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Multi-sensor classification of tennis strokes
Connaghan, Damien; Kelly, Philip; O'Connor, Noel E.
In this work, we investigate tennis stroke recognition using a single inertial measuring unit attached to a player’s forearm during a competitive match. This paper evaluates the best approach for stroke detection using either accelerometers, gyroscopes or magnetometers, which are embedded into the inertial measuring unit. This work concludes what is the optimal training data set for stroke classification and proves that classifiers can perform well when tested on players who were not used to train the classifier. This work provides a significant step forward for our overall goal, which is to develop next generation sports coaching tools using both inertial and visual sensors in an instrumented indoor sporting environment.
Keyword(s): Machine learning; Signal processing; Electronic engineering; Software engineering; inertial measuring unit; sensors; sport
Publication Date:
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Connaghan, Damien, Kelly, Philip and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 <> (2011) Multi-sensor classification of tennis strokes. In: IEEE Sensors 2011, 28-31 Oct, Limerick, Ireland.
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First Indexed: 2011-11-03 05:16:22 Last Updated: 2019-02-09 06:48:15