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Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia
Abnormal movement of the head and neck is a typical symptom of Cervical Dystonia (CD). Accurate scoring on the severity scale is of great significance for treatment planning. The traditional scoring method is to use a protractor or contact sensors to calculate the angle of the movement, but this met...
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/PMC9230118/ https://www.ncbi.nlm.nih.gov/pubmed/35746424 http://dx.doi.org/10.3390/s22124642 |
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author | Ye, Chen Xiao, Yuhao Li, Ruoyu Gu, Hongkai Wang, Xinyu Lu, Tianyang Jin, Lingjing |
author_facet | Ye, Chen Xiao, Yuhao Li, Ruoyu Gu, Hongkai Wang, Xinyu Lu, Tianyang Jin, Lingjing |
author_sort | Ye, Chen |
collection | PubMed |
description | Abnormal movement of the head and neck is a typical symptom of Cervical Dystonia (CD). Accurate scoring on the severity scale is of great significance for treatment planning. The traditional scoring method is to use a protractor or contact sensors to calculate the angle of the movement, but this method is time-consuming, and it will interfere with the movement of the patient. In the recent outbreak of the coronavirus disease, the need for remote diagnosis and treatment of CD has become extremely urgent for clinical practice. To solve these problems, we propose a multi-view vision based CD severity scale scoring method, which detects the keypoint positions of the patient from the frontal and lateral images, and finally scores the severity scale by calculating head and neck motion angles. We compared the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) subscale scores calculated by our vision based method with the scores calculated by a neurologist trained in dyskinesia. An analysis of the correlation coefficient was then conducted. Intra-class correlation (ICC)(3,1) was used to measure absolute accuracy. Our multi-view vision based CD severity scale scoring method demonstrated sufficient validity and reliability. This low-cost and contactless method provides a new potential tool for remote diagnosis and treatment of CD. |
format | Online Article Text |
id | pubmed-9230118 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92301182022-06-25 Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia Ye, Chen Xiao, Yuhao Li, Ruoyu Gu, Hongkai Wang, Xinyu Lu, Tianyang Jin, Lingjing Sensors (Basel) Article Abnormal movement of the head and neck is a typical symptom of Cervical Dystonia (CD). Accurate scoring on the severity scale is of great significance for treatment planning. The traditional scoring method is to use a protractor or contact sensors to calculate the angle of the movement, but this method is time-consuming, and it will interfere with the movement of the patient. In the recent outbreak of the coronavirus disease, the need for remote diagnosis and treatment of CD has become extremely urgent for clinical practice. To solve these problems, we propose a multi-view vision based CD severity scale scoring method, which detects the keypoint positions of the patient from the frontal and lateral images, and finally scores the severity scale by calculating head and neck motion angles. We compared the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) subscale scores calculated by our vision based method with the scores calculated by a neurologist trained in dyskinesia. An analysis of the correlation coefficient was then conducted. Intra-class correlation (ICC)(3,1) was used to measure absolute accuracy. Our multi-view vision based CD severity scale scoring method demonstrated sufficient validity and reliability. This low-cost and contactless method provides a new potential tool for remote diagnosis and treatment of CD. MDPI 2022-06-20 /pmc/articles/PMC9230118/ /pubmed/35746424 http://dx.doi.org/10.3390/s22124642 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 Ye, Chen Xiao, Yuhao Li, Ruoyu Gu, Hongkai Wang, Xinyu Lu, Tianyang Jin, Lingjing Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia |
title | Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia |
title_full | Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia |
title_fullStr | Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia |
title_full_unstemmed | Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia |
title_short | Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia |
title_sort | pilot feasibility study of a multi-view vision based scoring method for cervical dystonia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9230118/ https://www.ncbi.nlm.nih.gov/pubmed/35746424 http://dx.doi.org/10.3390/s22124642 |
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