Activity recognition and monitoring using multiple sensors on different body positions

The design of an activity recognition and monitoring sys-tem based on the eWatch, multi-sensor platform worn on different body positions, is presented in this paper. The sys-tem 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 sam-pling rates, and analyze the tradeoff between recognition accuracy and computational complexity. The classification accuracy on different body positions used for wearing elec-tronic devices was evaluated. 1