Abstract
The estimation of the envelope is an important issue in surface electromyography (EMG) signal processing, which has relevant applications. The present document shows the process of getting the best envelope from the EMG signals based on digital filtering, the following algorithms have been implemented: the discrete-time state-space unbiased finite impulse response (UFIR) filter, Kalman filter (KF), and algorithms in discrete-time state-space for Gauss-Markov CMN such as cUFIR and cKF. We exploit EMG records of the electrical activity of muscles during movement. The motion for a resolution we tabled shows that better smoothing can be obtained using cUFIR and cKF. Higher accuracy of the developed cUFIR and cKF algorithms against UFIR and KF is demonstrated experimentally and by simulation.
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