Human activity recognition from accelerometer data using a wearable device

Authors:
Pierluigi Casale;Oriol Pujol;Petia Radeva
Affiliations:
Computer Vision Center and Dept. of Applied Mathematics and Analysis, University of Barcelona, Barcelona, Spain;Computer Vision Center and Dept. of Applied Mathematics and Analysis, University of Barcelona, Barcelona, Spain;Computer Vision Center and Dept. of Applied Mathematics and Analysis, University of Barcelona, Barcelona, Spain
Venue:
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Year:
2011

Citing 8
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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%.