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Tracking and Characterization of Spinal Cord-Injured Patients by Means of RGB-D Sensors
In physical rehabilitation, motion capture solutions are well-known but not as widespread as they could be. The main limit to their diffusion is not related to cost or usability but to the fact that the data generated when tracking a person must be elaborated according to the specific context and ai...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663008/ https://www.ncbi.nlm.nih.gov/pubmed/33158050 http://dx.doi.org/10.3390/s20216273 |
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author | Colombo Zefinetti, Filippo Vitali, Andrea Regazzoni, Daniele Rizzi, Caterina Molinero, Guido |
author_facet | Colombo Zefinetti, Filippo Vitali, Andrea Regazzoni, Daniele Rizzi, Caterina Molinero, Guido |
author_sort | Colombo Zefinetti, Filippo |
collection | PubMed |
description | In physical rehabilitation, motion capture solutions are well-known but not as widespread as they could be. The main limit to their diffusion is not related to cost or usability but to the fact that the data generated when tracking a person must be elaborated according to the specific context and aim. This paper proposes a solution including customized motion capture and data elaboration with the aim of supporting medical personnel in the assessment of spinal cord-injured (SCI) patients using a wheelchair. The configuration of the full-body motion capturing system is based on an asymmetric 3 Microsoft Kinect v2 sensor layout that provides a path of up to 6 m, which is required to properly track the wheelchair. Data elaboration is focused on the automatic recognition of the pushing cycles and on plotting any kinematic parameter that may be interesting in the assessment. Five movements have been considered to evaluate the wheelchair propulsion: the humeral elevation, the horizontal abduction of the humerus, the humeral rotation, the elbow flexion and the trunk extension along the sagittal plane. More than 60 volunteers with a spinal cord injury were enrolled for testing the solution. To evaluate the reliability of the data computed with SCI APPlication (APP) for the pushing cycle analysis, the patients were subdivided in four groups according to the level of the spinal cord injury (i.e., high paraplegia, low paraplegia, C7 tetraplegia and C6 tetraplegia). For each group, the average value and the standard deviation were computed and a comparison with similar acquisitions performed with a high-end solution is shown. The measurements computed by the SCI-APP show a good reliability for analyzing the movements of SCI patients’ propulsion wheelchair. |
format | Online Article Text |
id | pubmed-7663008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76630082020-11-14 Tracking and Characterization of Spinal Cord-Injured Patients by Means of RGB-D Sensors Colombo Zefinetti, Filippo Vitali, Andrea Regazzoni, Daniele Rizzi, Caterina Molinero, Guido Sensors (Basel) Article In physical rehabilitation, motion capture solutions are well-known but not as widespread as they could be. The main limit to their diffusion is not related to cost or usability but to the fact that the data generated when tracking a person must be elaborated according to the specific context and aim. This paper proposes a solution including customized motion capture and data elaboration with the aim of supporting medical personnel in the assessment of spinal cord-injured (SCI) patients using a wheelchair. The configuration of the full-body motion capturing system is based on an asymmetric 3 Microsoft Kinect v2 sensor layout that provides a path of up to 6 m, which is required to properly track the wheelchair. Data elaboration is focused on the automatic recognition of the pushing cycles and on plotting any kinematic parameter that may be interesting in the assessment. Five movements have been considered to evaluate the wheelchair propulsion: the humeral elevation, the horizontal abduction of the humerus, the humeral rotation, the elbow flexion and the trunk extension along the sagittal plane. More than 60 volunteers with a spinal cord injury were enrolled for testing the solution. To evaluate the reliability of the data computed with SCI APPlication (APP) for the pushing cycle analysis, the patients were subdivided in four groups according to the level of the spinal cord injury (i.e., high paraplegia, low paraplegia, C7 tetraplegia and C6 tetraplegia). For each group, the average value and the standard deviation were computed and a comparison with similar acquisitions performed with a high-end solution is shown. The measurements computed by the SCI-APP show a good reliability for analyzing the movements of SCI patients’ propulsion wheelchair. MDPI 2020-11-04 /pmc/articles/PMC7663008/ /pubmed/33158050 http://dx.doi.org/10.3390/s20216273 Text en © 2020 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 Colombo Zefinetti, Filippo Vitali, Andrea Regazzoni, Daniele Rizzi, Caterina Molinero, Guido Tracking and Characterization of Spinal Cord-Injured Patients by Means of RGB-D Sensors |
title | Tracking and Characterization of Spinal Cord-Injured Patients by Means of RGB-D Sensors |
title_full | Tracking and Characterization of Spinal Cord-Injured Patients by Means of RGB-D Sensors |
title_fullStr | Tracking and Characterization of Spinal Cord-Injured Patients by Means of RGB-D Sensors |
title_full_unstemmed | Tracking and Characterization of Spinal Cord-Injured Patients by Means of RGB-D Sensors |
title_short | Tracking and Characterization of Spinal Cord-Injured Patients by Means of RGB-D Sensors |
title_sort | tracking and characterization of spinal cord-injured patients by means of rgb-d sensors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663008/ https://www.ncbi.nlm.nih.gov/pubmed/33158050 http://dx.doi.org/10.3390/s20216273 |
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