Optimal rejection of movement artefacts from myoelectric signals by means of a wavelet filtering procedure

In this work the problem of rejection of motion artefacts from surface myoe lectric signals, recorded during dynamic contractions, is studied. In fact, the extraction of frequency parameters and the detection of muscular activ ation patterns can be detrimentally affected by artefacts due to the moveme nt of the surface electrodes, particularly stressed by the dynamic conditio ns of the exercise performed during measurement. In order to overcome this difficulty, four different filtering procedures have been tested and compar ed: a high-pass filtering procedure, a moving average procedure, a moving m edian procedure and a new adaptive wavelet based procedure, expressly desig ned for this work. Orthogonal Meyer wavelets are used with the aim of obtai ning both a good reconstruction and a decomposition of the signal into non- overlapping bands. The four procedures have been tested with a set of diffe rent proofs utilising both synthetic and experimentally recorded myoelectri c signals. The results show that the wavelet procedure performs better than the other methods both in information preservation and in time-detection. Moreover, the features of user-independence and adaptivity to the noise lev el suggest a wider range of applications of the proposed algorithm. (C) 199 9 Elsevier Science Ltd. All rights reserved.