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Motion trajectory analysis for evaluating the performance of functional upper extremity tasks in daily living : a pilot study

Li, Saiyi, Pathirana, Pubudu N. and Galea, Mary P. 2015, Motion trajectory analysis for evaluating the performance of functional upper extremity tasks in daily living : a pilot study, in EMBC 2015 : Biomedical Engineering : A Bridge to Improve the Quality of Health Care and the Quality of Life, IEEE, Piscataway, N.J., pp. 2701-2704, doi: 10.1109/EMBC.2015.7318949.

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Title Motion trajectory analysis for evaluating the performance of functional upper extremity tasks in daily living : a pilot study
Author(s) Li, Saiyi
Pathirana, Pubudu N.
Galea, Mary P.
Conference name IEEE Engineering in Medicine and Biology Society. Conference (37th : 2015 : Milan, Italy)
Conference location Milan, Italy
Conference dates 25-29 Aug. 2015
Title of proceedings EMBC 2015 : Biomedical Engineering : A Bridge to Improve the Quality of Health Care and the Quality of Life
Editor(s) Patton, J.
Publication date 2015
Start page 2701
End page 2704
Total pages 4
Publisher IEEE
Place of publication Piscataway, N.J.
Summary Since 1998, tele-rehabilitation has been extensively studied for its potential capacity of saving time and cost for both therapists and patients. However, one gap hindering the deployment of tele-rehabilitation service is the approach to evaluate the outcome after tele-rehabilitation exercises without the presence of professional clinicians. In this paper, we propose an approach to model jerky and jerky-free movement trajectories with hidden Markov models (HMMs). The HMMs are then utilised to identify the jerky characteristics in a motion trajectory, thereby providing the number and amplitude of jerky movements in the specific length of the trajectory. Eventually, the ability of performing functional upper extremity tasks can be evaluated by classifying the motion trajectory into one of the pre-defined ability levels by looking at the number and amplitude of jerky movements. The simulation experiment confirmed that the proposed method is able to correctly classify motion trajectories into various ability levels to a high degree.
ISBN 9781424492718
ISSN 1557-170X
Language eng
DOI 10.1109/EMBC.2015.7318949
Field of Research 010203 Calculus of Variations, Systems Theory and Control Theory
010204 Dynamical Systems in Applications
090602 Control Systems, Robotics and Automation
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082523

Document type: Conference Paper
Collections: School of Engineering
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