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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–...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9269345 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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