1932

Abstract

Cuffless blood pressure (BP) measurement has become a popular field due to clinical need and technological opportunity. However, no method has been broadly accepted hitherto. The objective of this review is to accelerate progress in the development and application of cuffless BP measurement methods. We begin by describing the principles of conventional BP measurement, outstanding hypertension/hypotension problems that could be addressed with cuffless methods, and recent technological advances, including smartphone proliferation and wearable sensing, that are driving the field. We then present all major cuffless methods under investigation, including their current evidence. Our presentation includes calibrated methods (i.e., pulse transit time, pulse wave analysis, and facial video processing) and uncalibrated methods (i.e., cuffless oscillometry, ultrasound, and volume control). The calibrated methods can offer convenience advantages, whereas the uncalibrated methods do not require periodic cuff device usage or demographic inputs. We conclude by summarizing the field and highlighting potentially useful future research directions.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-bioeng-110220-014644
2022-06-06
2024-12-13
Loading full text...

Full text loading...

/deliver/fulltext/bioeng/24/1/annurev-bioeng-110220-014644.html?itemId=/content/journals/10.1146/annurev-bioeng-110220-014644&mimeType=html&fmt=ahah

Literature Cited

  1. 1.
    GBD 2015 Mortal. Causes Death Collab 2016. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 388:1459–544
    [Google Scholar]
  2. 2.
    Sessler, Daniel I, Saugel B. 2019. Beyond “failure to rescue”: the time has come for continuous ward monitoring. Br. J. Anaesth. 122:3304–6
    [Google Scholar]
  3. 3.
    Maheshwari K, Nathanson BH, Munson SH, Khangulov V, Stevens M et al. 2018. The relationship between ICU hypotension and in-hospital mortality and morbidity in septic patients. Intensive Care Med. 44:6857–67
    [Google Scholar]
  4. 4.
    Zenati MS, Billiar TR, Townsend RN, Peitzman AB, Harbrecht BG. 2002. A brief episode of hypotension increases mortality in critically ill trauma patients. J. Trauma 53:2232–37
    [Google Scholar]
  5. 5.
    Tamura T 2020. Regulation and approval of continuous non-invasive blood-pressure monitoring devices. MEDICON 2019: XV Mediterranean Conference on Medical and Biological Engineering and Computing J Henriques, N Neves, P de Carvalho 1021–27 IFMBE Proc. 76. Cham, Switz.: Springer Nat .
    [Google Scholar]
  6. 6.
    Nachman D, Gepner Y, Goldstein N, Kabakov E, Ishay AB et al. 2020. Comparing blood pressure measurements between a photoplethysmography-based and a standard cuff-based manometry device. Sci. Rep. 10:16116
    [Google Scholar]
  7. 7.
    Vybornova A, Polychronopoulou E, Wurzner-Ghajarzadeh A, Fallet S, Sola J, Wuerzner G. 2021. Blood pressure from the optical Aktiia bracelet: a 1-month validation study using an extended ISO81060-2 protocol adapted for a cuffless wrist device. Blood Press. Monit 26:4305–11
    [Google Scholar]
  8. 8.
    Ahn JH, Song J, Choi I, Youn J, Cho JW. 2021. Validation of blood pressure measurement using a smartwatch in patients with Parkinson's disease. Front. Neurol. 12:650929
    [Google Scholar]
  9. 9.
    Nair D, Tan S-Y, Gan H-W, Lim S-F, Yan J et al. 2008. The use of ambulatory tonometric radial arterial wave capture to measure ambulatory blood pressure: the validation of a novel wrist-bound device in adults. J. Hum. Hypertens. 22:3220–22
    [Google Scholar]
  10. 10.
    Mukkamala R, Hahn JO, Inan OT, Mestha LK, Kim CS et al. 2015. Toward ubiquitous blood pressure monitoring via pulse transit time: theory and practice. IEEE Trans. Biomed. Eng. 62:81879–901
    [Google Scholar]
  11. 11.
    Sola J, Delgado-Gonzalo R, eds. 2019. The Handbook of Cuffless Blood Pressure Monitoring: A Practical Guide for Clinicians, Researchers, and Engineers Cham, Switz.: Springer Nat.
    [Google Scholar]
  12. 12.
