Preliminary study on upper limb movement identification based on sEMG signal

Stroke has become a very prevalent disease, especially in elder people. Many researches have focused on developing advanced and intelligent robotic system to assist the treatment of patients. For this field, Electromyography (EMG) is widely used for its benefit to get valuable information about the neuromuscular activity of a muscle. In this paper, wavelet packet decomposition method which is a kind of time-frequency domain is used for movement identification. Appropriate coefficients between three important movements for ADLs and sEMG signal will be extracted with wavelet packet decomposition method. These coefficients could be used as the input of BP neural network for movement identification. Experimental results proved that this method is effective off-line. Whereas the on-line identification rate should be improved in the future works.