Accepted for/Published in: JMIR Bioinformatics and Biotechnology
Date Submitted: Apr 6, 2022
Open Peer Review Period: Apr 5, 2022 - May 31, 2022
Date Accepted: Jul 7, 2022
(closed for review but you can still tweet)
Monitoring physical behavior in rehabilitation: A development and validation study of a machine learning-based algorithm for thigh mounted accelerometers
ABSTRACT
Background:
Physical activity (PA) is emerging as an outcome measure. Accelerometers have become an important tool in monitoring physical behavior and newer analytical approaches of recognition methods increase the degree of details.
Objective:
The purpose of this study was to develop and validate an algorithm for classifying several daily physical behaviors using a single thigh-mounted accelerometer and a supervised machine learning scheme.
Methods:
We collected training data for adding further behavior classes to an existing algorithm. Combining data, we were potentially able to classify 11 behaviors, using a Random Forest learning scheme. We validated the algorithm through a simulated free-living procedure using chest-mounted cameras for establishing the ground truth. Furthermore, we adjusted our algorithm and compared the performance with a validated algorithm.
Results:
In the simulated free-living validation, the performance of the algorithm decreased to 64% as a weighted average for the 11 classes (F-measure). After reducing to 5 classes corresponding with the validated algorithm, the result revealed high performance in comparison with both the ground truth and the validated algorithm.
Conclusions:
We developed an algorithm to classify 11 physical behaviors. We obtained high classification levels within specific behaviors, while others yielded lower classification potential.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.