The Haar Wavelet Transform in the Time Series Similarity Paradigm
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Gait analyzer based on a cell phone with a single three-axis accelerometer
Proceedings of the 8th conference on Human-computer interaction with mobile devices and services
Human Activity Recognizer for Mobile Devices with Multiple Sensors
UIC-ATC '09 Proceedings of the 2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing
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We propose a novel human activity recognizer for an application for mobile phones. Since such applications should not consume too much electric power, our method should have not only high accuracy but also low electric power consumption by using just a single three-axis accelerometer. In feature extraction with the wavelet transform, we employ the Haar mother wavelet that allows low computational complexity. In addition, we reduce dimensions of features by using the singular value decomposition. In spite of the complexity reduction, we discriminate a user's status into walking, running, standing still and being in a moving train with an accuracy of over 90%.