{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T21:48:05Z","timestamp":1780696085767,"version":"3.54.1"},"reference-count":24,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,12,25]],"date-time":"2020-12-25T00:00:00Z","timestamp":1608854400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2017R1A5A1015596"],"award-info":[{"award-number":["NRF-2017R1A5A1015596"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Continuous blood pressure (BP) monitoring is important for patients with hypertension. However, BP measurement with a cuff may be cumbersome for the patient. To overcome this limitation, various studies have suggested cuffless BP estimation models using deep learning algorithms. A generalized model should be considered to decrease the training time, and the model reproducibility should be taken into account in multi-day scenarios. In this study, a BP estimation model with a bidirectional long short-term memory network is proposed. The features are extracted from the electrocardiogram, photoplethysmogram, and ballistocardiogram. The leave-one-subject-out (LOSO) method is incorporated to generalize the model and fine-tuning is applied. The model was evaluated using one-day and multi-day tests. The proposed model achieved a mean absolute error (MAE) of 2.56 and 2.05 mmHg for the systolic and diastolic BP (SBP and DBP), respectively, in the one-day test. Moreover, the results demonstrated that the LOSO method with fine-tuning was more compatible in the multi-day test. The MAE values of the model were 5.82 and 5.24 mmHg for the SBP and DBP, respectively.<\/jats:p>","DOI":"10.3390\/s21010096","type":"journal-article","created":{"date-parts":[[2020,12,25]],"date-time":"2020-12-25T09:30:19Z","timestamp":1608888619000},"page":"96","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Beat-to-Beat Continuous Blood Pressure Estimation Using Bidirectional Long Short-Term Memory Network"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6960-9127","authenticated-orcid":false,"given":"Dongseok","family":"Lee","sequence":"first","affiliation":[{"name":"Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 03080, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyunbin","family":"Kwon","sequence":"additional","affiliation":[{"name":"Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 03080, Korea"},{"name":"Medical Research Center, Institute of Medical and Biological Engineering, Seoul National University, Seoul 03080, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9102-7107","authenticated-orcid":false,"given":"Dongyeon","family":"Son","sequence":"additional","affiliation":[{"name":"Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 03080, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7418-5042","authenticated-orcid":false,"given":"Heesang","family":"Eom","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Kwangwoon University, Seoul 01897, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheolsoo","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Kwangwoon University, Seoul 01897, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yonggyu","family":"Lim","sequence":"additional","affiliation":[{"name":"Department of Oriental Biomedical Engineering, Sangji University, Wonju 26339, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chulhun","family":"Seo","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Soongsil University, Seoul 06978, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwangsuk","family":"Park","sequence":"additional","affiliation":[{"name":"Medical Research Center, Institute of Medical and Biological Engineering, Seoul National University, Seoul 03080, Korea"},{"name":"Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1016\/j.ccl.2010.07.006","article-title":"Principles and techniques of blood pressure measurement","volume":"28","author":"Ogedegbe","year":"2010","journal-title":"Cardiol. 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