serious games.
© 2016 IEEE. Clarifying and evolving the PHM for Astronauts concept, introduced in , this conceptual paper focuses on particular PHM-based solutions to bring Human Health and Performance (HH&P) technologies to the required technology readiness level (TRL) in order to mitigate the HH&P risks of manned space exploration missions. This paper discusses the particular PHM-based solutions for some HH&P technologies that are, namely by NASA designation, the Autonomous Medical Decision technology and the Integrated Biomedical Informatics technology. Both of the technologies are identified as essential ones in NASA's integrated technology roadmap for the Technology Area 06: Human Health, Life Support, and Habitation Systems. The proposed technology solutions are to bridge PHM, an engineering discipline, to HH&P domain in order to mitigate the risks by focusing on efforts to reduce countermeasure mass and volume and drive the risks down to an acceptable level. The Autonomous Medical Decision technology is based on wireless handheld devices and is a result of a paradigm shift from tele-medicine to that of health support autonomy. The Integrated Biomedical Informatics technology is based on Crew Electronic Health Records (CEHR) system with predictive diagnostics capability developed for crew members rather than for healthcare professionals. The paper explores the proposed PHM-based solutions on crew health maintenance in terms of predictive diagnostics providing early and actionable real-time warnings of impending health problems that otherwise would have gone undetected.
Jalali, R, El-khatib, K & McGregor, C 2015, 'Smart City Architecture for Community Level Services Through the Internet of Things', 2015 8TH INTERNATIONAL CONFERENCE ON INTELLIGENCE IN NEXT GENERATION NETWORKS, 18th International Conference on Intelligence in Next Generation Networks, IEEE, Paris, FRANCE, pp. 108-113.
McGregor, C 2015, 'A framework for online health analytics for advanced prognostics and health management of astronauts', 2015 IEEE Aerospace Conference, 2015 IEEE Aerospace Conference, IEEE.View/Download from: Publisher's site
McGregor, C, Bonnis, B, Stanfield, B & Stanfield, M 2015, 'A Method for Real-time Stimulation and Response Monitoring using Big Data and its Application to Tactical Training', 2015 IEEE 28TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), 28th IEEE International Symposium on Computer-Based Medical Systems (CBMS), IEEE COMPUTER SOC, Univ Sao Paulo, Sao Paulo, BRAZIL, pp. 169-170.View/Download from: Publisher's site
McGregor, C, Heath, J & Choi, Y 2015, 'Streaming Physiological Data: General Public Perceptions of Secondary Use and Application to Research in Neonatal Intensive Care', MEDINFO 2015: EHEALTH-ENABLED HEALTH, 15th World Congress on Health and Biomedical Informatics (MEDINFO), IOS PRESS, Int Med Informat Assoc, Brazilian Hlth Informat Soc, Sao Paulo, BRAZIL, pp. 453-457.View/Download from: Publisher's site
Nizami, S, Green, JR & McGregor, C 2015, 'An Artifact Detection Framework for Clinical Decision Support Systems', WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING, 2015, VOLS 1 AND 2, World Congress on Medical Physics and Biomedical Engineering, SPRINGER INTERNATIONAL PUBLISHING AG, Toronto, CANADA, pp. 1393-1396.View/Download from: Publisher's site
Bressan, N, McGregor, C, Smith, K, Lecce, L & James, A 2014, 'Heart rate variability as an indicator for morphine pharmacokinetics and pharmacodynamics in critically ill newborn infants', 2014 36TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 36th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), IEEE, Chicago, IL, pp. 5719-5722.
Monitoring the health and well-being of human beings during any manned spaceflight is a critical aspect of the space mission. To date this has been done almost exclusively with telemetry to ground stations and monitoring of the physiological data by physicians. With lunar and Mars missions the transmission latency become problematic, and in additional to longer latency, Mars missions would also be subject to more restricted bandwidth availability and to blackout periods due to the normal rotation of Mars when the lander would be on the far side of the planet relative to earth for roughly half of each Mars solar day. While these blackout period could be reduced or removed with relay satellite in Martian orbit, this may not be practical for early missions to Mars. As such, Autonomous Medical Care has been identified by NASA as one of the top priority technologies to be developed for Mars missions, with seven Risk Categories with that area. Two of these are Monitoring and Prevention; and Medical Informatics, Technologies and Support Systems. In this paper, the Artemis platform, which was developed originally for real-time diagnostics in neonatal intensive care is presented as a solution to these areas of Autonomous Medical Care for Mars missions. This platform has the capability, in addition to real-time diagnostics, to provide supervisory medical monitoring, modularity in deployment of specialized diagnostic algorithms and also the offline (earth-based) development and deployment of new algorithms based on additional mission needs. The platform and these capabilities are described, along with examples of its use. Furthermore, its requirements in terms of resources within the inherently limited resources of a long space mission are also presented and analysed, and a proposed physical architecture for both the space and ground control components are proposed. © 2014 IEEE.
Eklund, JM, Fontana, N, Pugh, E, McGregor, C, Yielder, P, James, A, Keyzers, M, Hahn, C & McNamara, P 2014, 'Automated Sleep-Wake Detection in Neonates from Cerebral Function Monitor Signals', 2014 IEEE 27TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), 27th IEEE International Symposium on Computer-Based Medical Systems (CBMS), IEEE, Icahn Sch Med, New York, NY, pp. 22-27.View/Download from: Publisher's site
Greer, R, Olivier, C, Pugh, JE, Eklund, JM & McGregor, C 2014, 'Remote, Real-Time Monitoring and Analysis of Vital Signs of Neonatal Graduate Infants', 2014 36TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 36th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), IEEE, Chicago, IL, pp. 1382-1385.
