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Type: Journal article
Title: Arm movement speed assessment via a Kinect camera: A preliminary study in healthy subjects
Author: Elgendi, M.
Picon, F.
Magnenat-Thalmann, N.
Abbott, D.
Citation: BioMedical Engineering Online, 2014; 13(88):1-14
Publisher: BioMed Central
Issue Date: 2014
ISSN: 1475-925X
Statement of
Mohamed Elgendi, Flavien Picon, Nadia Magnenat-Thalmann and Derek Abbott
Abstract: 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 handmovements 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.
Keywords: Hand speed analysis; kinect; physiological movement
Rights: © 2014 Elgendi et al.; licensee BioMed Central Ltd This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.
RMID: 0020139012
DOI: 10.1186/1475-925X-13-88
Appears in Collections:Electrical and Electronic Engineering publications

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