Arm movement speed assessment via a Kinect camera : a preliminary study in healthy subjects

Background Many clinical studies have shown that the arm movement of patients with neurological injury is often slow. In this paper, the speed of arm movements in healthy subjects is evaluated in order to validate the efficacy of using a Kinect camera for automated analysis. The consideration of ar...

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Main Authors: Elgendi, Mohamed, Picon, Flavien, Magnenat-Thalmann, Nadia, Abbott, Derek
Other Authors: Institute for Media Innovation
Format: Article
Language:English
Published: 2014
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Online Access:https://hdl.handle.net/10356/104896
http://hdl.handle.net/10220/20379
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1048962022-02-16T16:28:49Z Arm movement speed assessment via a Kinect camera : a preliminary study in healthy subjects Elgendi, Mohamed Picon, Flavien Magnenat-Thalmann, Nadia Abbott, Derek Institute for Media Innovation DRNTU::Science::Medicine::Biomedical engineering Background Many clinical studies have shown that the arm movement of patients with neurological injury is often slow. In this paper, the speed of arm movements in healthy subjects is evaluated in order to validate the efficacy of using a Kinect camera for automated analysis. The consideration of arm movement appears trivial at first glance, but in reality it is a very complex neural and biomechanical process that can potentially be used for detecting neurological disorders. Methods We recorded hand movements using a Kinect camera from 27 healthy subjects (21 males) with a mean age of 29 years undergoing three different arbitrary arm movement speeds: fast, medium, and slow. Results Our developed algorithm is able to classify the three arbitrary speed classes with an overall error of 5.43% for interclass speed classification and 0.49% for intraclass classification. Conclusions This is the first step toward laying the foundation for future studies that investigate abnormality in arm movement via use of a Kinect camera. Published version 2014-08-21T07:22:29Z 2019-12-06T21:42:12Z 2014-08-21T07:22:29Z 2019-12-06T21:42:12Z 2014 2014 Journal Article Elgendi, M., Picon, F., Magnenat-Thalmann, N., & Abbott, D. (2014). Arm movement speed assessment via a Kinect camera: A preliminary study in healthy subjects. BioMedical Engineering OnLine, 13(1), 88-. 1475-925X https://hdl.handle.net/10356/104896 http://hdl.handle.net/10220/20379 10.1186/1475-925X-13-88 24968711 en BioMedical Engineering OnLine © 2014 Elgendi et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedicationwaiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwisestated. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science::Medicine::Biomedical engineering
spellingShingle DRNTU::Science::Medicine::Biomedical engineering
Elgendi, Mohamed
Picon, Flavien
Magnenat-Thalmann, Nadia
Abbott, Derek
Arm movement speed assessment via a Kinect camera : a preliminary study in healthy subjects
description Background Many clinical studies have shown that the arm movement of patients with neurological injury is often slow. In this paper, the speed of arm movements in healthy subjects is evaluated in order to validate the efficacy of using a Kinect camera for automated analysis. The consideration of arm movement appears trivial at first glance, but in reality it is a very complex neural and biomechanical process that can potentially be used for detecting neurological disorders. Methods We recorded hand movements using a Kinect camera from 27 healthy subjects (21 males) with a mean age of 29 years undergoing three different arbitrary arm movement speeds: fast, medium, and slow. Results Our developed algorithm is able to classify the three arbitrary speed classes with an overall error of 5.43% for interclass speed classification and 0.49% for intraclass classification. Conclusions This is the first step toward laying the foundation for future studies that investigate abnormality in arm movement via use of a Kinect camera.
author2 Institute for Media Innovation
author_facet Institute for Media Innovation
Elgendi, Mohamed
Picon, Flavien
Magnenat-Thalmann, Nadia
Abbott, Derek
format Article
author Elgendi, Mohamed
Picon, Flavien
Magnenat-Thalmann, Nadia
Abbott, Derek
author_sort Elgendi, Mohamed
title Arm movement speed assessment via a Kinect camera : a preliminary study in healthy subjects
title_short Arm movement speed assessment via a Kinect camera : a preliminary study in healthy subjects
title_full Arm movement speed assessment via a Kinect camera : a preliminary study in healthy subjects
title_fullStr Arm movement speed assessment via a Kinect camera : a preliminary study in healthy subjects
title_full_unstemmed Arm movement speed assessment via a Kinect camera : a preliminary study in healthy subjects
title_sort arm movement speed assessment via a kinect camera : a preliminary study in healthy subjects
publishDate 2014
url https://hdl.handle.net/10356/104896
http://hdl.handle.net/10220/20379
_version_ 1725985587241943040