MATEC Web Conf.
Volume 292, 201923rd International Conference on Circuits, Systems, Communications and Computers (CSCC 2019)
|Number of page(s)||6|
|Published online||24 September 2019|
Analysis and Smoothing of EMG Signal Envelope Using Kalman and UFIR Filtering under Colored Measurement Noise
1Department of Electronics Engineering, Universidad de Guanajuato, Salamanca, 36885, Mexico
This article describes some filtering methods to remove artifacts from the EMG signal envelope. Diverse EMG waveforms are studied using the Kalman filter (KF) and unbiased finite impulse response (UFIR) filter. The filters are developed in discrete-time state-space for Gauss-Markov colored measurement noise (CMN) and termed as cKF and cUFIR. It is shown that a choice of a proper CMN factor allows extracting the EMG waveform envelope with a high robustness. Extensive investigation have shown that the cKF and cUFIR filter are most efficient when the density is low of the motor unit action potential (MUAP) of the EMG and the Hilbert transform is required. Otherwise, when the envelope is well-pronounced and well-shaped with sharp edges due to a high MUAP density, the filters can be applied directly without using the Hilbert transform.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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