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Teach Your WiFi-Device: Recognise Simultaneous Activities and Gestures from Time-Domain RF-Features

Author

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  • Stephan Sigg

    (Goettingen University, Goettingen, Germany)

  • Shuyu Shi

    (Department of Informatics, Graduate University for Advanced Studies, Japan)

  • Yusheng Ji

    (Department of Informatics, Graduate University for Advanced Studies, Japan)

Abstract

The authors consider two untackled problems in RF-based activity recognition: the distinction of simultaneously conducted activities of individuals and the recognition of gestures from purely time-domain-based features. Recognition is based on a single antenna system. This is important for the application in end-user devices which are usually single-antenna systems and have seldom access to more sophisticated, e.g. frequency-based features. In case studies with software defined radio nodes utilised in an active, device-free activity recognition (DFAR) system, the authors observe a good recognition accuracy for the detection of multiple simultaneously conducted activities with two and more receive devices. Four gestures and two baseline situations are distinguished with good accuracy in a second case study.

Suggested Citation

  • Stephan Sigg & Shuyu Shi & Yusheng Ji, 2014. "Teach Your WiFi-Device: Recognise Simultaneous Activities and Gestures from Time-Domain RF-Features," International Journal of Ambient Computing and Intelligence (IJACI), IGI Global, vol. 6(1), pages 20-34, January.
    • Handle: RePEc:igg:jaci00:v:6:y:2014:i:1:p:20-34
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