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Estimation of Tri-Axial Walking Ground Reaction Forces of Left and Right Foot from Total Forces in Real-Life Environments
Continuous monitoring of natural human gait in real-life environments is essential in many applications including disease monitoring, rehabilitation, and professional sports. Wearable inertial measurement units are successfully used to measure body kinematics in real-life environments and to estimat...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022007/ https://www.ncbi.nlm.nih.gov/pubmed/29921797 http://dx.doi.org/10.3390/s18061966 |
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author | Shahabpoor, Erfan Pavic, Aleksandar |
author_facet | Shahabpoor, Erfan Pavic, Aleksandar |
author_sort | Shahabpoor, Erfan |
collection | PubMed |
description | Continuous monitoring of natural human gait in real-life environments is essential in many applications including disease monitoring, rehabilitation, and professional sports. Wearable inertial measurement units are successfully used to measure body kinematics in real-life environments and to estimate total walking ground reaction forces [Formula: see text] using equations of motion. However, for inverse dynamics and clinical gait analysis, the [Formula: see text] of each foot is required separately. Using an experimental dataset of 1243 tri-axial separate-foot [Formula: see text] time histories measured by the authors across eight years, this study proposes the ‘Twin Polynomial Method’ (TPM) to estimate the tri-axial left and right foot [Formula: see text] signals from the total [Formula: see text] signals. For each gait cycle, TPM fits polynomials of degree five, eight, and nine to the known single-support part of the left and right foot vertical, anterior-posterior, and medial-lateral [Formula: see text] signals, respectively, to extrapolate the unknown double-support parts of the corresponding [Formula: see text] signals. Validation of the proposed method both with force plate measurements (gold standard) in the laboratory, and in real-life environment showed a peak-to-peak normalized root mean square error of less than 2.5%, 6.5% and 7.5% for the estimated [Formula: see text] signals in the vertical, anterior-posterior and medial-lateral directions, respectively. These values show considerable improvement compared with the currently available [Formula: see text] decomposition methods in the literature. |
format | Online Article Text |
id | pubmed-6022007 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-60220072018-07-02 Estimation of Tri-Axial Walking Ground Reaction Forces of Left and Right Foot from Total Forces in Real-Life Environments Shahabpoor, Erfan Pavic, Aleksandar Sensors (Basel) Article Continuous monitoring of natural human gait in real-life environments is essential in many applications including disease monitoring, rehabilitation, and professional sports. Wearable inertial measurement units are successfully used to measure body kinematics in real-life environments and to estimate total walking ground reaction forces [Formula: see text] using equations of motion. However, for inverse dynamics and clinical gait analysis, the [Formula: see text] of each foot is required separately. Using an experimental dataset of 1243 tri-axial separate-foot [Formula: see text] time histories measured by the authors across eight years, this study proposes the ‘Twin Polynomial Method’ (TPM) to estimate the tri-axial left and right foot [Formula: see text] signals from the total [Formula: see text] signals. For each gait cycle, TPM fits polynomials of degree five, eight, and nine to the known single-support part of the left and right foot vertical, anterior-posterior, and medial-lateral [Formula: see text] signals, respectively, to extrapolate the unknown double-support parts of the corresponding [Formula: see text] signals. Validation of the proposed method both with force plate measurements (gold standard) in the laboratory, and in real-life environment showed a peak-to-peak normalized root mean square error of less than 2.5%, 6.5% and 7.5% for the estimated [Formula: see text] signals in the vertical, anterior-posterior and medial-lateral directions, respectively. These values show considerable improvement compared with the currently available [Formula: see text] decomposition methods in the literature. MDPI 2018-06-19 /pmc/articles/PMC6022007/ /pubmed/29921797 http://dx.doi.org/10.3390/s18061966 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shahabpoor, Erfan Pavic, Aleksandar Estimation of Tri-Axial Walking Ground Reaction Forces of Left and Right Foot from Total Forces in Real-Life Environments |
title | Estimation of Tri-Axial Walking Ground Reaction Forces of Left and Right Foot from Total Forces in Real-Life Environments |
title_full | Estimation of Tri-Axial Walking Ground Reaction Forces of Left and Right Foot from Total Forces in Real-Life Environments |
title_fullStr | Estimation of Tri-Axial Walking Ground Reaction Forces of Left and Right Foot from Total Forces in Real-Life Environments |
title_full_unstemmed | Estimation of Tri-Axial Walking Ground Reaction Forces of Left and Right Foot from Total Forces in Real-Life Environments |
title_short | Estimation of Tri-Axial Walking Ground Reaction Forces of Left and Right Foot from Total Forces in Real-Life Environments |
title_sort | estimation of tri-axial walking ground reaction forces of left and right foot from total forces in real-life environments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022007/ https://www.ncbi.nlm.nih.gov/pubmed/29921797 http://dx.doi.org/10.3390/s18061966 |
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