{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T18:13:55Z","timestamp":1774030435035,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2023,9,16]],"date-time":"2023-09-16T00:00:00Z","timestamp":1694822400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Medical Research Council Singapore","award":["STAR19may-0001"],"award-info":[{"award-number":["STAR19may-0001"]}]},{"name":"National Medical Research Council Singapore","award":["NUHSRO\/2020\/124\/TMR\/LOA"],"award-info":[{"award-number":["NUHSRO\/2020\/124\/TMR\/LOA"]}]},{"name":"National Medical Research Council Singapore","award":["OFLCG19May-0035"],"award-info":[{"award-number":["OFLCG19May-0035"]}]},{"name":"National Medical Research Council Singapore","award":["CTGIIT23jan-0001"],"award-info":[{"award-number":["CTGIIT23jan-0001"]}]},{"name":"National Medical Research Council Singapore","award":["STaR20nov-0003"],"award-info":[{"award-number":["STaR20nov-0003"]}]},{"name":"National Medical Research Council Singapore","award":["CG21APR1009"],"award-info":[{"award-number":["CG21APR1009"]}]},{"name":"National Medical Research Council Singapore","award":["TF2223-IMH-01"],"award-info":[{"award-number":["TF2223-IMH-01"]}]},{"name":"National Medical Research Council Singapore","award":["R01MH120080"],"award-info":[{"award-number":["R01MH120080"]}]},{"name":"National Medical Research Council Singapore","award":["R01MH133334"],"award-info":[{"award-number":["R01MH133334"]}]},{"name":"NUS Yong Loo Lin School of Medicine","award":["STAR19may-0001"],"award-info":[{"award-number":["STAR19may-0001"]}]},{"name":"NUS Yong Loo Lin School of Medicine","award":["NUHSRO\/2020\/124\/TMR\/LOA"],"award-info":[{"award-number":["NUHSRO\/2020\/124\/TMR\/LOA"]}]},{"name":"NUS Yong Loo Lin School of Medicine","award":["OFLCG19May-0035"],"award-info":[{"award-number":["OFLCG19May-0035"]}]},{"name":"NUS Yong Loo Lin School of Medicine","award":["CTGIIT23jan-0001"],"award-info":[{"award-number":["CTGIIT23jan-0001"]}]},{"name":"NUS Yong Loo Lin School of Medicine","award":["STaR20nov-0003"],"award-info":[{"award-number":["STaR20nov-0003"]}]},{"name":"NUS Yong Loo Lin School of Medicine","award":["CG21APR1009"],"award-info":[{"award-number":["CG21APR1009"]}]},{"name":"NUS Yong Loo Lin School of Medicine","award":["TF2223-IMH-01"],"award-info":[{"award-number":["TF2223-IMH-01"]}]},{"name":"NUS Yong Loo Lin School of Medicine","award":["R01MH120080"],"award-info":[{"award-number":["R01MH120080"]}]},{"name":"NUS Yong Loo Lin School of Medicine","award":["R01MH133334"],"award-info":[{"award-number":["R01MH133334"]}]},{"name":"Singapore National Medical Research Council (NMRC) LCG","award":["STAR19may-0001"],"award-info":[{"award-number":["STAR19may-0001"]}]},{"name":"Singapore National Medical Research Council (NMRC) LCG","award":["NUHSRO\/2020\/124\/TMR\/LOA"],"award-info":[{"award-number":["NUHSRO\/2020\/124\/TMR\/LOA"]}]},{"name":"Singapore National Medical Research Council (NMRC) LCG","award":["OFLCG19May-0035"],"award-info":[{"award-number":["OFLCG19May-0035"]}]},{"name":"Singapore National Medical Research Council (NMRC) LCG","award":["CTGIIT23jan-0001"],"award-info":[{"award-number":["CTGIIT23jan-0001"]}]},{"name":"Singapore National Medical Research Council (NMRC) LCG","award":["STaR20nov-0003"],"award-info":[{"award-number":["STaR20nov-0003"]}]},{"name":"Singapore National Medical Research Council (NMRC) LCG","award":["CG21APR1009"],"award-info":[{"award-number":["CG21APR1009"]}]},{"name":"Singapore National Medical Research Council (NMRC) LCG","award":["TF2223-IMH-01"],"award-info":[{"award-number":["TF2223-IMH-01"]}]},{"name":"Singapore National Medical Research Council (NMRC) LCG","award":["R01MH120080"],"award-info":[{"award-number":["R01MH120080"]}]},{"name":"Singapore National Medical Research Council (NMRC) LCG","award":["R01MH133334"],"award-info":[{"award-number":["R01MH133334"]}]},{"name":"NMRC CTG-IIT","award":["STAR19may-0001"],"award-info":[{"award-number":["STAR19may-0001"]}]},{"name":"NMRC CTG-IIT","award":["NUHSRO\/2020\/124\/TMR\/LOA"],"award-info":[{"award-number":["NUHSRO\/2020\/124\/TMR\/LOA"]}]},{"name":"NMRC CTG-IIT","award":["OFLCG19May-0035"],"award-info":[{"award-number":["OFLCG19May-0035"]}]},{"name":"NMRC CTG-IIT","award":["CTGIIT23jan-0001"],"award-info":[{"award-number":["CTGIIT23jan-0001"]}]},{"name":"NMRC CTG-IIT","award":["STaR20nov-0003"],"award-info":[{"award-number":["STaR20nov-0003"]}]},{"name":"NMRC CTG-IIT","award":["CG21APR1009"],"award-info":[{"award-number":["CG21APR1009"]}]},{"name":"NMRC CTG-IIT","award":["TF2223-IMH-01"],"award-info":[{"award-number":["TF2223-IMH-01"]}]},{"name":"NMRC CTG-IIT","award":["R01MH120080"],"award-info":[{"award-number":["R01MH120080"]}]},{"name":"NMRC CTG-IIT","award":["R01MH133334"],"award-info":[{"award-number":["R01MH133334"]}]},{"name":"NMRC STaR","award":["STAR19may-0001"],"award-info":[{"award-number":["STAR19may-0001"]}]},{"name":"NMRC STaR","award":["NUHSRO\/2020\/124\/TMR\/LOA"],"award-info":[{"award-number":["NUHSRO\/2020\/124\/TMR\/LOA"]}]},{"name":"NMRC STaR","award":["OFLCG19May-0035"],"award-info":[{"award-number":["OFLCG19May-0035"]}]},{"name":"NMRC STaR","award":["CTGIIT23jan-0001"],"award-info":[{"award-number":["CTGIIT23jan-0001"]}]},{"name":"NMRC STaR","award":["STaR20nov-0003"],"award-info":[{"award-number":["STaR20nov-0003"]}]},{"name":"NMRC STaR","award":["CG21APR1009"],"award-info":[{"award-number":["CG21APR1009"]}]},{"name":"NMRC STaR","award":["TF2223-IMH-01"],"award-info":[{"award-number":["TF2223-IMH-01"]}]},{"name":"NMRC STaR","award":["R01MH120080"],"award-info":[{"award-number":["R01MH120080"]}]},{"name":"NMRC STaR","award":["R01MH133334"],"award-info":[{"award-number":["R01MH133334"]}]},{"name":"Singapore Ministry of Health (MOH) Centre Grant","award":["STAR19may-0001"],"award-info":[{"award-number":["STAR19may-0001"]}]},{"name":"Singapore Ministry of Health (MOH) Centre Grant","award":["NUHSRO\/2020\/124\/TMR\/LOA"],"award-info":[{"award-number":["NUHSRO\/2020\/124\/TMR\/LOA"]}]},{"name":"Singapore Ministry of Health (MOH) Centre Grant","award":["OFLCG19May-0035"],"award-info":[{"award-number":["OFLCG19May-0035"]}]},{"name":"Singapore Ministry of Health (MOH) Centre Grant","award":["CTGIIT23jan-0001"],"award-info":[{"award-number":["CTGIIT23jan-0001"]}]},{"name":"Singapore Ministry of Health (MOH) Centre Grant","award":["STaR20nov-0003"],"award-info":[{"award-number":["STaR20nov-0003"]}]},{"name":"Singapore Ministry of Health (MOH) Centre Grant","award":["CG21APR1009"],"award-info":[{"award-number":["CG21APR1009"]}]},{"name":"Singapore Ministry of Health (MOH) Centre Grant","award":["TF2223-IMH-01"],"award-info":[{"award-number":["TF2223-IMH-01"]}]},{"name":"Singapore Ministry of Health (MOH) Centre Grant","award":["R01MH120080"],"award-info":[{"award-number":["R01MH120080"]}]},{"name":"Singapore Ministry of Health (MOH) Centre Grant","award":["R01MH133334"],"award-info":[{"award-number":["R01MH133334"]}]},{"name":"Temasek Foundation","award":["STAR19may-0001"],"award-info":[{"award-number":["STAR19may-0001"]}]},{"name":"Temasek Foundation","award":["NUHSRO\/2020\/124\/TMR\/LOA"],"award-info":[{"award-number":["NUHSRO\/2020\/124\/TMR\/LOA"]}]},{"name":"Temasek Foundation","award":["OFLCG19May-0035"],"award-info":[{"award-number":["OFLCG19May-0035"]}]},{"name":"Temasek Foundation","award":["CTGIIT23jan-0001"],"award-info":[{"award-number":["CTGIIT23jan-0001"]}]},{"name":"Temasek Foundation","award":["STaR20nov-0003"],"award-info":[{"award-number":["STaR20nov-0003"]}]},{"name":"Temasek Foundation","award":["CG21APR1009"],"award-info":[{"award-number":["CG21APR1009"]}]},{"name":"Temasek