Estimation of Upper Limb Joint Angle Using Surface EMG Signal

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

Virtual games based self rehabilitation for home therapy system

It has been reported that 53,000 stroke events annually with ongoing costs are nearly $500 million per year for physical therapy care. This paper aims to provide effective and active rehabilitation for patients suffering from upper limb paresis, using gaming based a therapy technique. By disguising the tasks into more entertaining, patients are motivated to train for longer and more frequently. The advantage of this system can be a self-managed, at-home therapy system; reducing fatigue for physical therapists, and the time required for therapist-patient sessions. The system incorporates a virtual reality (VR) environment displaying both the games and a human model as feedback of the patients' actions whilst playing the games. Two games were developed, each targeting improvement of muscle strength, control, accuracy and speed. The difficulty of the games can be varied to suit a number of impairments and patient progress is monitored. The games are played using a Nintendo Wii controller. The successful improvements with lower costs associated with this system, are marked improvements for patients suffering from such a debilitating condition. © 2011 IEEE