Cargando…
Validation of a Wearable System for Lower Extremity Assessment
OBJECTIVE: Remote assessment and diagnosis of functional impairment caused by osteoarthritis (OA) of the knee can achieve early intervention of patients’ functional impairment, prevent the deterioration of OA of the knee, and provide functional remote screening for patients with knee OA. This study...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons Australia, Ltd
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10622265/ https://www.ncbi.nlm.nih.gov/pubmed/37545175 http://dx.doi.org/10.1111/os.13836 |
_version_ | 1785130499155427328 |
---|---|
author | Zhang, Haohua Song, Yang Li, Cheng Dou, Yong Wang, Dacheng Wu, Yinyue Chen, Xiaoyi Liu, Di |
author_facet | Zhang, Haohua Song, Yang Li, Cheng Dou, Yong Wang, Dacheng Wu, Yinyue Chen, Xiaoyi Liu, Di |
author_sort | Zhang, Haohua |
collection | PubMed |
description | OBJECTIVE: Remote assessment and diagnosis of functional impairment caused by osteoarthritis (OA) of the knee can achieve early intervention of patients’ functional impairment, prevent the deterioration of OA of the knee, and provide functional remote screening for patients with knee OA. This study introduced an inertial measurement unit (IMU) sensor‐based system to assess lower extremity function and perform gait analysis. Then, we compared its accuracy to gold‐standard motion capture and gait measurement systems. METHODS: Nine adults were selected to participate in a comparative study of gait assessment outcomes using an IMU sensor‐based wearable system, a gold‐standard motion capture system, and a pressure‐based gait analysis system. The subject walked on a path that incorporated all three systems. Data analysis was performed on spatiotemporal gait parameters, including velocity, cycle time, cadence, and stride length. This was followed by gait phases, including stance, swing, double stance, and single limb support phases. Data were processed using the data processing software of each system. An independent sample t‐test was conducted for inter‐group comparison to analyze the data. RESULTS: The spatiotemporal gait parameters of the systems demonstrated excellent consistency, and the gait phases showed high consistency. Compared to the gold‐standard pressure‐based gait analysis system (the GATERite system), the mean gait cycle time results were 1.124 s vs. 1.127 s (p = 0.404); cadence was 93.333 steps/min vs. 94.189 steps/min (p = 0.482); stance phase was 60.89% vs. 63.26% (p < 0.001); swing phase was 39.11% vs. 36.74% (p < 0.001); stride length was 1.404 m vs. 1.420 m (p = 0.743); speed was 1.093 m/s vs. 1.110 m/s (p = 0.725). Compared to the gold‐standard video‐based motion capture system, the root mean square error was 2.7° for the hip angle and 2.6° for the knee angle. CONCLUSIONS: This IMU‐based wearable system delivered precise measuring results to evaluate patients with knee OA. This technology can also be used to guide rehabilitation exercises for patients with knee OA. |
format | Online Article Text |
id | pubmed-10622265 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley & Sons Australia, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-106222652023-11-04 Validation of a Wearable System for Lower Extremity Assessment Zhang, Haohua Song, Yang Li, Cheng Dou, Yong Wang, Dacheng Wu, Yinyue Chen, Xiaoyi Liu, Di Orthop Surg Research Articles OBJECTIVE: Remote assessment and diagnosis of functional impairment caused by osteoarthritis (OA) of the knee can achieve early intervention of patients’ functional impairment, prevent the deterioration of OA of the knee, and provide functional remote screening for patients with knee OA. This study introduced an inertial measurement unit (IMU) sensor‐based system to assess lower extremity function and perform gait analysis. Then, we compared its accuracy to gold‐standard motion capture and gait measurement systems. METHODS: Nine adults were selected to participate in a comparative study of gait assessment outcomes using an IMU sensor‐based wearable system, a gold‐standard motion capture system, and a pressure‐based gait analysis system. The subject walked on a path that incorporated all three systems. Data analysis was performed on spatiotemporal gait parameters, including velocity, cycle time, cadence, and stride length. This was followed by gait phases, including stance, swing, double stance, and single limb support phases. Data were processed using the data processing software of each system. An independent sample t‐test was conducted for inter‐group comparison to analyze the data. RESULTS: The spatiotemporal gait parameters of the systems demonstrated excellent consistency, and the gait phases showed high consistency. Compared to the gold‐standard pressure‐based gait analysis system (the GATERite system), the mean gait cycle time results were 1.124 s vs. 1.127 s (p = 0.404); cadence was 93.333 steps/min vs. 94.189 steps/min (p = 0.482); stance phase was 60.89% vs. 63.26% (p < 0.001); swing phase was 39.11% vs. 36.74% (p < 0.001); stride length was 1.404 m vs. 1.420 m (p = 0.743); speed was 1.093 m/s vs. 1.110 m/s (p = 0.725). Compared to the gold‐standard video‐based motion capture system, the root mean square error was 2.7° for the hip angle and 2.6° for the knee angle. CONCLUSIONS: This IMU‐based wearable system delivered precise measuring results to evaluate patients with knee OA. This technology can also be used to guide rehabilitation exercises for patients with knee OA. John Wiley & Sons Australia, Ltd 2023-08-06 /pmc/articles/PMC10622265/ /pubmed/37545175 http://dx.doi.org/10.1111/os.13836 Text en © 2023 The Authors. Orthopaedic Surgery published by Tianjin Hospital and John Wiley & Sons Australia, Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Zhang, Haohua Song, Yang Li, Cheng Dou, Yong Wang, Dacheng Wu, Yinyue Chen, Xiaoyi Liu, Di Validation of a Wearable System for Lower Extremity Assessment |
title | Validation of a Wearable System for Lower Extremity Assessment |
title_full | Validation of a Wearable System for Lower Extremity Assessment |
title_fullStr | Validation of a Wearable System for Lower Extremity Assessment |
title_full_unstemmed | Validation of a Wearable System for Lower Extremity Assessment |
title_short | Validation of a Wearable System for Lower Extremity Assessment |
title_sort | validation of a wearable system for lower extremity assessment |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10622265/ https://www.ncbi.nlm.nih.gov/pubmed/37545175 http://dx.doi.org/10.1111/os.13836 |
work_keys_str_mv | AT zhanghaohua validationofawearablesystemforlowerextremityassessment AT songyang validationofawearablesystemforlowerextremityassessment AT licheng validationofawearablesystemforlowerextremityassessment AT douyong validationofawearablesystemforlowerextremityassessment AT wangdacheng validationofawearablesystemforlowerextremityassessment AT wuyinyue validationofawearablesystemforlowerextremityassessment AT chenxiaoyi validationofawearablesystemforlowerextremityassessment AT liudi validationofawearablesystemforlowerextremityassessment |