Foundation","award":["TF2223-IMH-01"],"award-info":[{"award-number":["TF2223-IMH-01"]}]},{"name":"Temasek Foundation","award":["R01MH120080"],"award-info":[{"award-number":["R01MH120080"]}]},{"name":"Temasek Foundation","award":["R01MH133334"],"award-info":[{"award-number":["R01MH133334"]}]},{"name":"United States National Institutes of Health","award":["STAR19may-0001"],"award-info":[{"award-number":["STAR19may-0001"]}]},{"name":"United States National Institutes of Health","award":["NUHSRO\/2020\/124\/TMR\/LOA"],"award-info":[{"award-number":["NUHSRO\/2020\/124\/TMR\/LOA"]}]},{"name":"United States National Institutes of Health","award":["OFLCG19May-0035"],"award-info":[{"award-number":["OFLCG19May-0035"]}]},{"name":"United States National Institutes of Health","award":["CTGIIT23jan-0001"],"award-info":[{"award-number":["CTGIIT23jan-0001"]}]},{"name":"United States National Institutes of Health","award":["STaR20nov-0003"],"award-info":[{"award-number":["STaR20nov-0003"]}]},{"name":"United States National Institutes of Health","award":["CG21APR1009"],"award-info":[{"award-number":["CG21APR1009"]}]},{"name":"United States National Institutes of Health","award":["TF2223-IMH-01"],"award-info":[{"award-number":["TF2223-IMH-01"]}]},{"name":"United States National Institutes of Health","award":["R01MH120080"],"award-info":[{"award-number":["R01MH120080"]}]},{"name":"United States National Institutes of Health","award":["R01MH133334"],"award-info":[{"award-number":["R01MH133334"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Background: Elevated nocturnal blood pressure (BP) is a risk factor for cardiovascular disease (CVD) and mortality. Cuffless BP assessment aided by machine learning could be a desirable alternative to traditional cuff-based methods for monitoring BP during sleep. We describe a machine-learning-based algorithm for predicting nocturnal BP using single-channel fingertip plethysmography (PPG) in healthy adults. Methods: Sixty-eight healthy adults with no apparent sleep or CVD (53% male), with a median (IQR) age of 29 (23\u201346 years), underwent overnight polysomnography (PSG) with fingertip PPG and ambulatory blood pressure monitoring (ABPM). Features based on pulse morphology were extracted from the PPG waveforms. Random forest models were used to predict night-time systolic blood pressure (SBP) and diastolic blood pressure (DBP). Results: Our model achieved the highest out-of-sample performance with a window length of 7 s across window lengths explored (60 s, 30 s, 15 s, 7 s, and 3 s). The mean absolute error (MAE \u00b1 STD) was 5.72 \u00b1 4.51 mmHg for SBP and 4.52 \u00b1 3.60 mmHg for DBP. Similarly, the root mean square error (RMSE \u00b1 STD) was 6.47 \u00b1 1.88 mmHg for SBP and 4.62 \u00b1 1.17 mmHg for DBP. The mean correlation coefficient between measured and predicted values was 0.87 for SBP and 0.86 for DBP. Based on Shapley additive explanation (SHAP) values, the most important PPG waveform feature was the stiffness index, a marker that reflects the change in arterial stiffness. Conclusion: Our results highlight the potential of machine learning-based nocturnal BP prediction using single-channel fingertip PPG in healthy adults. The accuracy of the predictions demonstrated that our cuffless method was able to capture the dynamic and complex relationship between PPG waveform characteristics and BP during sleep, which may provide a scalable, convenient, economical, and non-invasive means to continuously monitor blood pressure.