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

Version 2 2024-06-03, 12:03
Version 1 2015-01-01, 00:00
conference contribution
posted on 2024-06-03, 12:03 authored by S Li, Pubudu PathiranaPubudu Pathirana, MP Galea
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.

History

Related Materials

Location

Milan, Italy

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2015, IEEE

Editor/Contributor(s)

Patton J

Pagination

2701-2704

Start date

2015-08-25

End date

2015-08-29

ISSN

1557-170X

ISBN-13

9781424492718

Title of proceedings

EMBC 2015 : Biomedical Engineering : A Bridge to Improve the Quality of Health Care and the Quality of Life

Event

IEEE Engineering in Medicine and Biology Society. Conference (37th : 2015 : Milan, Italy)

Publisher

IEEE

Place of publication

Piscataway, N.J.