Automated detection of muscle fatigue conditions from cyclostationary based geometric features of surface electromyography signals-Reference-Cited by-同舟云学术

Automated detection of muscle fatigue conditions from cyclostationary based geometric features of surface electromyography signals

Published:2021-07-22 Issue: Volume: Page:1-13
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

K Divya Bharathi¹,P. A. Karthick²,S. Ramakrishnan¹

Affiliation:

1. Non-Invasive Imaging and Diagnostics Laboratory, Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India

2. Physiological Measurements and Instrumentation Laboratory, Department of Instrumentation and Control Engineering, National Institute of Technology Tiruchirappalli, Tiruchirappalli, India

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2021.1955104

Reference45 articles.

1. Computation and Evaluation of Features of Surface Electromyogram to Identify the Force of Muscle Contraction and Muscle Fatigue

2. Atlas of Muscle Innervation Zones

3. Cao H, Dib IEH, Antoni J, Marque C. 2007. Analysis of muscular fatigue during cyclic dynamic movement. In: Proceedings of 29th International Conference - IEEE Engineering in Medicine and Biology Society, August 23-26, Lyon, France. p. 1880–1883.

4. Da Costa EL. 1996. Detection and identification of cyclostationary signals [master’s thesis]. California: Naval Postgraduate School.

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