Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions

Authors:
Uwe Maurer;Asim Smailagic;Daniel P. Siewiorek;Michael Deisher
Affiliations:
Technische Universitat Munchen, Germany;Carnegie Mellon University, Pittsburgh;Carnegie Mellon University, Pittsburgh;Intel, Hillsboro, OR
Venue:
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
Year:
2006

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Abstract

The design of an activity recognition and monitoring system based on the eWatch, multi-sensor platform worn on different body positions, is presented in this paper. The system identifies the user's activity in realtime using multiple sensors and records the classification results during a day. We compare multiple time domain feature sets and sampling rates, and analyze the tradeoff between recognition accuracy and computational complexity. The classification accuracy on different body positions used for wearing electronic devices was evaluated.