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Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton

Because the target users of the assistive-type lower extremity exoskeletons (ASLEEs) are those who suffer from lower limb disabilities, customized gait is adopted for the control of ASLEEs. However, the customized gait is unable to provide stable motion for variable terrain, for example, flat, uphil...

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Autores principales: Yue, Chunfeng, Lin, Xichuan, Zhang, Ximing, Qiu, Jing, Cheng, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167578/
https://www.ncbi.nlm.nih.gov/pubmed/30319712
http://dx.doi.org/10.1155/2018/8610458
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author Yue, Chunfeng
Lin, Xichuan
Zhang, Ximing
Qiu, Jing
Cheng, Hong
author_facet Yue, Chunfeng
Lin, Xichuan
Zhang, Ximing
Qiu, Jing
Cheng, Hong
author_sort Yue, Chunfeng
collection PubMed
description Because the target users of the assistive-type lower extremity exoskeletons (ASLEEs) are those who suffer from lower limb disabilities, customized gait is adopted for the control of ASLEEs. However, the customized gait is unable to provide stable motion for variable terrain, for example, flat, uphill, downhill, and soft ground. The purpose of this paper is to realize gait detection and environment feature recognition for AIDER by developing a novel wearable sensing system. The wearable sensing system employs 7 force sensors as a sensing matrix to achieve high accuracy of ground reaction force detection. There is one more IMU sensor that is integrated into the structure to detect the angular velocity. By fusing force and angular velocity data, four typical terrain features can be recognized successfully, and the recognition rate can reach up to 93%.
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spelling pubmed-61675782018-10-14 Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton Yue, Chunfeng Lin, Xichuan Zhang, Ximing Qiu, Jing Cheng, Hong Appl Bionics Biomech Research Article Because the target users of the assistive-type lower extremity exoskeletons (ASLEEs) are those who suffer from lower limb disabilities, customized gait is adopted for the control of ASLEEs. However, the customized gait is unable to provide stable motion for variable terrain, for example, flat, uphill, downhill, and soft ground. The purpose of this paper is to realize gait detection and environment feature recognition for AIDER by developing a novel wearable sensing system. The wearable sensing system employs 7 force sensors as a sensing matrix to achieve high accuracy of ground reaction force detection. There is one more IMU sensor that is integrated into the structure to detect the angular velocity. By fusing force and angular velocity data, four typical terrain features can be recognized successfully, and the recognition rate can reach up to 93%. Hindawi 2018-09-18 /pmc/articles/PMC6167578/ /pubmed/30319712 http://dx.doi.org/10.1155/2018/8610458 Text en Copyright © 2018 Chunfeng Yue et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yue, Chunfeng
Lin, Xichuan
Zhang, Ximing
Qiu, Jing
Cheng, Hong
Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton
title Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton
title_full Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton
title_fullStr Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton
title_full_unstemmed Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton
title_short Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton
title_sort design and performance evaluation of a wearable sensing system for lower-limb exoskeleton
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167578/
https://www.ncbi.nlm.nih.gov/pubmed/30319712
http://dx.doi.org/10.1155/2018/8610458
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