Human Activity Recognition with Smart Watch based on H-SVM

Tao Tang, Qingxiang Zheng, Shaolin Weng, Ao Peng, Huiru Zheng

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    Abstract

    Activity recognition allows ubiquitous wearable device like smart watch to simplify the study and experiment. It is very convenient and extensibil-ity that we do study with the accelerometer sensor of a smart watch. In this paper, we use Samsung GEAR smart watch to collect data, then extract features, classify with H-SVM (Hierarchical Support Vector Machine) classifier and identify hu-man activities classification. Experiment results show great effect at low sam-pling rate, such as 10 Hz and 5 Hz, which will give us the energy saving. In most cases, the accuracies of activity recognition experiment are above 99%.
    Original languageEnglish
    Title of host publicationUnknown Host Publication
    PublisherAssociation for Computing Machinery
    Number of pages8
    Publication statusAccepted/In press - 8 Apr 2016
    EventThe 5th International Conference on Frontier Computing (FC 2016) -
    Duration: 8 Apr 2016 → …

    Conference

    ConferenceThe 5th International Conference on Frontier Computing (FC 2016)
    Period8/04/16 → …

    Keywords

    • Human Activity Recognition
    • Smart Watch
    • H-SVM

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