Recognizing Human Activities User-independently on Smartphones Based on Accelerometer Data

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Provided by: Creative Commons
Topic: Hardware
Format: PDF
Real-time human activity recognition on a mobile phone is presented in this paper. Unlike in most other studies, not only the data were collected using the accelerometers of a smartphone, but also models were implemented to the phone and the whole classification process (preprocessing, feature extraction and classification) was done on the device. The system is trained using phone orientation independent features to recognize five everyday activities: walking, running, cycling, driving a car and sitting/standing while the phone is in the pocket of the subject's trousers.
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