Paper Abstract and Keywords |
Presentation |
2019-03-05 14:00
Development of Doppler CSI model for Wi-Fi based hand gesture detection application Nopphon Keerativoranan, Jun-ichi Takada (TiTech) ASN2018-111 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
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 non-line-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. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Channel state information / Wireless LAN / Motion detection / bistaic Doppler radar / Time-variant channel model / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 468, ASN2018-111, pp. 175-180, March 2019. |
Paper # |
ASN2018-111 |
Date of Issue |
2019-02-25 (ASN) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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ASN2018-111 |
Conference Information |
Committee |
ASN MoNA IPSJ-MBL IPSJ-UBI |
Conference Date |
2019-03-04 - 2019-03-05 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
The University of Tokyo, Komaba Campus |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
General |
Paper Information |
Registration To |
ASN |
Conference Code |
2019-03-ASN-MoNA-MBL-UBI |
Language |
English |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Development of Doppler CSI model for Wi-Fi based hand gesture detection application |
Sub Title (in English) |
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Channel state information |
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Wireless LAN |
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Motion detection |
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bistaic Doppler radar |
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Time-variant channel model |
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1st Author's Name |
Nopphon Keerativoranan |
1st Author's Affiliation |
Tokyo Institute of Technology (TiTech) |
2nd Author's Name |
Jun-ichi Takada |
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Tokyo Institute of Technology (TiTech) |
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Speaker |
Author-1 |
Date Time |
2019-03-05 14:00:00 |
Presentation Time |
25 minutes |
Registration for |
ASN |
Paper # |
ASN2018-111 |
Volume (vol) |
vol.118 |
Number (no) |
no.468 |
Page |
pp.175-180 |
#Pages |
6 |
Date of Issue |
2019-02-25 (ASN) |
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