Hayes, G, El-Khatib, K & McGregor, C 2014, 'Supporting health informatics with platform-as-a-service cloud computing', Lecture Notes in Electrical Engineering, pp. 1149-1158.View/Download from: Publisher's site
Recent progression in health informatics data analysis has been impeded due to lack of hospital resources and computation power. To remedy this, some researchers have proposed a cloud-based web service patient monitoring system capable of providing offsite collection, analysis, and dissemination of remote patient physiological data. Unfortunately, some of these cloud services are not effective without utilizing next-generation hardware management techniques. In order to make cloud based patient monitoring a reality, this paper shows how leveraging an underlying platform-as-a-service (PaaS) cloud model can provide integration with web service patient monitoring systems while providing high availability, scalability, and security. © Springer Science+Business Media Dordrecht 2014.
Huang, W, McGregor, C & James, A 2014, 'A Comprehensive Framework Design for Continuous Quality Improvement within the Neonatal Intensive Care Unit: Integration of the SPOE, CRISP-DM and PaJMa Models', 2014 IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS (BHI), IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), IEEE, Valencia, SPAIN, pp. 289-292.
Kamaleswaran, R & McGregor, C 2014, 'A Real-Time Multi-Dimensional Visualization Framework For Critical And Complex Environments', 2014 IEEE 27TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), 27th IEEE International Symposium on Computer-Based Medical Systems (CBMS), IEEE, Icahn Sch Med, New York, NY, pp. 325-328.View/Download from: Publisher's site
Khazaei, H, McGregor, C, Eklund, M, El-Khatib, K & Thommandram, A 2014, 'Toward a Big Data Healthcare Analytics System: A Mathematical Modeling Perspective', 2014 IEEE World Congress on Services, 2014 IEEE World Congress on Services (SERVICES), IEEE.View/Download from: Publisher's site
Naik, T, Thommandram, A, Fernando, KES, Bressan, N, James, A & McGregor, C 2014, 'A Method for a Real-time Novel Premature Infant Pain Profile using High Rate, High Volume Physiological Data Streams', 2014 IEEE 27TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), 27th IEEE International Symposium on Computer-Based Medical Systems (CBMS), IEEE, Icahn Sch Med, New York, NY, pp. 34-37.View/Download from: Publisher's site
Shafiq, H, McGregor, C & Murphy, B 2014, 'The Impact of Cervical Manipulation on Heart Rate Variability', 2014 36TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 36th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), IEEE, Chicago, IL, pp. 3406-3409.
Thommandram, A, Eklund, JM, McGregor, C, Pugh, JE & James, AG 2014, 'A Rule-Based Temporal Analysis Method for Online Health Analytics and its Application for Real-Time Detection of Neonatal Spells', 2014 IEEE INTERNATIONAL CONGRESS ON BIG DATA (BIGDATA CONGRESS), 3rd IEEE International Congress on Big Data, IEEE, Anchorage, AK, pp. 470-477.View/Download from: Publisher's site
Wang, XL, Eklund, JM & McGregor, C 2014, 'Parametric Power Spectrum Analysis of ECG Signals for Obstructive Sleep Apnoea Classification', 2014 IEEE 27TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), 27th IEEE International Symposium on Computer-Based Medical Systems (CBMS), IEEE, Icahn Sch Med, New York, NY, pp. 8-13.View/Download from: Publisher's site
Bressan, NA, James, A & McGregor, C 2013, 'Integration of Drug Dosing Data with Physiological Data Streams using a Cloud Computing Paradigm', 2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), IEEE, Osaka, JAPAN, pp. 4175-4178.
Kamaleswaran, R, Thommandram, A, Zhou, Q, Eklund, M, Cao, Y, Wang, WP & McGregor, C 2013, 'Cloud framework for real-time synchronous physiological streams to support rural and remote critical care', Proceedings of CBMS 2013 - 26th IEEE International Symposium on Computer-Based Medical Systems, pp. 473-476.View/Download from: Publisher's site
We present a method for transmission and processing of real-time trans-continental medical data streams. We apply fundamentals of existing network technologies to create a secure tunnel from a remote hospital through an open-network to the Artemis Cloud. We capture and store incoming 1Hz data stream in our real-time event stream processor to allow for online real-time monitoring of the patient status. The contributions of this paper extend the Critical Care as a Service paradigm by incorporating remote monitoring centers. The results establish feasibility of the system to support real-time monitoring. However, existing protocols were required significant optimization to account for variability in throughput and availability of the network. © 2013 IEEE.
Kamaleswaran, R, Thommandram, A, Zhou, Q, Eklund, M, Cao, Y, Wang, WP & McGregor, C 2013, 'Cloud framework for real-time synchronous physiological streams to support rural and remote Critical Care', Proceedings - IEEE Symposium on Computer-Based Medical Systems, pp. 473-476.
We present a method for transmission and processing of real-time trans-continental medical data streams. We apply fundamentals of existing network technologies to create a secure tunnel from a remote hospital through an open-network to the Artemis Cloud. We capture and store incoming 1Hz data stream in our real-time event stream processor to allow for online real-time monitoring of the patient status. The contributions of this paper extend the Critical Care as a Service paradigm by incorporating remote monitoring centers. The results establish feasibility of the system to support real-time monitoring. However, existing protocols were required significant optimization to account for variability in throughput and availability of the network. © 2013 IEEE.
Monitoring the health and wellbeing of astronauts during spaceflight is an important aspect of any manned mission. To date the monitoring has been based on a sequential set of discontinuous samplings of physiological data to support initial studies on aspects such as weightlessness, and its impact on the cardiovascular system and to perform proactive monitoring for health status. The research performed and the real-time monitoring has been hampered by the lack of a platform to enable a more continuous approach to real-time monitoring. While any spaceflight is monitored heavily by Mission Control, an important requirement within the context of any spaceflight setting and in particular where there are extended periods with a lack of communication with Mission Control, is the ability for the mission to operate in an autonomous manner. This paper presents a platform to enable real-time astronaut monitoring for prognostics and health management within space medicine using online health analytics. The platform is based on extending previous online health analytics research known as the Artemis and Artemis Cloud platforms which have demonstrated their relevance for multi-patient, multi-diagnosis and multi-stream temporal analysis in real-time for clinical management and research within Neonatal Intensive Care. Artemis and Artemis Cloud source data from a range of medical devices capable of transmission of the signal via wired or wireless connectivity and hence are well suited to process real-time data acquired from astronauts. A key benefit of this platform is its ability to monitor their health and wellbeing onboard the mission as well as enabling the astronaut's physiological data, and other clinical data, to be sent to the platform components at Mission Control at each stage when that communication is available. As a result, researchers at Mission Control would be able to simulate, deploy and tailor predictive analytics and diagnostics during the same spaceflight for...
McGregor, C 2013, 'Wearable monitors on babies: Big data saving little people', 2013 IEEE International Symposium on Technology and Society (ISTAS): Social Implications of Wearable Computing and Augmediated Reality in Everyday Life, 2013 IEEE International Symposium on Technology and Society (ISTAS), IEEE.View/Download from: Publisher's site
McGregor, C, James, A, Eklund, M, Sow, D, Ebling, M & Blount, M 2013, 'Real-time Multidimensional Temporal Analysis of Complex High Volume Physiological Data Streams in the Neonatal Intensive Care Unit', MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2, 14th World Congress on Medical and Health Informatics (MEDINFO), IOS PRESS, Copenhagen, DENMARK, pp. 362-366.View/Download from: Publisher's site
Thommandram, A, Eklund, JM & McGregor, C 2013, 'Detection of Apnoea from Respiratory Time Series Data Using Clinically Recognizable Features and kNN Classification', 2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), IEEE, Osaka, JAPAN, pp. 5013-5016.
Thommandram, A, Pugh, JE, Eklund, JM, McGregor, C & James, AG 2013, 'Classifying Neonatal Spells Using Real-Time Temporal Analysis of Physiological Data Streams: Algorithm Development', 2013 IEEE POINT-OF-CARE HEALTHCARE TECHNOLOGIES (PHT), 1st IEEE-EMBS Special Topic Conference on Point-of-Care (POCT) Healthcare Technologies (PHT), IEEE, Bangalore, INDIA, pp. 240-243.
Bressan, N, James, A & McGregor, C 2012, 'Trends and opportunities for integrated real time neonatal clinical decision support', Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012, pp. 687-690.View/Download from: Publisher's site
Neonatal Intensive Care Unit maintain and support life during the critical period of premature development. This research presents the challenges, trends and opportunities for integrated real time neonatal clinical decision support. We demonstrated this potential using environment known as Artemis, a clinical decision support system. A review of the current devices in the intensive care unit and neonatal practice shows the current environment and our perspective for the future of the neonatal clinical decision support. The study demonstrates that Artemis will be able to incorporate new data streams from infusion pumps, EEG monitors and cerebral oxygenation monitors innovating the practice and improving the clinical support. © 2012 IEEE.
Kamaleswaran, R & McGregor, C 2012, 'CBPSP: Complex business processes for stream processing', 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering: Vision for a Greener Future, CCECE 2012.View/Download from: Publisher's site
This paper presents an extension called the Complex Business Processes for Stream Processing (CBPsp) to the Solution Manager Service (SMS) framework to support the definition and enactment of complex business processes for event stream processing. The critical care of an infant involves multiple caregivers performing complex activities, thus a system that is capable of presenting complex business processes to produce context sensitive real-time support is required. The proposed system CBPsp, supports the integration of heterogeneous sequential business processes and distinct data types to produce meaningful business objective driven outputs in real-time. Two research contributions are delivered. The first contribution is the real-time integration of synchronous and asynchronous streams in a loosely coupled model based on Service-Oriented Architecture principles. The second contribution is the definition and enactment of complex business processes along with their meaningful business objectives at the point of analysis within data stream management systems. © 2012 IEEE.
Kamaleswaran, R & McGregor, C 2012, 'Integrating complex business processes for knowledge-driven clinical decision support systems', Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 1306-1309.View/Download from: Publisher's site
This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS. © 2012 IEEE.
Kamaleswaran, R, McGregor, C & James, A 2012, 'A novel framework for event stream processing of clinical practice guidelines', Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012, pp. 933-936.View/Download from: Publisher's site
Clinical Decision Support Systems (CDSSs) play important roles aiding in patient care; they provide accurate data analysis and timely evidence-informed recommendations. Although the availability of biomedical data continues to flourish, there have been limited translations of this type of data to information in real-time at the bedside. Existing systems have either focused on providing process-oriented or knowledge-modeled frameworks, often relying on retrospective data analysis. We have developed a framework capable of providing clinicians the ability to represent existing knowledge and processes in realtime. This framework presents a real-time environment for modeling clinical workflow processes abstracted from clinical guidelines, while applying existing knowledge to produce intelligent evidence-informed recommendations. In this paper we provide a framework to support the detection of neonatal hypoglycaemia using a design supporting the automated realtime, evidence-informed enactment of complex businessprocesses existing in clinical practice guidelines. © 2012 IEEE.