<\/jats:p>","DOI":"10.3390\/s23187931","type":"journal-article","created":{"date-parts":[[2023,9,17]],"date-time":"2023-09-17T23:57:46Z","timestamp":1694995066000},"page":"7931","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Nocturnal Blood Pressure Estimation from Sleep Plethysmography Using Machine Learning"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4387-9276","authenticated-orcid":false,"given":"Gizem","family":"Yilmaz","sequence":"first","affiliation":[{"name":"Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingyu","family":"Lyu","sequence":"additional","affiliation":[{"name":"Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore"},{"name":"Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5115-4112","authenticated-orcid":false,"given":"Ju Lynn","family":"Ong","sequence":"additional","affiliation":[{"name":"Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lieng Hsi","family":"Ling","sequence":"additional","affiliation":[{"name":"Department of Cardiology, National University Heart Centre Singapore, Singapore 119074, Singapore"},{"name":"Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4304-0112","authenticated-orcid":false,"given":"Thomas","family":"Penzel","sequence":"additional","affiliation":[{"name":"Interdisciplinary Center of Sleep Medicine, Charit\u00e9\u2014Universit\u00e4tsmedizin Berlin, 10117 Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B. T. Thomas","family":"Yeo","sequence":"additional","affiliation":[{"name":"Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore"},{"name":"Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore"},{"name":"Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117549, Singapore"},{"name":"N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore 117549, Singapore"},{"name":"Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore 117549, Singapore"},{"name":"Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6087-0548","authenticated-orcid":false,"given":"Michael W. L.","family":"Chee","sequence":"additional","affiliation":[{"name":"Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,16]]},"reference":[{"key":"ref_1","unstructured":"NCD Risk Factor Collaboration (NCD-RisC) (2017). Worldwide trends in blood pressure from 1975 to 2015: A pooled analysis of 1479 population-based measurement studies with 19\u00b71 million participants. Lancet, 389, 37\u201355."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1269","DOI":"10.1161\/HYP.0000000000000066","article-title":"2017 ACC\/AHA\/AAPA\/ABC\/ACPM\/AGS\/APhA\/ASH\/ASPC\/NMA\/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: Executive Summary: A Report of the American College of Cardiology\/American Heart Association Task Force on Clinical Practice Guidelines","volume":"71","author":"Whelton","year":"2018","journal-title":"Hypertension"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3021","DOI":"10.1093\/eurheartj\/ehy339","article-title":"2018 ESC\/ESH Guidelines for the management of arterial hypertension: The Task Force for the management of arterial hypertension of the European Society of Cardiology (ESC) and the European Society of Hypertension (ESH)","volume":"39","author":"Williams","year":"2018","journal-title":"Eur. Heart J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1001\/jama.2019.9811","article-title":"Association of Office and Ambulatory Blood Pressure With Mortality and Cardiovascular Outcomes","volume":"322","author":"Yang","year":"2019","journal-title":"JAMA"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1038\/hr.2012.26","article-title":"Nocturnal blood pressure and cardiovascular disease: A review of recent advances","volume":"35","author":"Yano","year":"2012","journal-title":"Hypertens. Res."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Dey, J., Gaurav, A., and Tiwari, V.N. (2018, January 18\u201321). InstaBP: Cuff-less Blood Pressure Monitoring on Smartphone using Single PPG Sensor. Proceedings of the 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, USA.","DOI":"10.1109\/EMBC.2018.8513189"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Chowdhury, M.H., Shuzan, M.N.I., Chowdhury, M.E.H., Mahbub, Z.B., Uddin, M.M., Khandakar, A., and Reaz, M.B.I. (2020). Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques. Sensors, 20.","DOI":"10.3390\/s20113127"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"115655","DOI":"10.1109\/ACCESS.2021.3103763","article-title":"Beats-to-Beats Estimation of Blood Pressure During Supine Cycling Exercise Using a Probabilistic Nonparametric Method","volume":"9","author":"Liu","year":"2021","journal-title":"IEEE Access"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1879","DOI":"10.1109\/TBME.2015.2441951","article-title":"Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Theory and Practice","volume":"62","author":"Mukkamala","year":"2015","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.artmed.2011.05.001","article-title":"Non-invasive estimate of blood glucose and blood pressure from a photoplethysmograph by means of machine learning techniques","volume":"53","year":"2011","journal-title":"Artif. Intell. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"101870","DOI":"10.1016\/j.bspc.2020.101870","article-title":"A review of machine learning techniques in photoplethysmography for the non-invasive cuff-less measurement of blood pressure","volume":"58","author":"Kyriacou","year":"2020","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1038\/s41746-019-0136-7","article-title":"The use of photoplethysmography for assessing hypertension","volume":"2","author":"Elgendi","year":"2019","journal-title":"NPJ Digit. Med."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"H493","DOI":"10.1152\/ajpheart.00392.2021","article-title":"Assessing hemodynamics from the photoplethysmogram to gain insights into vascular age: A review from VascAgeNet","volume":"322","author":"Charlton","year":"2022","journal-title":"Am. J. Physiol. Heart Circ. Physiol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"044003","DOI":"10.1088\/1361-6579\/ab7d78","article-title":"Investigating the physiological mechanisms of the photoplethysmogram features for blood pressure estimation","volume":"41","author":"Lin","year":"2020","journal-title":"Physiol. Meas."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2007","DOI":"10.1016\/S0735-1097(99)00441-6","article-title":"Photoplethysmographic assessment of pulse wave reflection: Blunted response to endothelium-dependent beta2-adrenergic vasodilation in type II diabetes mellitus","volume":"34","author":"Chowienczyk","year":"1999","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"986","DOI":"10.1038\/s41598-022-27170-2","article-title":"Features from the photoplethysmogram and the electrocardiogram for estimating changes in blood pressure","volume":"13","author":"Finnegan","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Yilmaz, G., Ong, J.L., Ling, L.-H., and Chee, M.W.L. (2023). Insights Into Vascular Physiology From Sleep Photoplethysmography. Sleep, zsad172.","DOI":"10.1093\/sleep\/zsad172"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2427","DOI":"10.1097\/HJH.0000000000001111","article-title":"Vascular stiffness determined from a nocturnal digital pulse wave signal: Association with sleep, sleep-disordered breathing, and hypertension","volume":"34","author":"Svedmyr","year":"2016","journal-title":"J. Hypertens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"zsz322","DOI":"10.1093\/sleep\/zsz322","article-title":"Pulse wave amplitude drops during sleep: Clinical significance and characteristics in a general population sample","volume":"43","author":"Hirotsu","year":"2020","journal-title":"Sleep"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"102301","DOI":"10.1016\/j.bspc.2020.102301","article-title":"Deep learning models for cuffless blood pressure monitoring from PPG signals using attention mechanism","volume":"65","author":"Kyriacou","year":"2021","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Hsu, Y.