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

Authors
  • Elgendi, Mohamed1
  • Picon, Flavien2
  • Magnenat-Thalmann, Nadia2
  • Abbott, Derek3
  • 1 University of Alberta, Department of Computing Science, 2-32 Athabasca Hall, Edmonton, T6G 2E1, Canada , Edmonton (Canada)
  • 2 Nanyang Technological University, Institute of Media Innovation, 50 Nanyang Drive, Singapore, 637553, Singapore , Singapore (Singapore)
  • 3 University of Adelaide, School of Electrical and Electronic Engineering, Adelaide, SA 5005, Australia , Adelaide (Australia)
Type
Published Article
Journal
BioMedical Engineering OnLine
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Jun 27, 2014
Volume
13
Issue
1
Identifiers
DOI: 10.1186/1475-925X-13-88
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundMany 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.MethodsWe 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.ResultsOur 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.ConclusionsThis is the first step toward laying the foundation for future studies that investigate abnormality in arm movement via use of a Kinect camera.

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