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

    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%.
    LanguageEnglish
    Title of host publicationUnknown Host Publication
    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 → …

    Fingerprint

    Watches
    Support vector machines
    Experiments
    Accelerometers
    Energy conservation
    Classifiers
    Sensors

    Keywords

    • Human Activity Recognition
    • Smart Watch
    • H-SVM

    Cite this

    Tang, T., Zheng, Q., Weng, S., Peng, A., & Zheng, H. (Accepted/In press). Human Activity Recognition with Smart Watch based on H-SVM. In Unknown Host Publication
    Tang, Tao ; Zheng, Qingxiang ; Weng, Shaolin ; Peng, Ao ; Zheng, Huiru. / Human Activity Recognition with Smart Watch based on H-SVM. Unknown Host Publication. 2016.
    @inproceedings{9e6d6592793f4dc98ae4c24f495f3568,
    title = "Human Activity Recognition with Smart Watch based on H-SVM",
    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{\%}.",
    keywords = "Human Activity Recognition, Smart Watch, H-SVM",
    author = "Tao Tang and Qingxiang Zheng and Shaolin Weng and Ao Peng and Huiru Zheng",
    year = "2016",
    month = "4",
    day = "8",
    language = "English",
    booktitle = "Unknown Host Publication",

    }

    Tang, T, Zheng, Q, Weng, S, Peng, A & Zheng, H 2016, Human Activity Recognition with Smart Watch based on H-SVM. in Unknown Host Publication. The 5th International Conference on Frontier Computing (FC 2016), 8/04/16.

    Human Activity Recognition with Smart Watch based on H-SVM. / Tang, Tao; Zheng, Qingxiang; Weng, Shaolin; Peng, Ao; Zheng, Huiru.

    Unknown Host Publication. 2016.

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

    TY - GEN

    T1 - Human Activity Recognition with Smart Watch based on H-SVM

    AU - Tang, Tao

    AU - Zheng, Qingxiang

    AU - Weng, Shaolin

    AU - Peng, Ao

    AU - Zheng, Huiru

    PY - 2016/4/8

    Y1 - 2016/4/8

    N2 - 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%.

    AB - 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%.

    KW - Human Activity Recognition

    KW - Smart Watch

    KW - H-SVM

    M3 - Conference contribution

    BT - Unknown Host Publication

    ER -

    Tang T, Zheng Q, Weng S, Peng A, Zheng H. Human Activity Recognition with Smart Watch based on H-SVM. In Unknown Host Publication. 2016