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An Objective Balance Error Scoring System for Sideline Concussion Evaluation Using Duplex Kinect Sensors
Sports-related concussion is a common sports injury that might induce potential long-term consequences without early diagnosis and intervention in the field. However, there are few options of such sensor systems available. The aim of the study is to propose and validate an automated concussion admin...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5677441/ https://www.ncbi.nlm.nih.gov/pubmed/29053602 http://dx.doi.org/10.3390/s17102398 |
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author | Zhu, Mengqi Huang, Zhonghua Ma, Chao Li, Yinlin |
author_facet | Zhu, Mengqi Huang, Zhonghua Ma, Chao Li, Yinlin |
author_sort | Zhu, Mengqi |
collection | PubMed |
description | Sports-related concussion is a common sports injury that might induce potential long-term consequences without early diagnosis and intervention in the field. However, there are few options of such sensor systems available. The aim of the study is to propose and validate an automated concussion administration and scoring approach, which is objective, affordable and capable of detecting all balance errors required by the balance error scoring system (BESS) protocol in the field condition. Our approach is first to capture human body skeleton positions using two Microsoft Kinect sensors in the proposed configuration and merge the data by a custom-made algorithm to remove the self-occlusion of limbs. The standing balance errors according to BESS protocol were further measured and accessed automatically by the proposed algorithm. Simultaneously, the BESS test was filmed for scoring by an experienced rater. Two results were compared using Pearson coefficient r, obtaining an excellent consistency (r = 0.93, p < 0.05). In addition, BESS test–retest was performed after seven days and compared using intraclass correlation coefficients (ICC), showing a good test–retest reliability (ICC = 0.81, p < 0.01). The proposed approach could be an alternative of objective tools to assess postural stability for sideline sports concussion diagnosis. |
format | Online Article Text |
id | pubmed-5677441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-56774412017-11-17 An Objective Balance Error Scoring System for Sideline Concussion Evaluation Using Duplex Kinect Sensors Zhu, Mengqi Huang, Zhonghua Ma, Chao Li, Yinlin Sensors (Basel) Article Sports-related concussion is a common sports injury that might induce potential long-term consequences without early diagnosis and intervention in the field. However, there are few options of such sensor systems available. The aim of the study is to propose and validate an automated concussion administration and scoring approach, which is objective, affordable and capable of detecting all balance errors required by the balance error scoring system (BESS) protocol in the field condition. Our approach is first to capture human body skeleton positions using two Microsoft Kinect sensors in the proposed configuration and merge the data by a custom-made algorithm to remove the self-occlusion of limbs. The standing balance errors according to BESS protocol were further measured and accessed automatically by the proposed algorithm. Simultaneously, the BESS test was filmed for scoring by an experienced rater. Two results were compared using Pearson coefficient r, obtaining an excellent consistency (r = 0.93, p < 0.05). In addition, BESS test–retest was performed after seven days and compared using intraclass correlation coefficients (ICC), showing a good test–retest reliability (ICC = 0.81, p < 0.01). The proposed approach could be an alternative of objective tools to assess postural stability for sideline sports concussion diagnosis. MDPI 2017-10-20 /pmc/articles/PMC5677441/ /pubmed/29053602 http://dx.doi.org/10.3390/s17102398 Text en © 2017 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 Zhu, Mengqi Huang, Zhonghua Ma, Chao Li, Yinlin An Objective Balance Error Scoring System for Sideline Concussion Evaluation Using Duplex Kinect Sensors |
title | An Objective Balance Error Scoring System for Sideline Concussion Evaluation Using Duplex Kinect Sensors |
title_full | An Objective Balance Error Scoring System for Sideline Concussion Evaluation Using Duplex Kinect Sensors |
title_fullStr | An Objective Balance Error Scoring System for Sideline Concussion Evaluation Using Duplex Kinect Sensors |
title_full_unstemmed | An Objective Balance Error Scoring System for Sideline Concussion Evaluation Using Duplex Kinect Sensors |
title_short | An Objective Balance Error Scoring System for Sideline Concussion Evaluation Using Duplex Kinect Sensors |
title_sort | objective balance error scoring system for sideline concussion evaluation using duplex kinect sensors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5677441/ https://www.ncbi.nlm.nih.gov/pubmed/29053602 http://dx.doi.org/10.3390/s17102398 |
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