Reducing noise, artifacts and interference in single-channel EMG signals: A review

Auteurs

Marianne Boyer, Department of Mechanical Engineering, Université Laval, Québec, G1V 0A6, QC, Canada, Centre for Interdisciplinary Research in Rehabilitation and Social Integration, CIUSSS de la Capitale-Nationale, Québec, G1M 2S8, QC, Canada
Laurent Bouyer, Centre for Interdisciplinary Research in Rehabilitation and Social Integration, CIUSSS de la Capitale-Nationale, Québec, G1M 2S8, QC, Canada, Department of Rehabilitation, Université Laval, Québec, G1 V0A, QC, Canada
Jean-Sébastien Roy, Centre for Interdisciplinary Research in Rehabilitation and Social Integration, CIUSSS de la Capitale-Nationale, Québec, G1M 2S8, QC, Canada, Department of Rehabilitation, Université Laval, Québec, G1 V0A, QC, Canada
Alexandre Campeau-Lecours, Department of Mechanical Engineering, Université Laval, Québec, G1V 0A6, QC, Canada, Centre for Interdisciplinary Research in Rehabilitation and Social Integration, CIUSSS de la Capitale-Nationale, Québec, G1M 2S8, QC, Canada

Type de document

Revues de littérature, synthèses de connaissances

Année de publication

2023

Langue

Anglais

Titre de la revue

Sensors

Résumé

Electromyography (EMG) is gaining importance in many research and clinical applications, including muscle fatigue detection, control of robotic mechanisms and prostheses, clinical diagnosis of neuromuscular diseases and quantification of force. However, EMG signals can be contaminated by various types of noise, interference and artifacts, leading to potential data misinterpretation. Even assuming best practices, the acquired signal may still contain contaminants. The aim of this paper is to review methods employed to reduce the contamination of single channel EMG signals. Specifically, we focus on methods which enable a full reconstruction of the EMG signal without loss of information. This includes subtraction methods used in the time domain, denoising methods performed after the signal decomposition and hybrid approaches that combine multiple methods. Finally, this paper provides a discussion on the suitability of the individual methods based on the type of contaminant(s) present in the signal and the specific requirements of the application. © 2023 by the authors.

Mots-clés

Électromyographie, Electromyography, Interférence, Interference

Numéro de projet IRSST

n/a

Citation recommandée

Boyer, M., Bouyer, L., Roy, J.-S. et Campeau-Lecours, A. (2023). Reducing noise, artifacts and interference in single-channel EMG signals: A review. Sensors, 23(6). https://doi.org/10.3390/s23062927