McGregor, C, Catley, C & James, A 2012, 'Variability analysis with analytics applied to physiological data streams from the neonatal intensive care unit', Proceedings - IEEE Symposium on Computer-Based Medical Systems.View/Download from: Publisher's site
Late onset neonatal sepsis (LONS) is one clinical condition that shows promise for earlier onset detection through the analysis of physiological signals. However, current work on Heart Rate Variability (HRV) analysis does not discuss the impact of narcotics and other drugs on early identification of sepsis. We present results of a pilot retrospective data mining study of neonatal intensive care unit patients using a dataset of 30 second spot readings. We derive analytics by creating temporal abstractions of hourly summaries for HRV and respiratory rate variability (RRV). Using representative patient examples, we illustrate an analytics user interface design that shows 1) the potential in using our HRV analytics for early identification of LONS with 30 second spot readings; and 2) that based on initial pilot results, reporting analytics for HRV and RRV concurrently adds value to HRV analysis by distinguishing between patients with low HRV due to imminent sepsis and those patients with low HRV due to the presence of confounding factors such as surgery and narcotics. © 2012 IEEE.
McGregor, C, Steadman, A, Percival, J & James, A 2012, 'A method for modeling health informatics capacity in patient journeys supported by interprofessional teams', Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 2790-2799.View/Download from: Publisher's site
Neonatal intensive care is one of the most complex areas of healthcare; as a result, information flow within this unit must be as efficient as possible. This paper presents initial research findings based on the use of the patient journey modeling technique known as PaJMa to audit the current state of health informatics within NICUs in Canada and internationally. In this paper, a case study from an Ontario NICU is utilized and their "Investigations" process is modeled using PaJMa. © 2012 IEEE.
O'Reilly, RD, Morrison, JP & McGregor, C 2012, 'A system for the transmission, processing and visualisation of EEG to support Irish Neonatal Intensive Care Units', 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering: Vision for a Greener Future, CCECE 2012.View/Download from: Publisher's site
A system, constructed as a "proof of concept", for providing an Irish tele-neurophysiology service is presented. It is based on a distributed architecture and capable of handling synchronous data streams from multiple Irish Neonatal Intensive Care Units. It provides Ireland with an infrastructure for overcoming factors affecting the diagnosis of neurological disorders in neonates. The system supports collaborative efforts by neurophysiologists, removes geographical constraints on expert knowledge and allows for the creation of national data stores while simultaneously supporting the trans-Atlantic processing of EEG. Technical obstacles affecting its successful implementation are outlined and solutions proposed. The implementation of such a system could significantly improve the quality of care provided to neonates. © 2012 IEEE.
Eklund, JM, Catley, C, McGregor, C & James, A 2011, 'Detection of apnoea in newborn infants using impedance respiratory wave data', Proceedings of the IASTED International Symposia on Imaging and Signal Processing in Healthcare and Technology, ISPHT 2011, pp. 90-94.View/Download from: Publisher's site
Apnoea is a serious condition that occurs frequently in prematurely born infants as well as other patients requiring critical care. At least while in the intensive care environment, these patients are provided with constant care assisted by modern medical monitoring systems. The systems record continuous data from each patient, however most of these data are not used except when a care provider observes the device directly, or when an alert - that is used to draw the attention of those same providers - is generated. This paper explores how these continuous data streams can be used in real-time to provide better alert mechanisms and diagnostics, with particular focus on the impedance respiratory waveform, a high rate physiological stream that measures the expansion and contraction of the patient's chest and is traditionally used to determine the respiratory rate. The direct use of this data stream is compared to the derived respiratory rate as a means to estimate the onset of a suspected case of apnoea.
McGregor, C 2011, 'A cloud computing framework for real-time rural and remote service of critical care', Proceedings - IEEE Symposium on Computer-Based Medical Systems.View/Download from: Publisher's site
Critical care patients in rural, remote and some urban healthcare facilities do not have the same level of access to intensivist specialist support as patients in higher care level urban critical care units (CCUs). New clinical research is also demonstrating that computationally intensive analysis of physiological data streams in near real-time has the potential to detect the onset of certain conditions earlier. The provision of clinical decision support tools, in a cost effective way to all CCUs has the potential to reduce mortality and morbidity rates, reduce critical care patient transportation between CCUs and in so doing reduce healthcare costs. This research presents Artemis Cloud, a cloud computing based Software-asa-Service and Data-as-a-Service approach for the provision of remote real-time patient monitoring and support for clinical research. This research is demonstrated using a neonatal intensive care unit case study supporting clinical research for earlier onset detection of late onset neonatal sepsis. © 2011 IEEE.
McGregor, C, Catley, C & James, A 2011, 'A process mining driven framework for clinical guideline improvement in critical care', CEUR Workshop Proceedings.
This paper presents a framework for process mining in critical care. The framework uses the CRISP-DM model, extended to incorporate temporal and multidimensional aspects (CRISP-TDMn), combined with the Patient Journey Modeling Architecture (PaJMa), to provide a structured approach to knowledge discovery of new condition onset pathophysiologies in physiological data streams. The approach is based on temporal abstraction and mining of physiological data streams to develop process flow mappings that can be used to update patient journeys; instantiated in critical care within clinical practice guidelines. We demonstrate the framework within the neonatal intensive care setting, where we are performing clinical research in relation to pathophysiology within physiological streams of patients diagnosed with late onset neonatal sepsis. We present an instantiation of the framework for late onset neonatal sepsis, using CRISP-TDMn for the process mining model and PaJMa for the knowledge representation.
Mcgregor, C, Catley, C, James, A & Padbury, J 2011, 'Next Generation Neonatal Health Informatics with Artemis', USER CENTRED NETWORKED HEALTH CARE, 23 rd Conference of the European Federation of Medical Informatics (MIE), IOS PRESS, Forum Databehandling Helsesektoren, Oslo, NORWAY, pp. 115-119.View/Download from: Publisher's site
Nizami, S, Green, JR & McGregor, C 2011, 'Service oriented architecture to support real-time implementation of artifact detection in critical care monitoring', Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 4925-4928.View/Download from: Publisher's site
The quality of automated real-time critical care monitoring is impacted by the degree of signal artifact present in clinical data. This is further complicated when different clinical rules applied for disease detection require source data at different frequencies and different signal quality. This paper proposes a novel multidimensional framework based on service oriented architecture to support real-time implementation of clinical artifact detection in critical care settings. The framework is instantiated through a Neonatal Intensive Care case study which assesses signal quality of physiological data streams prior to detection of late-onset neonatal sepsis. In this case study requirements and provisions of artifact and clinical event detection are determined for real-time clinical implementation, which forms the second important contribution of this paper. © 2011 IEEE.
