Abstract
In the development of robot-assisted rehabilitation systems for upper limb rehabilitation therapy, human electromyogram (EMG) is widely used due to its ability to detect the user intended motion. EMG is one kind of biological signal that can be recorded to evaluate the performance of skeletal muscles by means of a sensor electrode. Based on recorded EMG signals, user intended motion could be extracted via estimation of joint torque, force or angle. Therefore, this estimation becomes one of the most important factors to achieve accurate user intended motion. In this paper, an upper limb joint angle estimation methodology is proposed. A back propagation neural network (BPNN) is developed to estimate the shoulder and elbow joint angles from the recorded EMG signals. A Virtual Human Model (VHM) is also developed and integrated with BPNN to perform the simulation of the estimated angle. The relationships between sEMG signals and upper limb movements are observed in this paper. The effectiveness of our developments is evaluated with four healthy subjects and a VHM simulation. The results show that the methodology can be used in the estimation of joint angles based on EMG.
Highlights
Physical rehabilitation is the process of physical training that someone uses to improve or recover from their lost physical functions due to spinal cord injury (SCI), traumatic brain injury (TBI) or cerebrovascular accident (CVA)
It has been proved that a normal rehabilitation system will not provide fast recovery or an effective system unless the system is integrated with human biological signals, especially with EMG signal [4]
The complete system consists of three steps, where Step 1 deals with biosignal measurement and processing, Step 2 takes care of finding the relationship between surface EMG (sEMG) signals and joint angle by means of back propagation neural network (BPNN) and Step 3 performs the simulation of estimated shoulder and elbow joint angle of Virtual Human Model (VHM) that mimics the real human’s arm movements
Summary
Physical rehabilitation is the process of physical training that someone uses to improve or recover from their lost physical functions due to spinal cord injury (SCI), traumatic brain injury (TBI) or cerebrovascular accident (CVA). Second or third degree polynomial functions (EMGσ) were added to a nonlinear parametric model and model parameters were estimated via a pseudoinverse and ridge regression method to improve the accuracy of the estimated elbow torque value Another elbow joint estimation was carried out by Khalil et al [7]. The real joint angle was measured by a goniometer to calibrate and train the developed artificial neural network and estimate the elbow joint angle from EMG signals. Another estimation method of joint angle was developed by Masairo et al [10].
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