Abstract
Supposed that there is an instrument that could identify a user's true intention to move and assist in exerting forces, it would substantially improve the quality of life and independence of the elderly and injured. The electromyogram(EMG) is that the simplest and the most convenient electrical signals that can be acquired from human muscle. On the other hand, the electromyogram(EMG) is used extensively on diagnosing muscular or nerve pathological disorder. Additionally, EMG is also used in control of prosthesis. Therefore, the objection of this study is to build up a portable EMG identification system to be the input command of an actively lower limbs prosthesis. In this study, an artificial back-propagation neural network for EMG identification is realized on a Digital Signal Processor(DSP). First, a Matlab program is developed to test the feasibility of the software. In the beginning, the EMG would be collected by the signal-conditioning circuit. Then, a wavelet transformation was applied to preserve the desired frequency band but filtered out the others. After the basic feature attraction, the signals would be sent into an artificial neural network to proceed the simulation. Finally, the complete algorithm would be realized on a DSP chip.