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| Presentation | 2023-01-20 10:20 Arterial Blood Pressure Waveform Estimation from Photoplethysmogram under Inter-subject Paradigm by U-Net and Domain Adversarial Training Rikuto Yoshizawa, Kohei Yamamoto, Tomoaki Ohtsuki (Keio)  SeMI2022-96 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Blood pressure (BP) estimation methods using photoplethysmogram (PPG) signals based on deep learning models have been actively studied. These methods are also the basis of non-contact BP estimation methods using a camera or a Doppler radar. However, the performance evaluations of many previous studies are under data leakage. To properly evaluate the generalizability of BP estimation models, the evaluation should be performed under the experimental condition that subjects are completely separated between training and test data (inter-subject paradigm). In this research, we propose a BP estimation method from PPG signals under inter-subject paradigm using a subject-distinguishable large public dataset. Our BP estimation method estimates an 8-second BP waveform called arterial BP (ABP) from an 8-second PPG segment using U-Net. From the estimated ABP, systolic BP (SBP), diastolic BP (DBP), and mean BP (MBP) are calculated, which are the discrete single values for the 8-second ABP. In addition, we apply domain adversarial training, which facilitates the BP estimation model to extract subject-invariant features for improving BP estimation accuracy under inter-subject paradigm. Our experimental results showed that our method can estimate BP with moderate accuracy under inter-subject paradigm, particularly MBP. The mean absolute errors for the estimated SBP, DBP, MBP, and ABP were 15.21, 7.12, 8.20, and 10.14 mmHg, respectively. The Pearson’s correlation coefficients between the true and estimated values were 0.49, 0.39, 0.54, and 0.84, respectively. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Blood pressure / Photoplethysmogram / Deep learning / Inter-subject / Domain adversarial training / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 341, SeMI2022-96, pp. 113-118, Jan. 2023. | |
| Paper # | SeMI2022-96 | |
| Date of Issue | 2023-01-12 (SeMI) | |
| 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 | SeMI2022-96 |
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| Conference Information | |
| Committee | SeMI SeMI |
| Conference Date | 2023-01-19 - 2023-01-20 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Naruto grand hotel |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SeMI |
| Conference Code | 2023-01-SeMI-SeMI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Arterial Blood Pressure Waveform Estimation from Photoplethysmogram under Inter-subject Paradigm by U-Net and Domain Adversarial Training |
| Sub Title (in English) | |
| Keyword(1) | Blood pressure |
| Keyword(2) | Photoplethysmogram |
| Keyword(3) | Deep learning |
| Keyword(4) | Inter-subject |
| Keyword(5) | Domain adversarial training |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Rikuto Yoshizawa |
| 1st Author's Affiliation | Keio University (Keio) |
| 2nd Author's Name | Kohei Yamamoto |
| 2nd Author's Affiliation | Keio University (Keio) |
| 3rd Author's Name | Tomoaki Ohtsuki |
| 3rd Author's Affiliation | Keio University (Keio) |
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| Speaker | Author-1 |
| Date Time | 2023-01-20 10:20:00 |
| Presentation Time | 10 minutes |
| Registration for | SeMI |
| Paper # | SeMI2022-96 |
| Volume (vol) | vol.122 |
| Number (no) | no.341 |
| Page | pp.113-118 |
| #Pages | 6 |
| Date of Issue | 2023-01-12 (SeMI) |
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