    Ding XR, Zhao N, Yang GZ, Pettigrew RI, Lo B et al. 2016. Continuous blood pressure measurement from invasive to unobtrusive: celebration of 200th birth anniversary of Carl Ludwig. IEEE J. Biomed. Heal. Inf. 20:61455–65
    [Google Scholar]
  13. 13.
    Natarajan K, Yavarimanesh M, Wang W, Mukkamala R 2021. Camera-based blood pressure monitoring. Contactless Vital Signs Monitoring W Wang, X Wang 117–49 Oxford, UK: Elsevier
    [Google Scholar]
  14. 14.
    Mukkamala R, Hahn J-O, Chandrasekhar A 2021. Photoplethysmography in non-invasive blood pressure monitoring. Photoplethysmography: Technology, Signal Analysis, and Applications PA Kyriacou, J Allen Oxford, UK: Elsevier
    [Google Scholar]
  15. 15.
    Buxi D, Redouté JM, Yuce MR. 2015. A survey on signals and systems in ambulatory blood pressure monitoring using pulse transit time. Physiol. Meas. 36:3R1–26
    [Google Scholar]
  16. 16.
    Hosanee M, Chan G, Welykholowa K, Cooper R, Kyriacou PA et al. 2020. Cuffless single-site photoplethysmography for blood pressure monitoring. J. Clin. Med. 9:3723
    [Google Scholar]
  17. 17.
    Sharma M, Barbosa K, Ho V, Griggs D, Ghirmai T et al. 2017. Cuff-less and continuous blood pressure monitoring: a methodological review. Technologies 5:221
    [Google Scholar]
  18. 18.
    Elgendi M, Fletcher R, Liang Y, Howard N, Lovell NH et al. 2019. The use of photoplethysmography for assessing hypertension. NPJ Digit. Med. 2:60
    [Google Scholar]
  19. 19.
    Pandit JA, Lores E, Batlle D. 2020. Cuffless blood pressure monitoring: promises and challenges. Clin. J. Am. Soc. Nephrol. 15:101531–38
    [Google Scholar]
  20. 20.
    El-Hajj C, Kyriacou PA. 2020. A review of machine learning techniques in photoplethysmography for the non-invasive cuff-less measurement of blood pressure. Biomed. Signal Process. Control. 58:101870
    [Google Scholar]
  21. 21.
    O'Brien E, Fitzgerald D 1994. The history of blood pressure measurement. J. Hum. Hypertens. 8:73–84
    [Google Scholar]
  22. 22.
    Marino PL. 2007. The ICU Book Philadelphia: Lippincott Williams & Wilkins. , 3rd ed..
    [Google Scholar]
  23. 23.
    Wesseling KH, Jansen JRC, Settels JJ, Schreuder JJ. 1993. Computation of aortic flow from pressure in humans using a nonlinear, three-element model. J. Appl. Physiol. 74:52566–73
    [Google Scholar]
  24. 24.
    Mukkamala R, Xu D. 2010. Continuous and less invasive central hemodynamic monitoring by blood pressure waveform analysis. Am. J. Physiol. Heart Circ. Physiol. 299:3584–99
    [Google Scholar]
  25. 25.
    Perloff D, Grim C, Flack J, Frohlich ED. 1993. Human blood pressure determination by sphygmomanometry. Circulation 88:2460–70
    [Google Scholar]
  26. 26.
    Ng K-G, Small CF. 1994. Survey of automated noninvasive blood pressure monitors. J. Clin. Eng. 19:6452–75
    [Google Scholar]
  27. 27.
    Forouzanfar M, Dajani HR, Groza VZ, Bolic M, Rajan S, Batkin I. 2015. Oscillometric blood pressure estimation: past, present, and future. IEEE Rev. Biomed. Eng. 8:44–63
    [Google Scholar]
  28. 28.
    Drzewiecki G, Hood R, Apple H. 1994. Theory of the oscillometric maximum and the systolic and diastolic detection ratios. Ann. Biomed. Eng. 22:188–96
    [Google Scholar]
  29. 29.
    Ramsey M. 1979. Noninvasive automatic determination of mean arterial pressure. Med. Biol. Eng. Comput. 17:111–18
    [Google Scholar]
  30. 30.
    Geddes LA, Voelz M, Combs C, Reiner D, Babbs CE. 1982. Characterization of the oscillometric method for measuring indirect blood pressure. Ann. Biomed. Eng. 10:271–80
    [Google Scholar]
  31. 31.
    Penáz J. 1992. Criteria for set point estimation in the volume clamp method of blood pressure measurement. Physiol. Res. 41:15–10
    [Google Scholar]
  32. 32.
    Imholz BPM, Wieling W, Van Montfrans GA, Wesseling KH. 1998. Fifteen years experience with finger arterial pressure monitoring: assessment of the technology. Cardiovasc. Res. 38:3605–16
    [Google Scholar]
  33. 33.
