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 contributionpeer-review

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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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