A Hand-rehabilitation FES System For Stroke Patients

About three-quarters of stroke survivors have varying degrees of motor dysfunction. Functional electrical stimulation (FES) technology is one of the most effective ways to recover motor functions of stroke patients. Using FES to reconstruct hand functions of the patients is especially interesting because it can significantly improve the independency and confidence of a patient and alleviate burdens on his/her family.In this thesis a multi-channel FES system based on TMS320F2812 Digital Signal Processor was developed to reconstruct the grasp and pinch movements of stroke patients. This system is portable, secure, extendable and user-friendly. To validate the system, we designed two experiments for healthy subjects and stroke patients respectively. In the experiments,5 healthy people and 5 stroke patients were recruited to perform the tasks of grasping a ball and pinching a spoon under the control of our FES system. The experimental results show that by using our FES system all 5 healthy subjects and 4 out of the 5 stroke patients successfully completed the grasp and pinch actions.In order to prevent muscle damage caused by excessive FES stimulation, we need to monitor the degree of muscle fatigue during FES treatment. This thesis developed a method to measure the degree of muscle fatigue based on EMG signals of the target muscle. We designed an experiment to record EMG signals at different fatigue levels, and then analyzed the time-domain and frequency-domain features of the signals. The results show that integrated electromyogram (iEMG), Zero Crossing Rate (ZCR) and Median Frequency (MF) are well correlated with the fatigue degree, suggesting that these features are strong candidate features for measuring muscle fatigue.