Blount, M, McGregor, C, James, A, Sow, D, Kamaleswaran, R, Tuuha, S, Percival, J & Percival, N 2010, 'On the integration of an artifact system and a real-time healthcare analytics system', IHI'10 - Proceedings of the 1st ACM International Health Informatics Symposium, pp. 647-655.View/Download from: Publisher's site
As a result of advances in software technology, particularly stream computing, it is now possible to implement scalable systems capable of real-time analysis of multiple physiological data streams of multiple patients. There is a growing body of evidence showing that early onset indicators of some medical conditions can be observed as subtle changes in the physiological data streams of affected patients. These real-time healthcare analytics systems can detect the early onset indicators and thus may result in earlier detection of the medical condition which may lead to earlier intervention and improved patient outcomes. Blood draws and nasal suctioning can cause changes in the values of some physiological data stream elements. Such events, sometimes referred to as physiological stream artifacts can cause the real-time analytics systems to generate false alarms since the systems assume each data element is indicative the patient's underlying physiological condition. In order to minimize the generation of false alarms, artifact events must be captured and integrated in real time with the analytics result. We present the summary of an artifact study in a tertiary neonatal intensive care unit within a children's hospital where a real-time analytics system is being piloted as part of a clinical research study. We utilize the information gathered relating to the nature of these events and propose a framework to integrate the artifact events with the analytic results in real time © 2010 ACM.
Catley, C, Smith, K, McGregor, C, James, A & Eklund, JM 2010, 'A framework to model and translate clinical rules to support complex real-time analysis of physiological and clinical data', IHI'10 - Proceedings of the 1st ACM International Health Informatics Symposium, pp. 307-315.View/Download from: Publisher's site
We present a framework to model and translate clinical rules to support complex real-time analysis of both synchronous physiological data and asynchronous clinical data. The framework is demonstrated through a case study in a neonatal intensive care context showing how a clinical rule for detecting an apnoeic event is modeled across multiple physiological data streams in the Artemis environment, which employs IBM's InfoSphere Streams middleware to support real-time stream processing. Initial clinical hypotheses for apnoea detection are modeled using UML activity diagrams which are subsequently translated into Stream's SPADE code to be deployed in Artemis to deliver real-time decision support. Our aim is to provide a Clinical Decision Support System capable of identifying and detecting patterns in physiological data streams indicative of the onset of clinically significant conditions that that may adversely affect health outcomes. Benefits associated with our approach include: 1) reduced time and effort on the clinician's part to assess health data from multiple sources; 2) the ability to allow clinicians to control the rules-engine of Artemis to enhance clinical care within their unique environments; 3) the ability to apply clinical alerts to both synchronous and asynchronous data; and 4) the ability to continuously process data in real-time. © 2010 ACM.
Goldie, J, McGregor, C & Murphy, B 2010, 'Determining Levels of Arousal using Electrocardiography: A study of HRV during Transcranial Magnetic Stimulation', 2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10), IEEE, Buenos Aires, ARGENTINA, pp. 1198-1201.View/Download from: Publisher's site
Kamaleswaran, R, McGregor, C & Eklund, JM 2010, 'A Method for Clinical and Physiological Event Stream Processing', 2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10), IEEE, Buenos Aires, ARGENTINA, pp. 1170-1173.View/Download from: Publisher's site
Nizami, S, Green, JR, Eklund, JM & McGregor, C 2010, 'Heart disease classification through HRV analysis using parallel cascade identification and fast orthogonal search', 2010 IEEE International Workshop on Medical Measurements and Applications, MeMeA 2010 - Proceedings, pp. 134-139.View/Download from: Publisher's site
Heart rate variability (HRV) is an established indicator of cardiac health. Recent developments have shown the potential of nonlinear metrics for pattern classification of various heart conditions. Evidence indicates that the combination of multiple linear and nonlinear features leads to increased classification accuracy. In our paper, we demonstrate HRV classification using two dynamic nonlinear techniques called Parallel Cascade Identification (PCI) and Fast Orthogonal Search (FOS). We investigate the use of these two techniques for feature extraction from publicly available Physionet electrocardiogram (ECG) data to differentiate between normal sinus rhythm of the heart and 3 undesired conditions: arrhythmia, supraventricular arrhythmia, and congestive heart failure. Results compare well with previous studies which have used more features over the same dataset. We hypothesize that combining PCI and FOS features with traditional HRV features will show further improvement in classification accuracy and so can assist in real-time patient monitoring. ©2010 IEEE.
Percival, J, McGregor, C, Percival, N, Kamaleswaran, R & Tuuha, S 2010, 'A framework for nursing documentation enabling integration with HER and real-time patient monitoring', Proceedings - IEEE Symposium on Computer-Based Medical Systems, pp. 468-473.View/Download from: Publisher's site
This paper proposes a framework for mobile nursing documentation enabling the integration of clinical intervention data with both electronic health record systems and real-time intelligent decision support systems for patient monitoring. A brief discussion on the networking and information security concerns is presented in order to provide context for the mobile application design decisions surround data transmission and storage. The framework is demonstrated using an initial case study in a neonatal intensive care unit. © 2010 IEEE.
