Impact of robotic exoskeleton based on electromyography for rehabilitation of post stroke patient

Abstract

Ischemic stroke is one of the stroke types that commonly occur in people with stroke. This is usually followed by symptoms such as weakness or paralyzed limb. The purpose of this study is to train the stroke patient independently using a robotic exoskeleton based on electromyography (EMG) signal. This study was an experimental research with a compare one sample. The results of conventional exercise were used independently in addition to the robotic exoskeleton method for two weeks. Samples were taken based on the patient who had MT-3 (Manual Scale Testing) measurement scale. The EMG signal was collected from biceps during the exercise. The EMG signal was extracted using root mean square (RMS) feature which represented the energy of the muscle. The EMG data were analyzed using single factor ANOVA to obtain a significant difference of RMS. Results indicated that there was no significant difference of RMS with a p-value of 0.85 (alpha= 0.05). The used of the robotic exoskeleton method for rehabilitation of stroke patient was not effective for a short time assessment but more preferred as an observation of the EMG activities during the exercise for the post-stroke patient.