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Paper Abstract and Keywords
Presentation 2019-01-29 10:50
MUSIC Algorithm-based Heart Rate Estimation with Doppler Sensor
Kohei Yamamoto, Kentaroh Toyoda, Tomoaki Ohtsuki (Keio Univ.) ASN2018-89
Abstract (in Japanese) (See Japanese page) 
(in English) Heartbeat is one of the major signals that provide the crucial information on our health. Specifically, the HR (Heart Rate) is known to be highly related with our stress, which motivates researchers to develop HR estimation technique for the stress estimation. A Doppler sensor could be a device to facilitate the non-contact HR estimation. As one of Doppler sensor-based HR estimation methods, the MUSIC (MUltiple SIgnal Classification)-algorithm based HR estimation method has been proposed. However, the conventional MUSIC algorithm-based HR estimation method not only needs a long time window, but also requires to estimate the number of sinusoidal signals composing the analyzed signals, P, which is challenging. In this paper, we propose a novel MUSIC-based HR estimation method with the DCT (Discrete Cosine Transform)-based parameter P estimation. In the proposed method, the analyzed signal is firstly decomposed by DCT.
P is then estimated by extracting components that might be related with heartbeats. The signal reconstruction is performed by the inverse DCT based on only such P components, which not only results in the reconstructed signal consisting of P sinusoidal signals, but also reduces the effect of the noise due to respiration and body movements within a time window so that the HR is estimated accurately even with a short time window. Finally, the HR is estimated by MUSIC with the estimated P. Through the experiments on 10 subjects, we confirmed that our method outperformed the conventional one by the estimation accuracy of the HR and the stress indexes such as CVI (Cardiac Vagal Index) and CSI (Cardiac Sympathetic Index).
Keyword (in Japanese) (See Japanese page) 
(in English) Doppler sensor / Heart rate estimation / Stress estimation / Health care / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 428, ASN2018-89, pp. 59-64, Jan. 2019.
Paper # ASN2018-89 
Date of Issue 2019-01-21 (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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Conference Information
Committee ASN  
Conference Date 2019-01-28 - 2019-01-29 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyuukamura Ibusuki 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Ambient intelligence, Sensor networks, Poster session, etc. 
Paper Information
Registration To ASN 
Conference Code 2019-01-ASN 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) MUSIC Algorithm-based Heart Rate Estimation with Doppler Sensor 
Sub Title (in English)  
Keyword(1) Doppler sensor  
Keyword(2) Heart rate estimation  
Keyword(3) Stress estimation  
Keyword(4) Health care  
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1st Author's Name Kohei Yamamoto  
1st Author's Affiliation Keio University (Keio Univ.)
2nd Author's Name Kentaroh Toyoda  
2nd Author's Affiliation Keio University (Keio Univ.)
3rd Author's Name Tomoaki Ohtsuki  
3rd Author's Affiliation Keio University (Keio Univ.)
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Speaker Author-1 
Date Time 2019-01-29 10:50:00 
Presentation Time 25 minutes 
Registration for ASN 
Paper # ASN2018-89 
Volume (vol) vol.118 
Number (no) no.428 
Page pp.59-64 
#Pages 6 
Date of Issue 2019-01-21 (ASN) 

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