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Human Activity Recognition from Accelerometer Data Using a Wearable Device

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Pattern Recognition and Image Analysis (IbPRIA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6669))

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Abstract

Activity Recognition is an emerging field of research, born from the larger fields of ubiquitous computing, context-aware computing and multimedia. Recently, recognizing everyday life activities becomes one of the challenges for pervasive computing. In our work, we developed a novel wearable system easy to use and comfortable to bring. Our wearable system is based on a new set of 20 computationally efficient features and the Random Forest classifier. We obtain very encouraging results with classification accuracy of human activities recognition of up to 94%.

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Casale, P., Pujol, O., Radeva, P. (2011). Human Activity Recognition from Accelerometer Data Using a Wearable Device. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_36

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  • DOI: https://doi.org/10.1007/978-3-642-21257-4_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21256-7

  • Online ISBN: 978-3-642-21257-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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