-C., Li, Y.-H., Chang, C.-C., and Harfiya, L.N. (2020). Generalized Deep Neural Network Model for Cuffless Blood Pressure Estimation with Photoplethysmogram Signal Only. Sensors, 20.","DOI":"10.3390\/s20195668"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"58146","DOI":"10.1109\/ACCESS.2020.2981903","article-title":"Cuffless Blood Pressure Estimation Using Single Channel Photoplethysmography: A Two-Step Method","volume":"8","author":"Khalid","year":"2020","journal-title":"IEEE Access"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"025006","DOI":"10.1088\/1361-6579\/ab030e","article-title":"Estimating blood pressure trends and the nocturnal dip from photoplethysmography","volume":"40","author":"Radha","year":"2019","journal-title":"Physiol. Meas."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2179","DOI":"10.1109\/TBME.2014.2318779","article-title":"An Armband Wearable Device for Overnight and Cuff-Less Blood Pressure Measurement","volume":"61","author":"Zheng","year":"2014","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1161","DOI":"10.1161\/HYPERTENSIONAHA.121.17747","article-title":"Evaluation of the Accuracy of Cuffless Blood Pressure Measurement Devices: Challenges and Proposals","volume":"78","author":"Mukkamala","year":"2021","journal-title":"Hypertension"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"103392","DOI":"10.1016\/j.compbiomed.2019.103392","article-title":"SVR ensemble-based continuous blood pressure prediction using multi-channel photoplethysmogram","volume":"113","author":"Ng","year":"2019","journal-title":"Comput. Biol. Med."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Su, P., Ding, X.-R., Zhang, Y.-T., Liu, J., Miao, F., and Zhao, N. (2018, January 4). Long-term blood pressure prediction with deep recurrent neural networks. Proceedings of the 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), Las Vegas, NV, USA.","DOI":"10.1109\/BHI.2018.8333434"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1093\/sleep\/14.6.540","article-title":"A New Method for Measuring Daytime Sleepiness: The Epworth Sleepiness Scale","volume":"14","author":"Johns","year":"1991","journal-title":"Sleep"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1097\/MBP.0000000000000424","article-title":"Validation of the Spacelabs 90227 OnTrak device according to the European and British Hypertension Societies as well as the American protocols","volume":"25","author":"Shennan","year":"2020","journal-title":"Blood Press. Monit."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"105004","DOI":"10.1088\/1361-6579\/aae021","article-title":"An Open Source Benchmarked Toolbox for Cardiovascular Waveform and Interval Analysis","volume":"39","author":"Vest","year":"2018","journal-title":"Physiol. Meas."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"14","DOI":"10.2174\/157340312801215782","article-title":"On the Analysis of Fingertip Photoplethysmogram Signals","volume":"8","author":"Elgendi","year":"2012","journal-title":"Curr. Cardiol. Rev."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Couceiro, R., Carvalho, P., Paiva, R.P., Henriques, J., Antunes, M., Quintal, I., and Muehlsteff, J. (September, January 28). Multi-Gaussian fitting for the assessment of left ventricular ejection time from the Photoplethysmogram. Proceedings of the 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, CA, USA.","DOI":"10.1109\/EMBC.2012.6346831"},{"key":"ref_33","first-page":"5","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Lang."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"456","DOI":"10.3389\/fpsyg.2017.00456","article-title":"Repeated Measures Correlation","volume":"8","author":"Bakdash","year":"2017","journal-title":"Front. Psychol."