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Paper Abstract and Keywords
Presentation 2015-03-03 10:45
[Poster Presentation] Analysis of Apnea Hypopnea Index (AHI) Prediction Model by Breath sounds
Yuki Kashina, Nichito Nakata, Naoto Sakata, Hirofumi Nakajima (Kogakuin Univ.), Yasuhiro Yamaguchi (UTokyo) EA2014-113 SIP2014-154 SP2014-176
Abstract (in Japanese) (See Japanese page) 
(in English) Sleep Apnea Syndrome (SAS) is a type of sleep disorder that causes behavioral effects such as the daytime sleepiness. As it has been reported that the daytime sleepiness may lead to a car accident at the end, the early detection of the disorder is desirable. The previous report by the authors proposed a prediction model for Apnea Hypopnea Index (AHI) that is a diagnostic criterion for SAS. The model predicts AHI based on breath sounds during sleep. However, as the evaluations for the model and errors were performed among few subjects, it would be insufficient as a practical use in terms of the number of subjects. This report presents an investigation for the effectiveness of noises during sleep on prediction accuracy. As a result, it was found that the prediction accuracy was relatively stable even if the noises during sleep were around. Moreover, the results indicated the high generalization ability of the proposed model and that the prediction errors among the subjects were lower than 3%.
Keyword (in Japanese) (See Japanese page) 
(in English) Sleep Apnea Syndrome / Apnea Hypopnea Index / Breath sounds / Snoring sounds / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 473, EA2014-113, pp. 225-230, March 2015.
Paper # EA2014-113 
Date of Issue 2015-02-23 (EA, SIP, SP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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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 EA2014-113 SIP2014-154 SP2014-176

Conference Information
Committee SIP EA SP  
Conference Date 2015-03-02 - 2015-03-03 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To EA 
Conference Code 2015-03-SIP-EA-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Analysis of Apnea Hypopnea Index (AHI) Prediction Model by Breath sounds 
Sub Title (in English)  
Keyword(1) Sleep Apnea Syndrome  
Keyword(2) Apnea Hypopnea Index  
Keyword(3) Breath sounds  
Keyword(4) Snoring sounds  
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1st Author's Name Yuki Kashina  
1st Author's Affiliation Kogakuin University (Kogakuin Univ.)
2nd Author's Name Nichito Nakata  
2nd Author's Affiliation Kogakuin University (Kogakuin Univ.)
3rd Author's Name Naoto Sakata  
3rd Author's Affiliation Kogakuin University (Kogakuin Univ.)
4th Author's Name Hirofumi Nakajima  
4th Author's Affiliation Kogakuin University (Kogakuin Univ.)
5th Author's Name Yasuhiro Yamaguchi  
5th Author's Affiliation The University of tokyo (UTokyo)
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Speaker Author-1 
Date Time 2015-03-03 10:45:00 
Presentation Time 90 minutes 
Registration for EA 
Paper # EA2014-113, SIP2014-154, SP2014-176 
Volume (vol) vol.114 
Number (no) no.473(EA), no.474(SIP), no.475(SP) 
Page pp.225-230 
#Pages
Date of Issue 2015-02-23 (EA, SIP, SP) 


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