Analysis of the effect of muscle fatigue on gait characteristics using data acquired by wearable sensors

Aishwarya Balakrishnan, Jeevan Medikonda, Pramod K. Namboothiri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Parkinson's disease (PD) patients suffer from numerous gait-related disturbances. Various factors contribute to the alteration in gait patterns, among which muscle fatigue plays a significant role. Traditional gait analysis techniques involve laboratory types of equipment that are expensive and require specialized personnel or software tools for analysis. In this paper, a portable wireless data acquisition system embedded with a network of wearable sensors is proposed that can aid real-time gait signal acquisition in an unconstrained environment. Experiments have been carried out to demonstrate the effectiveness of the proposed system and to examine the effect of muscle fatigue in gait monitoring using mechanomyography techniques. Results show distinct variability in mean stride time and cadence with the influence of muscle fatigue.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages137-140
Number of pages4
ISBN (Electronic)9781728198859
DOIs
Publication statusPublished - 30-10-2020
Event2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Udupi, India
Duration: 30-10-202031-10-2020

Publication series

Name2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings

Conference

Conference2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020
CountryIndia
CityUdupi
Period30-10-2031-10-20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications

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