Paper
18 February 2014 Human activity recognition by smartphones regardless of device orientation
Author Affiliations +
Proceedings Volume 9030, Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2014; 90300I (2014) https://doi.org/10.1117/12.2043180
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
Abstract
A new method for activity recognition using smartphones is proposed. Using three-axes accelerometer and gyroscope signals, the proposed system is able to identify low level activities with a high level of accuracy. The method works regardless of orientation of the device with respect to the body part to which it is attached. The algorithm achieves a high level of accuracy when trained on a small set of users and tested on an unknown user.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jafet Morales, David Akopian, and Sos Agaian "Human activity recognition by smartphones regardless of device orientation", Proc. SPIE 9030, Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2014, 90300I (18 February 2014); https://doi.org/10.1117/12.2043180
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CITATIONS
Cited by 21 scholarly publications.
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KEYWORDS
Gyroscopes

Principal component analysis

Sensors

Detection and tracking algorithms

Feature extraction

Feature selection

Databases

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