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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2012
    • vol. 1, nº 5, june 2012
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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2012
    • vol. 1, nº 5, june 2012
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    Recognizing Human Activities Userindependently on Smartphones Based on Accelerometer Data

    Autor: 
    Siirtola, Pekka
    ;
    Röning, Juha
    Fecha: 
    06/2012
    Palabra clave: 
    activity recognition; classification; mobile phones; IJIMAI
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/9597
    DOI: 
    http://dx.doi.org/10.9781/ijimai.2012.155
    Dirección web: 
    https://www.ijimai.org/journal/node/225
    Open Access
    Resumen:
    Real-time human activity recognition on a mobile phone is presented in this article. 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. Two classifiers were compared, knn (k nearest neighbors) and QDA (quadratic discriminant analysis). The models for real-time activity recognition were trained offline using a data set collected from eight subjects and these offline results were compared to real-time recognition rates, which are obtained by implementing models to mobile activity recognition application which currently supports two operating systems: Symbian^3 and Android. The results show that the presented method is light and, therefore, suitable for be used in real-time recognition. In addition, the recognition rates on the smartphones were encouraging, in fact, the recognition accuracies obtained are approximately as high as offline recognition rates. Also, the results show that the method presented is not an operating system dependent.
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    • vol. 1, nº 5, june 2012

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