},{"key":"ref_35","unstructured":"Lundberg, S.M., and Lee, S.-I. (2017). Advances in Neural Information Processing Systems, Curran Associates, Inc.. Available online: https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2017\/hash\/8a20a8621978632d76c43dfd28b67767-Abstract.html."},{"key":"ref_36","unstructured":"Solla, S., Leen, T., and M\u00fcller, K. (1999). Advances in Neural Information Processing Systems, MIT Press. Available online: https:\/\/proceedings.neurips.cc\/paper_files\/paper\/1999\/file\/7d12b66d3df6af8d429c1a357d8b9e1a-Paper.pdf."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Dai, H., Srikant, R., and Zhang, C. (2004). Advances in Knowledge Discovery and Data Mining, Springer.","DOI":"10.1007\/b97861"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1042\/cs1030371","article-title":"Determination of age-related increases in large artery stiffness by digital pulse contour analysis","volume":"103","author":"Millasseau","year":"2002","journal-title":"Clin. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"074001","DOI":"10.1088\/1361-6579\/ab9b67","article-title":"Age-related changes in pulse risetime measured by multi-site photoplethysmography","volume":"41","author":"Allen","year":"2020","journal-title":"Physiol. Meas."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, G., Howard, N., Abbott, D., Lim, K., Ward, R., and Elgendi, M. (2018). Can Photoplethysmography Replace Arterial Blood Pressure in the Assessment of Blood Pressure?. J. Clin. Med., 7.","DOI":"10.3390\/jcm7100316"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1687","DOI":"10.1093\/sleep\/33.12.1687","article-title":"Pulse Wave Amplitude Drops during Sleep are Reliable Surrogate Markers of Changes in Cortical Activity","volume":"33","author":"Delessert","year":"2010","journal-title":"Sleep"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1097\/ALN.0000000000000712","article-title":"Pulse Photoplethysmographic Analysis Estimates the Sympathetic Activity Directed to Heart and Vessels","volume":"123","author":"Colombo","year":"2015","journal-title":"Anesthesiology"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1111\/jsr.12593","article-title":"Arousal responses to respiratory events during sleep: The role of pulse wave amplitude","volume":"27","author":"Bosi","year":"2018","journal-title":"J. Sleep Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4159","DOI":"10.1093\/eurheartj\/ehy475","article-title":"Asleep blood pressure: Significant prognostic marker of vascular risk and therapeutic target for prevention","volume":"39","author":"Hermida","year":"2018","journal-title":"Eur. Heart J."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"20644","DOI":"10.1038\/s41598-021-99294-w","article-title":"Validation of the optical Aktiia bracelet in different body positions for the persistent monitoring of blood pressure","volume":"11","author":"Sola","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1093\/ajh\/hpac020","article-title":"Continuous Monitoring of Blood Pressure Using a Wrist-Worn Cuffless Device","volume":"35","author":"Sayer","year":"2022","journal-title":"Am. J. Hypertens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1161\/HYPERTENSIONAHA.118.10971","article-title":"Nocturnal Hypertension","volume":"71","author":"Kazuomi","year":"2018","journal-title":"Hypertension"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/18\/7931\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:52:12Z","timestamp":1760129532000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/18\/7931"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,16]]},"references-count":47,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2023,9]]}},"alternative-id":["s23187931"],"URL":"https:\/\/doi.org\/10.3390\/s23187931","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,16]]}}}