An automated activity monitoring system for rehabilitation
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Usher, Wayne
McCarthy, Mitchell
Leadbetter, Raymond
Ride, Jason
Casey, Leanne
Green, Heather
Morris, Norman
Muthukkumarasamy, Vallipuram
Laakso, E-Liisa
James, Daniel A
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Chan, KM
Subic, A
Fuss, FK
Clifton, P
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Abstract
Time lost due to injury or illness requiring rehabilitation is a major problem. Activity is an important part of rehabilitation, however compliance and adherence can be challenging. This paper addresses this issue by presenting an automatic system for monitoring activity allowing objective assessment of the activity. The system consisted of a smartphone based activity capture platform connected wirelessly to back-end server for analysis and storage and a web server to provide a user-friendly interface for feedback and education purposes. The system was validated by comparison with 3 accepted standard measuring devices and found to match their results well. The system also monitored the data of the participants over a continuous period of a number of days. It is evident that human factors play a part in both of the data collection strategies.
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Procedia Engineering
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60
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© 2013 The Authors. Published by Elsevier Ltd. Open access under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) License which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited. You may not alter, transform, or build upon this work.
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Engineering
Biomedical engineering not elsewhere classified