Robust Muscle Activity Onset Detection Using an Unsupervised Electromyogram Learning Framework

@inproceedings{Liu2015RobustMA,
  title={Robust Muscle Activity Onset Detection Using an Unsupervised Electromyogram Learning Framework},
  author={Jie Liu and Dongwen Ying and William Zev Rymer and Ping Zhou and Mikhail A. Lebedev},
  booktitle={PloS one},
  year={2015}
}
Accurate muscle activity onset detection is an essential prerequisite for many applications of surface electromyogram (EMG). This study presents an unsupervised EMG learning framework based on a sequential Gaussian mixture model (GMM) to detect muscle activity onsets. The distribution of the logarithmic power of EMG signal was characterized by a two-component GMM in each frequency band, in which the two components respectively correspond to the posterior distribution of EMG burst and non-burst… CONTINUE READING
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