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

Aishwarya Balakrishnan; Jeevan Medikonda; Pramod K. Namboothiri

doi:10.1109/DISCOVER50404.2020.9278096

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 proceeding › Conference contribution

5 Citations (Scopus)

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 language	English
Title of host publication	2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	137-140
Number of pages	4
ISBN (Electronic)	9781728198859
DOIs	https://doi.org/10.1109/DISCOVER50404.2020.9278096
Publication status	Published - 30-10-2020
Event	2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Udupi, India Duration: 30-10-2020 → 31-10-2020

Publication series

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

Conference

Conference	2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020
Country/Territory	India
City	Udupi
Period	30-10-20 → 31-10-20

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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10.1109/DISCOVER50404.2020.9278096

Cite this

Balakrishnan, A., Medikonda, J., & Namboothiri, P. K. (2020). Analysis of the effect of muscle fatigue on gait characteristics using data acquired by wearable sensors. In 2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings (pp. 137-140). Article 9278096 (2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DISCOVER50404.2020.9278096

Balakrishnan, Aishwarya ; Medikonda, Jeevan ; Namboothiri, Pramod K. / Analysis of the effect of muscle fatigue on gait characteristics using data acquired by wearable sensors. 2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 137-140 (2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings).

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title = "Analysis of the effect of muscle fatigue on gait characteristics using data acquired by wearable sensors",

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.",

author = "Aishwarya Balakrishnan and Jeevan Medikonda and Namboothiri, \{Pramod K.\}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 ; Conference date: 30-10-2020 Through 31-10-2020",

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doi = "10.1109/DISCOVER50404.2020.9278096",

language = "English",

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

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Balakrishnan, A, Medikonda, J & Namboothiri, PK 2020, Analysis of the effect of muscle fatigue on gait characteristics using data acquired by wearable sensors. in 2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings., 9278096, 2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 137-140, 2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020, Udupi, India, 30-10-20. https://doi.org/10.1109/DISCOVER50404.2020.9278096

Analysis of the effect of muscle fatigue on gait characteristics using data acquired by wearable sensors. / Balakrishnan, Aishwarya; Medikonda, Jeevan ; Namboothiri, Pramod K.
2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. p. 137-140 9278096 (2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Analysis of the effect of muscle fatigue on gait characteristics using data acquired by wearable sensors

AU - Balakrishnan, Aishwarya

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AU - Namboothiri, Pramod K.

PY - 2020/10/30

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N2 - 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.

AB - 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.

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Balakrishnan A, Medikonda J , Namboothiri PK. Analysis of the effect of muscle fatigue on gait characteristics using data acquired by wearable sensors. In 2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. p. 137-140. 9278096. (2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings). doi: 10.1109/DISCOVER50404.2020.9278096

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

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