Detection and Recognition of Motor unit Action Potentials in the Multi-channel Surface EMG Signals
The method about the detection and recognition of MUAP waveforms was explored by using spatial and temporal information from the multi-channel sEMG signals at the low contraction force. A combined detection method of continuous wavelet transform and hypothesis testing was applied for each channel sEMG signal. The comprehensive judgement rule was implemented and utilized to analyze the motor unit firing and extracted waveforms. Then, the single channel signal which contained the candidate MUAP waveforms was derived from the average processing of multi-channel sEMG signals. With the averaged signal, the clustering algorithm was applied, and the unclassified waveforms were identified. The experimental results showed that some illusive shapes were rejected and the satisfying recognition performance could be acquired by using the averaged sEMG signals.
motor unit action potential detection recognition spatial and temporal information multi-channel sEMG signals
Qiang Li Ji-Hai Yang
School of Information Engineering Southwest University of Science and Technology Mianyang, China Department of Electronic Science and Technology University of Science and Technology of China Hefei,
国际会议
成都
英文
6-10
2011-01-14（万方平台首次上网日期，不代表论文的发表时间）