Investigation of upper limb movement for VR based post stroke rehabilitation device

Abstract

The human upper limb muscles are involved in most of daily human activities. The muscles condition for upper limb motions is estimated based on the movement pattern of upper limb muscles. The upper limb muscle rehabilitation exercises such as fundamental movement and functional movement have been studied in order to investigate the movement pattern from the surface electromyogram (sEMG) signal. Electromyogram (EMG) signals contain information about muscle functions that can be extracted and can be used in analyzing the EMG signal of related muscles. In this research, the EMG signals are used to investigate the movement of the subject's upper limb during the rehabilitation activities. The statistical features of Root Mean Square (RMS) and Mean Absolute Value (MA V) are extracted from the EMG signal to analyze the muscle strength of each subject based on the rehabilitation task. The experiment results show that for the fundamental movement of biceps muscle with support, the average value of RMS is 328.26 mV while the average of MAV is 0.3568 mV. For the fundamental movement of biceps muscle without support, the average value of RMS is 216.48 mV while the average value of MAV is 0.2157 mV. For the functional movement with support, the average value of RMS is 4665.20 mV while the average value of MAV is 0.4102 mV. For the functional movement without support, the average value of RMS is 541.73mV while the average value of MAV is 0.1531 mV. The finding of the studies will be referred in designing virtual environment (VR) for the post stroke rehabilitation for the future arm rehabilitation device.