Surface EMG cross talk quantified at the motor unit population level for muscles of the hand, thigh, and calf

Author:

Germer Carina M.12ORCID,Farina Dario3ORCID,Elias Leonardo A.14ORCID,Nuccio Stefano5,Hug François678ORCID,Del Vecchio Alessandro9ORCID

Affiliation:

1. Neural Engineering Research Laboratory, Center for Biomedical Engineering, University of Campinas, Campinas, Brazil

2. Department of Bioengineering, Federal University of Pernambuco, Recife, Brazil

3. Department of Bioengineering, Faculty of Engineering, Imperial College London, London, United Kingdom

4. Department of Electronics and Biomedical Engineering, School of Electrical and Computer Engineering, University of Campinas, Campinas, Brazil

5. Department of Movement, Human and Health Sciences, University of Rome “Foro Italico,” Rome, Italy

6. Laboratory “Movement, Interactions, Performance,” Nantes University, Nantes, France

7. Institut Universitaire de France, Paris, France

8. School of Biomedical Sciences, The University of Queensland, Brisbane, Australia

9. Department of Artificial Intelligence in Biomedical Engineering, Faculty of Engineering, Friedrich-Alexander University, Erlangen-Nuremberg, Germany

Abstract

We proposed a new method for the identification and quantification of cross talk at the motor unit level. We show that surface EMG cross talk can lead to physiological misinterpretations of EMG signals such as overestimations in the muscle activity and intermuscular correlation. Cross talk had little influence on the EMG power spectrum, which indicates that conventional temporal filtering cannot minimize cross talk. Spatial filter (single and double differential) effectively reduces but not abolish cross talk.

Funder

MCTI | Conselho Nacional de Desenvolvimento Científico e Tecnológico

São Paulo Research Foundation

Institut Universitaire de France

Agence Nationale de la Recherche

Publisher

American Physiological Society

Subject

Physiology (medical),Physiology

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