In this work the problem of rejection of motion artefacts from surface myoelectric signals, recorded during dynamic contractions, is studied. In fact, the extraction of frequency parameters and the detection of muscular activation patterns can be detrimentally affected by artefacts due to the movement of the surface electrodes, particularly stressed by the dynamic conditions of the exercise performed during measurement. In order to overcome this difficulty, four different filtering procedures have been tested and compared: a high-pass filtering procedure, a moving average procedure, a moving median procedure and a new adaptive wavelet based procedure, expressly designed for this work. Orthogonal Meyer wavelets are used with the aim of obtaining both a good reconstruction and a decomposition of the signal into non-overlapping bands. The four procedures have been tested with a set of different proofs utilising both synthetic and experimentally recorded myoelectric 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 level suggest a wider range of applications of the proposed algorithm. (C) 1999 Elsevier Science Ltd. All rights reserved.

Conforto, S., D'Alessio, T., & Pignatelli, S. (1999). Optimal rejection of movement artefacts from myoelectric signals by means of a wavelet filtering procedure. JOURNAL OF ELECTROMYOGRAPHY AND KINESIOLOGY, 9(1), 47-57 [10.1016/S1050-6411(98)00023-6].

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

CONFORTO, SILVIA;D'ALESSIO, Tommaso;
1999

Abstract

In this work the problem of rejection of motion artefacts from surface myoelectric signals, recorded during dynamic contractions, is studied. In fact, the extraction of frequency parameters and the detection of muscular activation patterns can be detrimentally affected by artefacts due to the movement of the surface electrodes, particularly stressed by the dynamic conditions of the exercise performed during measurement. In order to overcome this difficulty, four different filtering procedures have been tested and compared: a high-pass filtering procedure, a moving average procedure, a moving median procedure and a new adaptive wavelet based procedure, expressly designed for this work. Orthogonal Meyer wavelets are used with the aim of obtaining both a good reconstruction and a decomposition of the signal into non-overlapping bands. The four procedures have been tested with a set of different proofs utilising both synthetic and experimentally recorded myoelectric 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 level suggest a wider range of applications of the proposed algorithm. (C) 1999 Elsevier Science Ltd. All rights reserved.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/122027
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 62
  • ???jsp.display-item.citation.isi??? 56
social impact