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Decision-tree-based human activity classification algorithm using single-channel foot-mounted gyroscope

McCarthy, Mitchell W., James, Daniel A., Lee, James B. and Rowlands, David D. (2015). Decision-tree-based human activity classification algorithm using single-channel foot-mounted gyroscope. Electronics Letters,51(9):675-676.

Document type: Journal Article
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IRMA ID 75039815xPUB948
Title Decision-tree-based human activity classification algorithm using single-channel foot-mounted gyroscope
Author McCarthy, Mitchell W.
James, Daniel A.
Lee, James B.
Rowlands, David D.
Journal Name Electronics Letters
Publication Date 2015
Volume Number 51
Issue Number 9
ISSN 0013-5194   (check CDU catalogue open catalogue search in new window)
Scopus ID 2-s2.0-84928746538
Start Page 675
End Page 676
Total Pages 2
Place of Publication United Kingdom
Publisher The Institution of Engineering and Technology
Field of Research PSYCHOLOGY AND COGNITIVE SCIENCES
HERDC Category C1 - Journal Article (DIISR)
Abstract Wearable devices that measure and recognise human activity in real time require classification algorithms that are both fast and accurate when implemented on limited hardware. A decision-tree-based method for differentiating between individual walking, running, stair climbing and stair descent strides using a single channel of a foot-mounted gyroscope suitable for implementation on embedded hardware is presented. Temporal features unique to each activity were extracted using an initial subject group (n = 13) and a decision-tree-based classification algorithm was developed using the timing information of these features. A second subject group (n = 10) completed the same activities to provide data for verification of the system. Results indicate that the classifier was able to correctly match each stride to its activity with >90% accuracy. Running and walking strides in particular matched with >99% accuracy. The outcomes demonstrate that a lightweight yet robust classification system is feasible for implementation on embedded hardware for real-time daily monitoring.
Keywords sensors
gyroscopes
decision trees
DOI http://dx.doi.org/10.1049/el.2015.0436   (check subscription with CDU E-Gateway service for CDU Staff and Students  check subscription with CDU E-Gateway in new window)
 
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