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Paper Abstract and Keywords
Presentation 2021-01-25 17:10
Low Power EEG Measurement Using Compressed Sensing Consideration of the Sampling Interval
Yuki Okabe, Daisuke Kanemoto (Osaka Univ.), Tomoya Mochizuki (Yamanashi Univ.), Osamu Maida, Tetsuya Hirose (Osaka Univ.) VLD2020-53 CPSY2020-36 RECONF2020-72
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, wireless EEG measurement devices that cause less discomfort to the subject have attracted much attention. Therefore, it is necessary to reduce the size of the battery installed in the wireless EEG measurement device, and low power consumption of the circuit is required. We are investigating compressed sensing EEG measurement framework. In the past, A/D conversion with random under sampling was used for compressing the data and complete random sampling was used for compressed sensing. This method is expected to significantly reduce the power consumption of wireless devices. In this study, we investigated a method to control the sampling interval in compressed sensing in order to achieve further reduction of power consumption in the implemented circuit.
Keyword (in Japanese) (See Japanese page) 
(in English) EEG / low-power consumption / Compressed Sensing / Independent Component Analysis / Random-Matrix / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 337, VLD2020-53, pp. 80-84, Jan. 2021.
Paper # VLD2020-53 
Date of Issue 2021-01-18 (VLD, CPSY, RECONF) 
ISSN Online edition: ISSN 2432-6380
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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)
Download PDF VLD2020-53 CPSY2020-36 RECONF2020-72

Conference Information
Committee CPSY RECONF VLD IPSJ-ARC IPSJ-SLDM  
Conference Date 2021-01-25 - 2021-01-26 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) FPGA Applications, etc. 
Paper Information
Registration To VLD 
Conference Code 2021-01-CPSY-RECONF-VLD-ARC-SLDM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Low Power EEG Measurement Using Compressed Sensing Consideration of the Sampling Interval 
Sub Title (in English)  
Keyword(1) EEG  
Keyword(2) low-power consumption  
Keyword(3) Compressed Sensing  
Keyword(4) Independent Component Analysis  
Keyword(5) Random-Matrix  
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1st Author's Name Yuki Okabe  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Daisuke Kanemoto  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Tomoya Mochizuki  
3rd Author's Affiliation Yamanashi University (Yamanashi Univ.)
4th Author's Name Osamu Maida  
4th Author's Affiliation Osaka University (Osaka Univ.)
5th Author's Name Tetsuya Hirose  
5th Author's Affiliation Osaka University (Osaka Univ.)
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Speaker Author-1 
Date Time 2021-01-25 17:10:00 
Presentation Time 25 minutes 
Registration for VLD 
Paper # VLD2020-53, CPSY2020-36, RECONF2020-72 
Volume (vol) vol.120 
Number (no) no.337(VLD), no.338(CPSY), no.339(RECONF) 
Page pp.80-84 
#Pages
Date of Issue 2021-01-18 (VLD, CPSY, RECONF) 


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