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Inertial Sensor Estimation of Initial and Terminal Contact during In-Field Running

Given the popularity of running-based sports and the rapid development of Micro-electromechanical systems (MEMS), portable wireless sensors can provide in-field monitoring and analysis of running gait parameters during exercise. This paper proposed an intelligent analysis system from wireless micro–...

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Autores principales: Yang, Yue, Wang, Li, Su, Steven, Watsford, Mark, Wood, Lauren Marie, Duffield, Rob
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269345/
https://www.ncbi.nlm.nih.gov/pubmed/35808307
http://dx.doi.org/10.3390/s22134812
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author Yang, Yue
Wang, Li
Su, Steven
Watsford, Mark
Wood, Lauren Marie
Duffield, Rob
author_facet Yang, Yue
Wang, Li
Su, Steven
Watsford, Mark
Wood, Lauren Marie
Duffield, Rob
author_sort Yang, Yue
collection PubMed
description Given the popularity of running-based sports and the rapid development of Micro-electromechanical systems (MEMS), portable wireless sensors can provide in-field monitoring and analysis of running gait parameters during exercise. This paper proposed an intelligent analysis system from wireless micro–Inertial Measurement Unit (IMU) data to estimate contact time (CT) and flight time (FT) during running based on gyroscope and accelerometer sensors in a single location (ankle). Furthermore, a pre-processing system that detected the running period was introduced to analyse and enhance CT and FT detection accuracy and reduce noise. Results showed pre-processing successfully detected the designated running periods to remove noise of non-running periods. Furthermore, accelerometer and gyroscope algorithms showed good consistency within 95% confidence interval, and average absolute error of 31.53 ms and 24.77 ms, respectively. In turn, the combined system obtained a consistency of 84–100% agreement within tolerance values of 50 ms and 30 ms, respectively. Interestingly, both accuracy and consistency showed a decreasing trend as speed increased (36% at high-speed fore-foot strike). Successful CT and FT detection and output validation with consistency checking algorithms make in-field measurement of running gait possible using ankle-worn IMU sensors. Accordingly, accurate IMU-based gait analysis from gyroscope and accelerometer information can inform future research on in-field gait analysis.
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spelling pubmed-92693452022-07-09 Inertial Sensor Estimation of Initial and Terminal Contact during In-Field Running Yang, Yue Wang, Li Su, Steven Watsford, Mark Wood, Lauren Marie Duffield, Rob Sensors (Basel) Article Given the popularity of running-based sports and the rapid development of Micro-electromechanical systems (MEMS), portable wireless sensors can provide in-field monitoring and analysis of running gait parameters during exercise. This paper proposed an intelligent analysis system from wireless micro–Inertial Measurement Unit (IMU) data to estimate contact time (CT) and flight time (FT) during running based on gyroscope and accelerometer sensors in a single location (ankle). Furthermore, a pre-processing system that detected the running period was introduced to analyse and enhance CT and FT detection accuracy and reduce noise. Results showed pre-processing successfully detected the designated running periods to remove noise of non-running periods. Furthermore, accelerometer and gyroscope algorithms showed good consistency within 95% confidence interval, and average absolute error of 31.53 ms and 24.77 ms, respectively. In turn, the combined system obtained a consistency of 84–100% agreement within tolerance values of 50 ms and 30 ms, respectively. Interestingly, both accuracy and consistency showed a decreasing trend as speed increased (36% at high-speed fore-foot strike). Successful CT and FT detection and output validation with consistency checking algorithms make in-field measurement of running gait possible using ankle-worn IMU sensors. Accordingly, accurate IMU-based gait analysis from gyroscope and accelerometer information can inform future research on in-field gait analysis. MDPI 2022-06-25 /pmc/articles/PMC9269345/ /pubmed/35808307 http://dx.doi.org/10.3390/s22134812 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yang, Yue
Wang, Li
Su, Steven
Watsford, Mark
Wood, Lauren Marie
Duffield, Rob
Inertial Sensor Estimation of Initial and Terminal Contact during In-Field Running
title Inertial Sensor Estimation of Initial and Terminal Contact during In-Field Running
title_full Inertial Sensor Estimation of Initial and Terminal Contact during In-Field Running
title_fullStr Inertial Sensor Estimation of Initial and Terminal Contact during In-Field Running
title_full_unstemmed Inertial Sensor Estimation of Initial and Terminal Contact during In-Field Running
title_short Inertial Sensor Estimation of Initial and Terminal Contact during In-Field Running
title_sort inertial sensor estimation of initial and terminal contact during in-field running
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269345/
https://www.ncbi.nlm.nih.gov/pubmed/35808307
http://dx.doi.org/10.3390/s22134812
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