Catley, C, Smith, K, McGregor, C & Tracy, M 2009, 'Extending CRISP-DM to incorporate temporal data mining of multidimensional medical data streams: A neonatal intensive care unit case study', Proceedings - IEEE Symposium on Computer-Based Medical Systems.View/Download from: Publisher's site
Using a Neonatal Intensive Care Unit (NICU) case study, this work investigates the current CRoss Industry Standard Process for Data Mining (CRISP-DM) approach for modeling Intelligent Data Analysis (IDA)-based systems that perform temporal data mining (TDM). The case study highlights the need for an extended CRISP-DM approach when modeling clinical systems applying Data Mining (DM) and Temporal Abstraction (TA). As the number of such integrated TA/DM systems continues to grow, this limitation becomes significant and motivated our proposal of an extended CRISP-DM methodology to support TDM, known as CRISP-TDM. This approach supports clinical investigations on multi-dimensional time series data. This research paper has three key objectives: 1) Present a summary of the extended CRISP-TDM methodology; 2) Demonstrate the applicability of the proposed model to the NICU data, focusing on the challenges associated with multi-dimensional time series data; and 3) Describe the proposed IDA architecture for applying integrated TDM. ©2009 IEEE.
Jeng, JJ, McGregor, C & Schiefer, J 2009, 'Second IEEE international workshop on real-time service-oriented architecture and applications: RTSOAA 2009', Proceedings - International Computer Software and Applications Conference.View/Download from: Publisher's site
Kamaleswaran, R, McGregor, C & Percival, J 2009, 'Service oriented architecture for the integration of clinical and physiological data for real-time event stream processing', 2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, IEEE, Minneapolis, MN, pp. 1667-+.View/Download from: Publisher's site
MacDougall, C, Percival, J & McGregor, C 2009, 'Integrating Health Information Technology into Clinical Guidelines', 2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, IEEE, Minneapolis, MN, pp. 4646-+.View/Download from: Publisher's site
McGregor, C & Smith, KP 2009, 'A survey of physiological monitoring data models to support the service of critical care', Proceedings - International Computer Software and Applications Conference, pp. 104-109.View/Download from: Publisher's site
Vast quantities of data is created by utilizing sensors to gather information from patients located in intensive care units worldwide through physiological monitoring. The service oriented architectural model has emerged as a mechanism to support data interchange in a structured way to support the provision of services. The nature of critical care is such that clinicians provide a service of care, often to patients that are not located within their intensive care unit, and prior to the arrangement of transport to their unit. As a result opportunities exist to utilize the service oriented approach to provide a service of critical care. This research presents a survey of how recent computing and IT research as applied to physiological collection, transmission and storage of physiological data utilizes the service of critical care concept based on a service oriented architecture approach. © 2009 IEEE.
McGregor, C, Smith, KP & Eklund, JM 2009, 'A survey of recent physiological monitoring and transmission to support the service of critical care', Proceedings - IEEE Symposium on Computer-Based Medical Systems.View/Download from: Publisher's site
Vast quantities of data is sensed from patients located in intensive care units worldwide through physiological monitoring. In recent times the service oriented architectural model has emerged as a mechanism to providing a structured computing approach to support the provision of services. The nature of critical care is such that clinicians provide a service of care, often to patients that are not located within their intensive care unit. As a result opportunities exist to utilize the service oriented approach to provide a service of critical care. This research presents a survey of recent computing research as applied to physiological collection and transmission to support intelligent patient monitoring using the service of critical care concept based on a service oriented architecture approach. ©2009 IEEE.
Catley, C, Stratti, H & McGregor, C 2008, 'Multi-Dimensional Temporal Abstraction and Data Mining of Medical Time Series Data: Trends and Challenges', 2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8, 30th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, IEEE, Vancouver, CANADA, pp. 4322-+.View/Download from: Publisher's site
Eklund, JM, McGregor, C & Smith, KP 2008, 'A Method for Physiological Data Transmission and Archiving to Support the Service of Critical Care Using DICOM and HL7', 2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8, 30th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, IEEE, Vancouver, CANADA, pp. 1486-+.View/Download from: Publisher's site
McGregor, C & Eklund, JM 2008, 'Real-time service-oriented architectures to support remote critical care: Trends and challenges', Proceedings - International Computer Software and Applications Conference, pp. 1199-1204.View/Download from: Publisher's site
Healthcare providers and governments are under pressure to maintain and improve the quality of care to an increasing volume of critical care patients at either end of the life cycle, namely premature and ill-term babies together with the elderly. The provision of a service of critical care utilizing real-time service-oriented architectures has the potential to enable clinicians to be supported in the care of a greater number patients that are, perhaps more importantly, located elsewhere to their intensive care units. This paper presents a review of recent research in the application of computing and IT to support the service of critical care and determines the trends and challenges for the application of real-time service-oriented architectures within the domain. © 2008 IEEE.
McGregor, C & Frize, M 2008, 'Women in Biomedical Engineering and Health Informatics', 2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8, 30th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, IEEE, Vancouver, CANADA, pp. 5933-+.View/Download from: Publisher's site
McGregor, C, Smith, KP & Percival, J 2008, 'Women in Biomedical Engineering and Health Informatics and its impact on Gender Representation for Accepted Publications at IEEE EMBC 2007', 2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8, 30th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, IEEE, Vancouver, CANADA, pp. 2881-2884.View/Download from: Publisher's site
Curry, JM, McGregor, C & Tracy, S 2007, 'A Systems Development Life Cycle Approach to Patient Journey Modeling Projects', MEDINFO 2007: PROCEEDINGS OF THE 12TH WORLD CONGRESS ON HEALTH (MEDICAL) INFORMATICS, PTS 1 AND 2, 12th World Congress on Health (Medical) Informatics, IOS PRESS, Brisbane, AUSTRALIA, pp. 905-+.
