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Paper Abstract and Keywords
Presentation 2022-01-21 14:05
Verification of gender identifiability and its sensitivity from heart rate data in Allstar heart rate variability big data analysis
Itaru Kaneko, Emi Yuda (Tohoku Univ.) NLP2021-85 MICT2021-60 MBE2021-46
Abstract (in Japanese) (See Japanese page) 
(in English) We have verified the analysis of Allstar heart rate big data (big data of heart rate that we are analyzing). This time, we have verified whether the gender can be identified from the heart rate big data. After 10-dimensional statistic extraction for 12,000 heartbeat data, gender identification was performed on them by various discrimination method. Lasso, linear regression, SVM, Random Forest, logistic regression, K-means, Elastic Net were compared. The best Accuracy / r2 score was 0.66 for logistic regression. Although it is possible to identify the gender to some extent by the identification based on these statistics, it was confirmed that the accuracy is not sufficient to identify the gender.
Keyword (in Japanese) (See Japanese page) 
(in English) Allstar heart rate big data / Gender / SVM / Random Forest / privacy / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 337, MBE2021-46, pp. 50-53, Jan. 2022.
Paper # MBE2021-46 
Date of Issue 2022-01-14 (NLP, MICT, MBE) 
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)
Download PDF NLP2021-85 MICT2021-60 MBE2021-46

Conference Information
Committee NLP MICT MBE NC  
Conference Date 2022-01-21 - 2022-01-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MBE 
Conference Code 2022-01-NLP-MICT-MBE-NC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Verification of gender identifiability and its sensitivity from heart rate data in Allstar heart rate variability big data analysis 
Sub Title (in English)  
Keyword(1) Allstar heart rate big data  
Keyword(2) Gender  
Keyword(3) SVM  
Keyword(4) Random Forest  
Keyword(5) privacy  
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Keyword(8)  
1st Author's Name Itaru Kaneko  
1st Author's Affiliation Tohoku University (Tohoku Univ.)
2nd Author's Name Emi Yuda  
2nd Author's Affiliation Tohoku University (Tohoku Univ.)
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Speaker Author-1 
Date Time 2022-01-21 14:05:00 
Presentation Time 25 minutes 
Registration for MBE 
Paper # NLP2021-85, MICT2021-60, MBE2021-46 
Volume (vol) vol.121 
Number (no) no.335(NLP), no.336(MICT), no.337(MBE) 
Page pp.50-53 
#Pages 4 
Date of Issue 2022-01-14 (NLP, MICT, MBE) 

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