{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,5]],"date-time":"2025-04-05T07:24:27Z","timestamp":1743837867529},"reference-count":54,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2020,1,27]],"date-time":"2020-01-27T00:00:00Z","timestamp":1580083200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1016\/j.bspc.2020.101870","type":"journal-article","created":{"date-parts":[[2020,2,11]],"date-time":"2020-02-11T21:07:04Z","timestamp":1581455224000},"page":"101870","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":208,"special_numbering":"C","title":["A review of machine learning techniques in photoplethysmography for the non-invasive cuff-less measurement of blood pressure"],"prefix":"10.1016","volume":"58","author":[{"given":"C.","family":"El-Hajj","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-2868-485X","authenticated-orcid":false,"given":"P.A.","family":"Kyriacou","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"9859","key":"10.1016\/j.bspc.2020.101870_bib0005","doi-asserted-by":"crossref","first-page":"2224","DOI":"10.1016\/S0140-6736(12)61766-8","article-title":"A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990\u20132010: a systematic analysis for the Global Burden of Disease Study 2010","volume":"380","author":"Lim","year":"2012","journal-title":"Lancet"},{"issue":"8","key":"10.1016\/j.bspc.2020.101870_bib0010","doi-asserted-by":"crossref","first-page":"3007","DOI":"10.1364\/BOE.7.003007","article-title":"Optical blood pressure estimation with photoplethysmography and FFT-based neural networks","volume":"7","author":"Xing","year":"2016","journal-title":"Biomed. Opt. Express"},{"key":"10.1016\/j.bspc.2020.101870_bib0015","series-title":"A Global Brief on Hypertension: Silent Killer, Global Public Health Crisis: World Health Day 2013 (No. WHO\/DCO\/WHD\/2013.2)","author":"World Health Organization","year":"2013"},{"key":"10.1016\/j.bspc.2020.101870_bib0020","series-title":"Dynamics of Mercury Pollution on Regional and Global Scales: Atmospheric Processes and Human Exposures Around the World","year":"2005"},{"issue":"2","key":"10.1016\/j.bspc.2020.101870_bib0025","first-page":"108","article-title":"Comparison between direct and invasive arterial blood pressure measurement in non-hypotensive critically ill patients","volume":"17","author":"Park","year":"2005","journal-title":"Rev. Bras. Ter. Intens."},{"issue":"5","key":"10.1016\/j.bspc.2020.101870_bib0030","doi-asserted-by":"crossref","first-page":"2460","DOI":"10.1161\/01.CIR.88.5.2460","article-title":"Human blood pressure determination by sphygmomanometry","volume":"88","author":"Perloff","year":"1993","journal-title":"Circulation"},{"issue":"1","key":"10.1016\/j.bspc.2020.101870_bib0035","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1007\/BF02368225","article-title":"Theory of the oscillometric maximum and the systolic and diastolic detection ratios","volume":"22","author":"Drzewiecki","year":"1994","journal-title":"Ann. Biomed. Eng."},{"issue":"1","key":"10.1016\/j.bspc.2020.101870_bib0040","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1111\/j.1469-8986.1981.tb01545.x","article-title":"Pulse transit time as an indicator of arterial blood pressure","volume":"18","author":"Geddes","year":"1981","journal-title":"Psychophysiology"},{"issue":"1","key":"10.1016\/j.bspc.2020.101870_bib0045","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.compeleceng.2012.09.005","article-title":"Noninvasive cuffless blood pressure estimation using pulse transit time and Hilbert\u2013Huang transform","volume":"39","author":"Choi","year":"2013","journal-title":"Comput. Electr. Eng."},{"issue":"8","key":"10.1016\/j.bspc.2020.101870_bib0050","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."},{"issue":"2","key":"10.1016\/j.bspc.2020.101870_bib0055","doi-asserted-by":"crossref","first-page":"21","DOI":"10.3390\/technologies5020021","article-title":"Cuff-less and continuous blood pressure monitoring: a methodological review","volume":"5","author":"Sharma","year":"2017","journal-title":"Technologies"},{"key":"10.1016\/j.bspc.2020.101870_bib0060","series-title":"2006 International Conference of the IEEE Engineering in Medicine and Biology Society","first-page":"3521","article-title":"Adaptive blood pressure estimation from wearable PPG sensors using peripheral artery pulse wave velocity measurements and multi-channel blind identification of local arterial dynamics","author":"McCombie","year":"2006"},{"issue":"1","key":"10.1016\/j.bspc.2020.101870_bib0065","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."