Musa, GMB, Al-Jumaily, A, Alnajjar, F & Shimoda, S 2017, 'Analyze The Human Movements To Help CNS To Shape The Synergy Using CNMF And Pattern Recognition', 2016 IEEE INTERNATIONAL SYMPOSIUM ON ROBOTICS AND INTELLIGENT SENSORS (IRIS 2016), vol. 105, pp. 170-176.View/Download from: UTS OPUS or Publisher's site
Bani Musa, G, Alnajjar, F, Al-Jumaily, A & Shimoda, S 2018, 'Upper Limb Recovery Prediction After Stroke Rehabilitation Based On Regression Method', Converging Clinical and Engineering Research on Neurorehabilitation III, International Conference on NeuroRehabilitation, Springer, Pisa, Italy, pp. 380-384.View/Download from: UTS OPUS or Publisher's site
In this paper, we investigate the possibility of a machine-learning algorithm using the Support Victor Machine Regression (SVMR) to predict the motor functional recovery of moderate post stroke patients during their rehabilitation program. To train the model, we used the recorded electromyography (EMG) signals from the upper limb muscles of the patients during their initial rehabilitation sessions. Then we tested the trained model to predict the later muscles performance of the patient during the same sessions. The results of this pilot study were promising; data were, to some extent, predictable. We believe such research direction could be essential to motivate the patient to complete the designed rehabilitation program and can assist the therapist to innovate proper rehabilitation menu for individual patients.