On-line Context Aware Physical Activity Recognition from the Accelerometer and Audio Sensors of Smartphones

Abstract : Activity Recognition (AR) from smartphone sensors has be-come a hot topic in the mobile computing domain since it can provide ser-vices directly to the user (health monitoring, fitness, context-awareness) as well as for third party applications and social network (performance sharing, profiling). Most of the research effort has been focused on direct recognition from accelerometer sensors and few studies have integrated the audio channel in their model despite the fact that it is a sensor that is always available on all kinds of smartphones. In this study, we show that audio features bring an important performance improvement over an accelerometer based approach. Moreover, the study demonstrates the interest of considering the smartphone location for on-line context-aware AR and the prediction power of audio features for this task. Finally, an-other contribution of the study is the collected corpus that is made avail-able to the community for AR recognition from audio and accelerometer sensors.
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Communication dans un congrès
European Conference on Ambient Intelligence, Nov 2014, Eindhoven, Netherlands. Springer International Publishing, 8850, pp.205-220, Ambient Intelligence. 〈10.1007/978-3-319-14112-1_17〉
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Contributeur : François Portet <>
Soumis le : jeudi 13 novembre 2014 - 17:18:46
Dernière modification le : jeudi 11 octobre 2018 - 08:48:03
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David Blachon, Doruk Cokun, François Portet. On-line Context Aware Physical Activity Recognition from the Accelerometer and Audio Sensors of Smartphones. European Conference on Ambient Intelligence, Nov 2014, Eindhoven, Netherlands. Springer International Publishing, 8850, pp.205-220, Ambient Intelligence. 〈10.1007/978-3-319-14112-1_17〉. 〈hal-01082580〉

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