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  1. 研究報告
  2. モバイルコンピューティングと新社会システム(MBL)
  3. 2019
  4. 2019-MBL-090

Development of Doppler CSI model for Wi-Fi based Hand Gesture Detection Application

https://ipsj.ixsq.nii.ac.jp/records/194583
https://ipsj.ixsq.nii.ac.jp/records/194583
bb3d930f-75eb-4020-8e57-6c6cd82c062e
名前 / ファイル ライセンス アクション
IPSJ-MBL19090031.pdf IPSJ-MBL19090031.pdf (580.4 kB)
Copyright (c) 2019 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG.
MBL:会員:¥0, DLIB:会員:¥0
Item type SIG Technical Reports(1)
公開日 2019-02-25
タイトル
タイトル Development of Doppler CSI model for Wi-Fi based Hand Gesture Detection Application
タイトル
言語 en
タイトル Development of Doppler CSI model for Wi-Fi based Hand Gesture Detection Application
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_18gh
資源タイプ technical report
著者所属
Department of Transdiciplinary Science and Engineering School of Environment and Society, Tokyo Institute of Technology
著者所属
Department of Transdiciplinary Science and Engineering School of Environment and Society, Tokyo Institute of Technology
著者所属(英)
en
Department of Transdiciplinary Science and Engineering School of Environment and Society, Tokyo Institute of Technology
著者所属(英)
en
Department of Transdiciplinary Science and Engineering School of Environment and Society, Tokyo Institute of Technology
著者名 Nopphon, Keerativoranan

× Nopphon, Keerativoranan

Nopphon, Keerativoranan

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Jun-ichi, Takada

× Jun-ichi, Takada

Jun-ichi, Takada

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著者名(英) Nopphon, Keerativoranan

× Nopphon, Keerativoranan

en Nopphon, Keerativoranan

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Jun-ichi, Takada

× Jun-ichi, Takada

en Jun-ichi, Takada

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論文抄録
内容記述タイプ Other
内容記述 Various studies have proposed the use of RF signals to realize a non-wearable hand gesture sensing applications in the environments where commercial vision-based motion sensing cannot properly operate such as nonline-of-sight (NLoS) environment and private places. One way to sense the hand motion is through the Doppler frequency extracted from channel state information (CSI) of Wi-Fi chips. Although many works have proposed the solutions for CSI-based hand gesture sensing, there is no model that could properly explain the behavior of hand movement in terms of Doppler profiles. In this paper, the deterministic CSI Doppler model has been developed which describes the Doppler frequency profile caused by particular gestures. Through simulation and discussion, it was found that Doppler frequency profile depends on the speed of the motion, position, and trajectory relative to transmitter and receiver. The density of the Doppler power spectrum is the result of the constructive accumulation of a various number of propagation paths experiencing similar Doppler frequency shift. In addition, the proposed model could be beneficial for the gesture recognition as it could generate the Doppler profile for pattern training.
論文抄録(英)
内容記述タイプ Other
内容記述 Various studies have proposed the use of RF signals to realize a non-wearable hand gesture sensing applications in the environments where commercial vision-based motion sensing cannot properly operate such as nonline-of-sight (NLoS) environment and private places. One way to sense the hand motion is through the Doppler frequency extracted from channel state information (CSI) of Wi-Fi chips. Although many works have proposed the solutions for CSI-based hand gesture sensing, there is no model that could properly explain the behavior of hand movement in terms of Doppler profiles. In this paper, the deterministic CSI Doppler model has been developed which describes the Doppler frequency profile caused by particular gestures. Through simulation and discussion, it was found that Doppler frequency profile depends on the speed of the motion, position, and trajectory relative to transmitter and receiver. The density of the Doppler power spectrum is the result of the constructive accumulation of a various number of propagation paths experiencing similar Doppler frequency shift. In addition, the proposed model could be beneficial for the gesture recognition as it could generate the Doppler profile for pattern training.
書誌レコードID
収録物識別子タイプ NCID
収録物識別子 AA11851388
書誌情報 研究報告モバイルコンピューティングとパーベイシブシステム(MBL)

巻 2019-MBL-90, 号 31, p. 1-6, 発行日 2019-02-25
ISSN
収録物識別子タイプ ISSN
収録物識別子 2188-8817
Notice
SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
出版者
言語 ja
出版者 情報処理学会
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