Study of intelligent bio-feedback therapy system based on transcutaneous electrical nerve stimulation and surface EMG signals

In this study, a novel artificial biofeedback system based on the transcutaneous electrical nerve stimulation and pattern recognition of surface electromyography(sEMG) signals is designed for the rehabilitation treatment. This system is composed of hardware circuit of sEMG acquisition, surface Agcl electrodes, electrical nerve stimulator and relevant software. The main purpose of the system is to cure the nerve and muscle disease by biofeedback intelligent technology instead of physicians, that is, by means of feature extraction and classification of sEMG, the system can identify three different state (sensory, motorial, painful) and the fatigue state of the muscle, then according to above discrimination results to control the output of the stimulator automatically. In this paper, Firstly, a surface electromyographic signal acquisition circuit and signal processing interface based MFC are developed and designed. Secondly, the AR(Auto-Regressive)and WT(wavelet transform) are adopted for signal feature extraction, then extracted feature vectors are feed to the SVM(support vector machine) classifier. Finally, according to the discrimination results to regulate the output of the stimulator. Experiments verify the effectiveness of the system.