Robust outlier detection in high-density surface electromyographic signals

H R Marateb; M Rojas-Martinez; M A Mananas Villanueva; R Merletti

doi:10.1109/IEMBS.2010.5627280

Robust outlier detection in high-density surface electromyographic signals

Annu Int Conf IEEE Eng Med Biol Soc. 2010:2010:4850-3. doi: 10.1109/IEMBS.2010.5627280.

Authors

H R Marateb¹, M Rojas-Martinez, M A Mananas Villanueva, R Merletti

Affiliation

¹ Laboratorio di Ingegneria del Sistema Neuromusculare (LISiN), Dipartimento di Elettronica, Politencnico di Torino, Italy. hamid.marateb@polito.it

PMID: 21096649
DOI: 10.1109/IEMBS.2010.5627280

Abstract

High Density surface Electromyography (HDsEMG) has been applied in both research and clinical applications for non-invasive neuromuscular assessment in several different fields using 2-D array. Proper interpretation of HDsEMG signals requires identifying "good" channels (where there is no short-circuit or bad-contact or major power line interference problem). Recording with many channels usually implies bad-contacts (that introduces large power line interference) and short-circuits (when using gels). In addition to online monitoring the electrode-contact quality, it is necessary to identify "bad" channels, or outliers, prior to the analysis of HDsEMG signal. In this paper we introduce a robust method to identify outliers in a set of monopolar HDsEMG signals recorded from Biceps and Triceps Brachii, Anconeus, Brachioradialis and Pronator Teres. The sensitivity and precision of this method show that this approach is promising.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Artifacts*
Diagnosis, Computer-Assisted / methods*
Electromyography / methods*
Humans
Muscle Contraction / physiology*
Muscle, Skeletal / physiology*
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity