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A bayesian nonparametric framework for activity recognition using accelerometer data Nguyen, T, Gupta, S, Venkatesh, S and Phung, D 2014, 'A bayesian nonparametric framework for activity recognition using accelerometer data', in Magnus Borga (ed.) Proceedings of the 22nd International Conference on Pattern Recognition (ICPR 2014), Stockholm, Sweden, 24-28 August 2014, pp. 2017-2022. Document type: Conference Paper Collection: Conference Papers Title A bayesian nonparametric framework for activity recognition using accelerometer data Author(s) Nguyen, T Gupta, S Venkatesh, S Phung, D Year 2014 Conference name ICPR 2014 Conference location Stockholm, Sweden Conference dates 24-28 August 2014 Proceedings title Proceedings of the 22nd International Conference on Pattern Recognition (ICPR 2014) Editor(s) Magnus Borga Publisher IEEE Place of publication United States Start page 2017 End page 2022 Total pages 6 Abstract Monitoring daily physical activity of human plays an important role in preventing diseases as well as improving health. In this paper, we demonstrate a framework for monitoring the physical activity levels in daily life. We collect the data using accelerometer sensors in a realistic setting without any supervision. The ground truth of activities is provided by the participants themselves using an experience sampling application running on mobile phones. The original data is discretized by the hierarchical Dirichlet process (HDP) into different activity levels and the number of levels is inferred automatically. We validate the accuracy of the extracted patterns by using them for the multi-label classification of activities and demonstrate the high performances in various standard evaluation metrics. We further show that the extracted patterns are highly correlated to the daily routine of users. Subjects Pattern Recognition and Data Mining DOI - identifier 10.1109/ICPR.2014.352 Copyright notice © 2014 IEEE ISBN 9781479952106 Related Links Link Description http://dx.doi.org/10.1109/ICPR.2014.352 Link to Published Version   Versions Version Filter Type Wed, 11 Nov 2015, 10:13:57 EST Filtered Full Citation counts:   Cited 5 times in Thomson Reuters Web of Science Article | Citations Cited 7 times in Scopus Article | Citations Altmetric details: Access Statistics: 193 Abstract Views  -  Detailed Statistics Created: Wed, 11 Nov 2015, 09:58:00 EST by Catalyst Administrator