},{"issue":"3","key":"10.1016\/j.bspc.2020.101870_bib0070","doi-asserted-by":"crossref","first-page":"R1","DOI":"10.1088\/0967-3334\/28\/3\/R01","article-title":"Photoplethysmography and its application in clinical physiological measurement","volume":"28","author":"Allen","year":"2007","journal-title":"Physiol. Meas."},{"issue":"10","key":"10.1016\/j.bspc.2020.101870_bib0075","doi-asserted-by":"crossref","first-page":"e12768","DOI":"10.14814\/phy2.12768","article-title":"Comparison of noninvasive pulse transit time estimates as markers of blood pressure using invasive pulse transit time measurements as a reference","volume":"4","author":"Gao","year":"2016","journal-title":"Physiol. Rep."},{"issue":"10","key":"10.1016\/j.bspc.2020.101870_bib0080","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1038\/sj.jhh.1001478","article-title":"Age-related changes in peripheral pulse timing characteristics at the ears, fingers and toes","volume":"16","author":"Allen","year":"2002","journal-title":"J. Hum. Hypertens."},{"issue":"11","key":"10.1016\/j.bspc.2020.101870_bib0085","doi-asserted-by":"crossref","first-page":"2222","DOI":"10.1007\/s10439-009-9759-1","article-title":"Continuous and noninvasive blood pressure measurement: a novel modeling methodology of the relationship between blood pressure and pulse wave velocity","volume":"37","author":"Chen","year":"2009","journal-title":"Ann. Biomed. Eng."},{"issue":"1","key":"10.1016\/j.bspc.2020.101870_bib0090","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1088\/0967-3334\/23\/1\/308","article-title":"The difference in pulse transit time to the toe and finger measured by photoplethysmography","volume":"23","author":"Nitzan","year":"2001","journal-title":"Physiol. Meas."},{"issue":"4","key":"10.1016\/j.bspc.2020.101870_bib0095","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1007\/s10439-011-0467-2","article-title":"Continuous and noninvasive measurement of systolic and diastolic blood pressure by one mathematical model with the same model parameters and two separate pulse wave velocities","volume":"40","author":"Chen","year":"2012","journal-title":"Ann. Biomed. Eng."},{"issue":"5","key":"10.1016\/j.bspc.2020.101870_bib0100","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1007\/BF02345755","article-title":"Continuous estimation of systolic blood pressure using the pulse arrival time and intermittent calibration","volume":"38","author":"Chen","year":"2000","journal-title":"Med. Biol. Eng. Comput."},{"issue":"9","key":"10.1016\/j.bspc.2020.101870_bib0105","doi-asserted-by":"crossref","first-page":"2443","DOI":"10.1109\/TIM.2015.2412000","article-title":"Model-based mean arterial pressure estimation using simultaneous electrocardiogram and oscillometric blood pressure measurements","volume":"64","author":"Forouzanfar","year":"2015","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.bspc.2020.101870_bib0110","series-title":"2005 IEEE Engineering in Medicine and Biology 27th Annual Conference","first-page":"996","article-title":"A correlation study on the variabilities in pulse transit time, blood pressure, and heart rate recorded simultaneously from healthy subjects","author":"Ma","year":"2006"},{"issue":"11","key":"10.1016\/j.bspc.2020.101870_bib0115","doi-asserted-by":"crossref","first-page":"2657","DOI":"10.1109\/TBME.2015.2440291","article-title":"Ballistocardiogram as proximal timing reference for pulse transit time measurement: potential for cuffless blood pressure monitoring","volume":"62","author":"Kim","year":"2015","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"10.1016\/j.bspc.2020.101870_bib0120","article-title":"Pulse arrival time is not an adequate surrogate for pulse transit time as a marker of blood pressure","author":"Zhang","year":"2011","journal-title":"Am. J. Physiol.-Heart Circul. Physiol."},{"key":"10.1016\/j.bspc.2020.101870_bib0125","volume":"vol. 1","author":"Noordergraaf","year":"2012"},{"issue":"3","key":"10.1016\/j.bspc.2020.101870_bib0130","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1007\/s12265-012-9349-8","article-title":"Elastin in large artery stiffness and hypertension","volume":"5","author":"Wagenseil","year":"2012","journal-title":"J. Cardiovasc. Transl. Res."