| Paper Abstract and Keywords |
| Presentation |
2024-09-05 10:30
Dependence of green light photoplethysmogram dynamical properties extraction on the time series length. Sora Okazaki, Nina Sviridova (TCU) NLP2024-41 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Photoplethysmogram (PPG) is pulse wave data obtained by projecting infrared, red, or green light to capture the volume changes in blood vessels caused by the heart’s blood pumping. It is used for measuring blood pressure, heart rate, and oxygen saturation. Green light, commonly used in smartwatches, allows measuring signals with higher accuracy due to its higher absorption coefficient in hemoglobin and lesser influence from non-blood tissues. Furthermore, it can be used to identify physiological and psychological health conditions based on the dynamical characteristics of the signals. Dynamical characteristics can be extracted by nonlinear time series analysis methods, which are sensitive to the quality of data recordings. This study investigates the dependency of extracting dynamic properties of green PPG from time series length using recurrence quantification analysis. The lower limit of the time series length is estimated to improve the applicability of the nonlinear analysis and reduce its calculation costs. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Time series length / Nonlinear time series / Recurrence plot / Recurrence quantification analysis / Green light photoplethysmogram / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 124, no. 178, NLP2024-41, pp. 1-5, Sept. 2024. |
| Paper # |
NLP2024-41 |
| Date of Issue |
2024-08-29 (NLP) |
| 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 |
NLP2024-41 |
| Conference Information |
| Committee |
NLP |
| Conference Date |
2024-09-05 - 2024-09-06 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Takayama City Library |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Nonlinear Problems, etc. |
| Paper Information |
| Registration To |
NLP |
| Conference Code |
2024-09-NLP |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Dependence of green light photoplethysmogram dynamical properties extraction on the time series length. |
| Sub Title (in English) |
|
| Keyword(1) |
Time series length |
| Keyword(2) |
Nonlinear time series |
| Keyword(3) |
Recurrence plot |
| Keyword(4) |
Recurrence quantification analysis |
| Keyword(5) |
Green light photoplethysmogram |
| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Sora Okazaki |
| 1st Author's Affiliation |
Tokyo City University (TCU) |
| 2nd Author's Name |
Nina Sviridova |
| 2nd Author's Affiliation |
Tokyo City University (TCU) |
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| Speaker |
Author-1 |
| Date Time |
2024-09-05 10:30:00 |
| Presentation Time |
25 minutes |
| Registration for |
NLP |
| Paper # |
NLP2024-41 |
| Volume (vol) |
vol.124 |
| Number (no) |
no.178 |
| Page |
pp.1-5 |
| #Pages |
5 |
| Date of Issue |
2024-08-29 (NLP) |