Gesture Recognition Method Utilizing Ultrasonic Active Acoustic Sensing

DOI DOI HANDLE Web Site Web Site 1 Citations 17 References Open Access
  • Watanabe Hiroki
    Graduate School of Engineering, Kobe University Research Fellow of Japan Society for the Promotion of Scienece
  • Terada Tsutomu
    Graduate School of Engineering, Kobe University PRESTO, Japan Science and Technology Agency
  • Tsukamoto Masahiko
    Graduate School of Engineering, Kobe University

Bibliographic Information

Other Title
  • Editor's Message to Special Issue on “Towards Secure Society Considering Things and Human Aspects”

Search this article

Description

<p>We propose a method for gesture recognition that utilizes active acoustic sensing, which transmits acoustic signals to a target, and recognizes the target's state by analyzing the response. In this study, the user wore a contact speaker that transmitted ultrasonic sweep signals to the user's body and a contact microphone that detected the ultrasound propagated through the body. The propagation characteristics of the ultrasound changed depending on the user's movements. We utilized these changes to recognize the user's gestures. One of the important novelty features of our method is that the user's gestures can be acquired not only from the physical movement but also from the user's internal state, such as muscle activity, since ultrasound is transmitted via both the user's internal body and body surface. Moreover, our method is not adversely affected by audible-range sounds generated by the environment and body movements because we utilize ultrasound. We implemented a device that uses active acoustic sensing to effectively transmit/detect the ultrasound to/from the body and investigated the performance of the proposed method in 21 contexts with 10 subjects. The evaluation results confirmed that the precision and recall are 93.1% and 91.6%, respectively when we set 10% of the data as training data and the rest as testing data in the same data set. When we used the data set for training and the other data set for testing in the same day, the precision and recall are 51.6% and 51.3%, respectively.</p>

Journal

Citations (1)*help

See more

References(17)*help

See more

Related Projects

See more

Keywords

Details 詳細情報について

Report a problem

Back to top