},{"key":"10.1016\/j.bspc.2020.101870_bib0135","doi-asserted-by":"crossref","first-page":"3153","DOI":"10.1109\/IEMBS.2003.1280811","article-title":"Continuous and noninvasive estimation of arterial blood pressure using a photoplethysmographic approach, September, IEEE","volume":"Vol. 4","author":"Teng","year":"2003","journal-title":"Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No. 03CH37439)"},{"key":"10.1016\/j.bspc.2020.101870_bib0140","series-title":"4th Kuala Lumpur International Conference on Biomedical Engineering 2008","first-page":"591","article-title":"Measuring blood pressure using a photoplethysmography approach","author":"Hassan","year":"2008"},{"issue":"1","key":"10.1016\/j.bspc.2020.101870_bib0145","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1007\/s10558-009-9070-7","article-title":"An evaluation of the cuffless blood pressure estimation based on pulse transit time technique: a half year study on normotensive subjects","volume":"9","author":"Wong","year":"2009","journal-title":"Cardiovasc. Eng."},{"key":"10.1016\/j.bspc.2020.101870_bib0150","series-title":"2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society","first-page":"6765","article-title":"Cuffless blood pressure estimation by error-correcting output coding method based on an aggregation of adaboost with a photoplethysmograph sensor","author":"Suzuki","year":"2009"},{"issue":"9","key":"10.1016\/j.bspc.2020.101870_bib0155","doi-asserted-by":"crossref","first-page":"1618","DOI":"10.1007\/s00134-013-2964-2","article-title":"Innovative continuous non-invasive cuffless blood pressure monitoring based on photoplethysmography technology","volume":"39","author":"Ruiz-Rodr\u00edguez","year":"2013","journal-title":"Intens. Care Med."},{"key":"10.1016\/j.bspc.2020.101870_bib0160","series-title":"Instrumentation and Measurement Technology Conference (I2MTC), 2013 IEEE International","first-page":"280","article-title":"A neural network-based method for continuous blood pressure estimation from a PPG signal","author":"Kurylyak","year":"2013"},{"issue":"23","key":"10.1016\/j.bspc.2020.101870_bib0165","doi-asserted-by":"crossref","first-page":"e215","DOI":"10.1161\/01.CIR.101.23.e215","article-title":"PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals","volume":"101","author":"Goldberger","year":"2000","journal-title":"Circulation"},{"issue":"2","key":"10.1016\/j.bspc.2020.101870_bib0170","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1109\/TII.2013.2288498","article-title":"Feature selection method for estimating systolic blood pressure using the taguchi method","volume":"10","author":"Suzuki","year":"2014","journal-title":"IEEE Trans. Ind. Inform."},{"key":"10.1016\/j.bspc.2020.101870_bib0175","series-title":"2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","first-page":"4567","article-title":"Estimating blood pressure using Windkessel model on photoplethysmogram","author":"Choudhury","year":"2014"},{"key":"10.1016\/j.bspc.2020.101870_bib0180","series-title":"2015 5th International Conference on Information Science and Technology (ICIST)","first-page":"117","article-title":"Cuffless and continuous blood pressure estimation based on multiple regression analysis","author":"Shen","year":"2015"},{"key":"10.1016\/j.bspc.2020.101870_bib0185","series-title":"2015 IEEE International Symposium on Circuits and Systems (ISCAS)","first-page":"1006","article-title":"Cuff-less high-accuracy calibration-free blood pressure estimation using pulse transit time","author":"Kachuee","year":"2015"},{"key":"10.1016\/j.bspc.2020.101870_bib0190","series-title":"2016 IEEE International Conference on Communications (ICC)","first-page":"1","article-title":"Blood pressure estimation from photoplethysmogram using latent parameters","author":"Datta","year":"2016"},{"key":"10.1016\/j.bspc.2020.101870_bib0195","series-title":"2016 IEEE International Conference on Smart Computing (SMARTCOMP)","first-page":"1","article-title":"Building continuous arterial blood pressure prediction models using recurrent networks","author":"Sideris","year":"2016"},{"key":"10.1016\/j.bspc.2020.101870_bib0200","series-title":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","first-page":"6385","article-title":"A feature exploration methodology for learning based cuffless blood pressure measurement using photoplethysmography","author":"Duan","year":"2016"},{"key":"10.1016\/j.bspc.2020.101870_bib0205","series-title":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","first-page":"607","article-title":"Cuff-less PPG based continuous blood pressure monitoring\u2014A smartphone based approach","author":"Gaurav","year":"2016"},{"key":"10.1016\/j.bspc.2020.101870_bib0210","series-title":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","first-page":"766","article-title":"Data-driven estimation of blood pressure using photoplethysmographic signals","author":"Gao","year":"2016"},{"issue":"3","key":"10.1016\/j.bspc.2020.101870_bib0215","doi-asserted-by":"crossref","first-page":"202","DOI":"10.7763\/IJCTE.2017.V9.1138","article-title":"Cuffless blood pressure estimation based on photoplethysmography signal and its second derivative","volume":"9","author":"Liu","year":"2017","journal-title":"Int. J. Comput. Theory Eng."