McGregor, C & Frize, M 2007, 'Women in biomedical engineering and health informatics', Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, p. 238.View/Download from: Publisher's site
A valuable session for anyone whether student or not, interested in learning more about Biomedical Engineering and Health Informatics as a career choice for women. Prominent women within the domains Biomedical Engineering and Health Informatics will present as members of a panel on issues such as time management and getting hired for a medical technology career. Other topics for discussion include: career/family balance, experiences with and strategies to eliminate glass ceilings together with working in a profession perceived to be male dominated. Latest information will be provided on the representation of women within these professions. Utilise the fantastic networking opportunity that will conclude this session to build and establish new professional networks with other women interested in your fields of expertise. Bring your contact details and be ready to make new contacts that are relevant for you! Time Management is a pre-requesite to professional success and income and societal impact are directly related to a person's ability to do good time management. There are some simple but fundamental guidelines that can be implemented by anyone and that have large and lasting impacts. This brief overview will go over some of the secrets of time management. How to get hired for a medical technology career. A highly technical education, solid interviewing skills and focused networking are the keys to success. You can be prepared © 2007 IEEE.
McGregor, C & Kneale, B 2007, 'Simulated neonatal intensive care units to support neonatologist international mobility', Proceedings of the 3rd IASTED International Conference on Telehealth, pp. 124-129.
Intensive care units (ICUs) worldwide offer support for patients in need of critical care. They boast a range of state-of-the-art medical monitoring devices to monitor a patient's physiological parameters such as blood oxygen, blood pressure, and heart rate. Other devices such as ventilators offer mechanical life support. While much of the existing research enabling ICT support for ICUs has focussed on the delivery of alerts, these approaches do not support mobility well. The Bush Babies on Broadband project aims to support NICU patient and care provider mobility. A key benefit of the Bush Babies on Broadband framework is that it is available to link regional hospitals with the supporting NICU Neonatologist 'on demand' eliminating the need to establish permanent point to point connections. The focus of this paper is on the reapplication of the Bush Babies on Broadband architecture to support mobility of the care provider. The ability of a Neonatologist to access multi-media information for babies contained within their neonatal intensive care unit, while located overseas is tested and results are presented.
McGregor, C & Stacey, M 2007, 'High frequency distributed data stream event correlation to improve neonatal clinical management', ACM International Conference Proceeding Series, pp. 146-151.View/Download from: Publisher's site
Approximately eighteen percent (18%) of babies born in New South Wales (NSW), Australia require special care or neonatal intensive care admission. Premature babies can be up to 17 weeks early and may only weigh 450gms; they can spend 3 or 4 months in intensive care and have dozens of specific diseases before discharge, many of these may have long term implications for the future health of the individual. In addition, fifteen percent of neonatal intensive care admissions are transferred after delivery from smaller regional or remote hospitals without intensive care facilities to larger Tertiary Referral or Children's Hospitals with Neonatal Intensive Care Units (NICUs). Similar conditions apply within Australia, New Zealand, Canada, USA and elsewhere where small non-tertiary units are spread throughout the country. This paper presents case study based applied research in progress supporting the development of a distributed event stream processing framework to enable high frequency distributed data stream event correlation to improve neonatal clinical management. This research extends the traditional notion of event-based approaches by extending the notion of an event to incorporate a composite event that exists over a period of time, as is required within the domain of health and medicine. This is achieved through a multi-agent event calculus based approach that supports temporal abstraction. A key contribution of this research is the ability to support automated medical condition onset detection. © 2007 ACM.
Stacey, M, McGregor, C & Tracy, M 2007, 'An architecture for multi-dimensional temporal abstraction and its application to support neonatal intensive care', 2007 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-16, 29th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, IEEE, Lyon, FRANCE, pp. 3752-3756.View/Download from: Publisher's site
Curry, J, McGregor, C & Tracy, S 2006, 'A communication tool to improve the patient journey modeling process', 2006 28TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-15, 28th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, IEEE, New York, NY, pp. 901-+.
McGregor, C, Heath, J & Wei, M 2005, 'A web services based framework for the transmission of physiological data for local and remote neonatal intensive care', 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service, Proceedings, IEEE International Conference on e-Technology, e-Commerce and e-Service, IEEE COMPUTER SOC, Hong Kong Baptist Univ, Hong Kong, PEOPLES R CHINA, pp. 496-501.View/Download from: Publisher's site
McGregor, C, Kneale, B & Tracy, M 2005, 'Bush babies broadband: On-demand virtual neonatal intensive care unit support for regional Australia', Third International Conference on Information Technology and Applications, Vol 2, Proceedings, 3rd International Conference on Information Technology and Applications, IEEE COMPUTER SOC, Sydney, AUSTRALIA, pp. 113-118.
McGregor, C, Purdy, M & Kneale, B 2005, 'Compression of XML physiological data streams to support neonatal intensive care unit web services', 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service, Proceedings, IEEE International Conference on e-Technology, e-Commerce and e-Service, IEEE COMPUTER SOC, Hong Kong Baptist Univ, Hong Kong, PEOPLES R CHINA, pp. 486-489.View/Download from: Publisher's site
Schiefer, J & McGregor, C 2004, 'Correlating events for monitoring business processes', ICEIS 2004 - Proceedings of the Sixth International Conference on Enterprise Information Systems, pp. 320-327.
