EMG AMPLITUDE ESTIMATORS BASED ON PROBABILITY DISTRIBUTION FOR MUSCLE–COMPUTER INTERFACE

@article{Phinyomark2013EMGAE,
  title={EMG AMPLITUDE ESTIMATORS BASED ON PROBABILITY DISTRIBUTION FOR MUSCLE–COMPUTER INTERFACE},
  author={Angkoon Phinyomark and Franck Quaine and Yann Laurillau and Sirinee Thongpanja and Chusak Limsakul and Pornchai Phukpattaranont},
  journal={Fluctuation and Noise Letters},
  year={2013},
  volume={12},
  pages={1350016}
}
To develop an advanced muscle–computer interface (MCI) based on surface electromyography (EMG) signal, the amplitude estimations of muscle activities, i.e., root mean square (RMS) and mean absolute value (MAV) are widely used as a convenient and accurate input for a recognition system. Their classification performance is comparable to advanced and high computational time-scale methods, i.e., the wavelet transform. However, the signal-to-noise-ratio (SNR) performance of RMS and MAV depends on a… 
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