},{"issue":"4","key":"10.1016\/j.bspc.2020.101870_bib0220","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1109\/TBME.2016.2580904","article-title":"Cuffless blood pressure estimation algorithms for continuous health-care monitoring","volume":"64","author":"Kachuee","year":"2017","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"6","key":"10.1016\/j.bspc.2020.101870_bib0225","doi-asserted-by":"crossref","first-page":"1730","DOI":"10.1109\/JBHI.2017.2691715","article-title":"A novel continuous blood pressure estimation approach based on data mining techniques","volume":"21","author":"Miao","year":"2017","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"10.1016\/j.bspc.2020.101870_bib0230","doi-asserted-by":"crossref","DOI":"10.1155\/2018\/7804243","article-title":"A novel neural network model for blood pressure estimation using photoplethesmography without electrocardiogram","volume":"2018","author":"Wang","year":"2018","journal-title":"J. Healthc. Eng."},{"key":"10.1016\/j.bspc.2020.101870_bib0235","series-title":"2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","first-page":"2857","article-title":"Features extraction for cuffless blood pressure estimation by autoencoder from photoplethysmography","author":"Shimazaki","year":"2018"},{"key":"10.1016\/j.bspc.2020.101870_bib0240","doi-asserted-by":"crossref","DOI":"10.1155\/2018\/1548647","article-title":"Blood pressure estimation using photoplethysmography only: comparison between different machine learning approaches","author":"Khalid","year":"2018","journal-title":"J. Healthc. Eng."},{"key":"10.1016\/j.bspc.2020.101870_bib0245","series-title":"2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","first-page":"5002","article-title":"InstaBP: cuff-less blood pressure monitoring on smartphone using single PPG sensor","author":"Dey","year":"2018"},{"key":"10.1016\/j.bspc.2020.101870_bib0250","series-title":"Cuffless Blood Pressure Estimation from Electrocardiogram and Photoplethysmogram Using Waveform Based ANN-LSTM Network","author":"Tanveer","year":"2018"},{"key":"10.1016\/j.bspc.2020.101870_bib0255","series-title":"2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI)","first-page":"323","article-title":"Long-term blood pressure prediction with deep recurrent neural networks","author":"Su","year":"2018"},{"issue":"2","key":"10.1016\/j.bspc.2020.101870_bib0260","doi-asserted-by":"crossref","first-page":"304","DOI":"10.3390\/app9020304","article-title":"PPG-based systolic blood pressure estimation method using PLS and level-crossing feature","volume":"9","author":"Fujita","year":"2019","journal-title":"Appl. Sci."},{"issue":"11","key":"10.1016\/j.bspc.2020.101870_bib0265","doi-asserted-by":"crossref","first-page":"2585","DOI":"10.3390\/s19112585","article-title":"A non-invasive continuous blood pressure estimation approach based on machine learning","volume":"19","author":"Chen","year":"2019","journal-title":"Sensors"},{"issue":"1","key":"10.1016\/j.bspc.2020.101870_bib0270","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1159\/000493478","article-title":"Blood pressure assessment with differential pulse transit time and deep learning: a proof of concept","volume":"5","author":"Ripoll","year":"2019","journal-title":"Kidney Dis."}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809420300264?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809420300264?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2021,2,9]],"date-time":"2021-02-09T20:33:21Z","timestamp":1612902801000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1746809420300264"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4]]},"references-count":54,"alternative-id":["S1746809420300264"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2020.101870","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2020,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A review of machine learning techniques in photoplethysmography for the non-invasive cuff-less measurement of blood pressure","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2020.101870","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2020 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"101870"}}