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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
Published on: December 11, 2015
Ascher Friedman1, Nabil Hajj Chehade, Chieh Chien
1Center of Embedded Networked Sensing, UCLA, USA. AscherFriedman@gmail.com
This study introduces a method to calibrate tri-axial accelerometer orientation for human activity recognition. The approach significantly improves accuracy for wrongly oriented sensors, making activity classification more reliable.
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