With the increasing demand for real-time information on critical performance indicators of business processes, the capturing, transformation and correlation of real-world events with minimal latency are a prerequisite for improving the speed and effectiveness of an organization's business operations. Events often include key business information about their relationship to other events that can be utilized to collect relevant event data for the calculation of business performance indicators. In this paper we introduce an approach for correlating events of business processes that uses correlation sessions to represent correlation knowledge. Correlation sessions facilitate the processing of data across multiple events and thereby enable a calculating of business metrics in near real-time. The benefit over existing approaches is that it is tailored to instrument business processes and business applications that may operate in a heterogeneous software environment. We propose a Java-based, container-managed environment which provides a distributed, scalable, near-real time processing of events and which includes a correlation service that effectively manages correlation sessions. We also show a complete example that illustrates how correlation sessions can be utilized for computing the cycle time of business processes.
Curry, J, McGregor, C, Potok, TE & Elmore, M 2003, 'XML and the semantic web: Implications and applications', Proceedings of the 36th Annual Hawaii International Conference on System Sciences, HICSS 2003, p. 121.View/Download from: Publisher's site
McGregor, C 2003, 'A method to extend BPEL4WS to enable business performance measurement', ICWS'03: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON WEB SERVICES, International Conference on Web Services, C S R E A PRESS, LAS VEGAS, NV, pp. 46-51.
McGregor, C 2003, 'Balanced scorecard driven business process definition using XML', Proceedings of the 36th Annual Hawaii International Conference on System Sciences, HICSS 2003.View/Download from: Publisher's site
© 2003 IEEE. During the last decade a variety of information technologies have emerged relating to business process modelling. One issue resulting from the introduction of these technologies is the inability to link the business process definition with the information gathered during the development of the business strategy. Organisations require the ability to define their business strategy, then use the outcomes of this definition to drive the business process definition. This paper details a methodology that applies XML to link business strategy with business process definition. The key contribution of this work is an extension to the balanced scorecard XML draft standard that incorporates quantified business process performance measures. This methodology is then applied to a specific case study where an organisation plans to provide personal loans to its customers.
McGregor, C & Schiefer, J 2003, 'A framework for analyzing and measuring business performance with web services', IEEE INTERNATIONAL CONFERENCE ON E-COMMERCE, IEEE International Conference on E-Commerce (CEC 2003), IEEE COMPUTER SOC, NEWPORT BEACH, CA, pp. 405-412.View/Download from: Publisher's site
Bryan, GM, Curry, JM, McGregor, C, Holdsworth, D & Sharply, R 2002, 'Using XML to facilitate information management across multiple local government agencies', Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 1190-1199.View/Download from: Publisher's site
© 2002 IEEE. The main barriers to the level of electronic data interchange required to seamlessly integrate services offered by legacy systems in an Internet environment are the need for applications to share a common data definition and the non-heterogeneity in database platforms. This paper details a collaborative research initiative between the Penrith City Council, Penrith Australia and the Centre for Advanced Systems Engineering (CASE) at the University of Western Sydney. It details the development of a fully functioning XML-based prototype system that provides effective integration of services offered by a collaborating group of legacy systems. The key contribution of this work is to provide an open systems based infrastructure that allows collaborating legacy systems, based on heterogeneous database and server platforms, to offer an integrated query service over the Internet.
McGregor, C & Kumaran, S 2002, 'An Agent-Based System for Trading Partner Management in B2B e-Commerce', 12th International Workshop on Research Issue in Data Engineering: Engineering E-Commerce/E-Business Systems, RIDE-2EC 2002, IEEE, San Jose, USA, pp. 84-89.View/Download from: Publisher's site
Organizations invest in B2B and workflow management systems to enable seamless integration of multiple transaction systems that support their business processes. However, knowledge of the organization's performance becomes buried within internal processing of the B2B workflow platform. This research introduces a framework that analyses workflow audit logs, utilizing DSS principles together with agent technologies, to feedback the organization's performance measures. We apply this framework to a private trading exchange case study where suppliers participate in an interorganizational order fulfillment workflow. Agents refine the organization's knowledge of supplier productivity and commitment as they learn from interactions over time with trading partners
McGregor, C & Kumaran, S 2002, 'Business process monitoring using web services in B2B e-commerce', Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002, p. 219.View/Download from: Publisher's site
© 2002 IEEE. Organisations are re-engineering their B2B communications to be performed through web services. Their aim is to create modularised services that support the business processes within their organisation and also those external entities that participate in these same business processes. This improvement is at the expense of the organisation's knowledge of its performance, as this knowledge will become buried within the internal processing of the web service platform. This research introduces an approach to reclaim and improve this knowledge for the organisation by establishing a framework that enables the definition of web services, together with the logging and analysis of the enactment of web services. This framework utilises web service concepts, DSS principles, and agent technologies, to enable feedback on the organisation's performance measures through the analysis of the web services. We apply this framework to a specific case study where suppliers participate in an inter-organisational workflow via a Private Exchange in the context of order fulfilment. A key benefit of this work is that the data is stored once but provides information both to the organisation acting as the customer and the organisation acting as the supplier. It therefore removes the need for development of internal performance monitoring tools to monitor web services performance.
McGregor, C, Bryan, G, Curry, J & Tracy, M 2002, 'The e-Baby data warehouse: A case study', Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 3018-3024.View/Download from: Publisher's site
© 2002 IEEE. Neonatal intensive care units (NICUs) require equipment and facilities to assist and monitor premature (and some full-term) babies. This equipment outputs physiological and clinical data, but current research does not provide doctors with techniques for capturing this data in a format that is suitable for analysis and research. Additionally, regional hospitals provide limited NICU support, but, without access to a neonatologist, the baby must be moved to another hospital. This paper details a framework for clinical and physiological data capture, the storage structures within the e-Baby data warehouse, and information access through a secure intranet/Internet browser. The key contribution of this work is the infrastructure that provides a platform for patient information data capture, storage, display and analysis. A key benefit of this work is to provide a mechanism for neonatologists to receive information directly from a regional hospital, thereby preventing, in some cases, the immediate need to move the baby.