    Fortin J, Marte W, Grüllenberger R, Hacker A, Habenbacher W et al. 2006. Continuous non-invasive blood pressure monitoring using concentrically interlocking control loops. Comput. Biol. Med. 36:9941–57
    [Google Scholar]
  34. 34.
    Matsumura K, Yamakoshi T, Rolfe P, Yamakoshi KI 2017. Advanced volume-compensation method for indirect finger arterial pressure determination: comparison with brachial sphygmomanometry. IEEE Trans. Biomed. Eng. 64:51131–37
    [Google Scholar]
  35. 35.
    Pressman GL, Newgard PM. 1963. A transducer for the continuous external measurement of arterial blood pressure. IEEE Trans. Bio-Med. Electron. 10:273–81
    [Google Scholar]
  36. 36.
    Eckerle JS 2006. Tonometry, arterial. Encyclopedia of Medical Devices and Instrumentation JG Webster 402–10 New York: Wiley
    [Google Scholar]
  37. 37.
    Drzewiecki GM, Melbin J, Noordergraaf A. 1983. Arterial tonometry: review and analysis. J. Biomech. 16:2141–52
    [Google Scholar]
  38. 38.
    Lewington S, Clarke R, Qizilbash N, Peto R, Collins R. 2002. Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. Lancet 360:93491903–13
    [Google Scholar]
  39. 39.
    Picone DS, Schultz MG, Otahal P, Aakhus S, Al-Jumaily AM et al. 2017. Accuracy of cuff-measured blood pressure: systematic reviews and meta-analyses. J. Am. Coll. Cardiol. 70:5572–86
    [Google Scholar]
  40. 40.
    Stergiou GS, Alpert BS, Mieke S, Wang J, O'Brien E. 2018. Validation protocols for blood pressure measuring devices in the 21st century. J. Clin. Hypertens. 20:1096–99
    [Google Scholar]
  41. 41.
    Stergiou GS, Alpert B, Mieke S, Asmar R, Atkins N et al. 2018. A universal standard for the validation of blood pressure measuring devices: Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization (AAMI/ESH/ISO) collaboration statement. Hypertension 71:3368–74
    [Google Scholar]
  42. 42.
    Nichols WW, O'Rourke MF, Vlachopoulos C 2011. McDonald's Blood Flow in Arteries: Theoretical, Experimental, and Clinical Principles London: Hodder Arnold
    [Google Scholar]
  43. 43.
    Karamanoglu M, O'Rourke MF, Avolio AP, Kelly RP. 1993. An analysis of the relationship between central aortic and peripheral upper limb pressure waves in man. Eur. Heart J. 14:2160–67
    [Google Scholar]
  44. 44.
    Gizdulich P, Prentza A, Wesseling KH. 1997. Models of brachial to finger pulse wave distortion and pressure decrement. Cardiovasc. Res. 33:3698–705
    [Google Scholar]
  45. 45.
    Giorgini P, Weder AB, Jackson EA, Brook RD 2014. A review of blood pressure measurement protocols among hypertension trials: implications for “evidence-based” clinical practice. J. Am. Soc. Hypertens. 8:9670–76
    [Google Scholar]
  46. 46.
    Chow CK, Teo KK, Rangarajan S, Islam S, Gupta R et al. 2013. Prevalence, awareness, treatment, and control of hypertension in rural and urban communities in high-, middle-, and low-income countries. JAMA 310:9959–68
    [Google Scholar]
  47. 47.
    Pickering TG, Phil D, Shimbo D, Haas D. 2006. Ambulatory blood-pressure monitoring. N. Engl. J. Med. 354:222368–74
    [Google Scholar]
  48. 48.
    Rosner B, Polk BF. 1983. Predictive values of routine blood pressure measurements in screening for hypertension. Am. J. Epidemiol. 117:4429–42
    [Google Scholar]
  49. 49.
    Taira D, Sentell T, Albright C, Lansidell D, Nakagawa K et al. 2017. Insights in public health: ambulatory blood pressure monitoring: underuse in clinical practice in Hawai'i. Hawai'i J. Med. Public Health 76:11314–17
    [Google Scholar]
  50. 50.
    Asayama K, Fujiwara T, Hoshide S, Ohkubo T, Kario K et al. 2019. Nocturnal blood pressure measured by home devices: evidence and perspective for clinical application. J. Hypertens. 37:5905–16
    [Google Scholar]
  51. 51.
    Agarwal R, Bills JE, Hecht TJW, Light RP. 2011. Role of home blood pressure monitoring in overcoming therapeutic inertia and improving hypertension control: a systematic review and meta-analysis. Hypertension 57:29–38
    [Google Scholar]
  52. 52.
    Zheng YL, Ding XR, Poon CCY, Lo BPL, Zhang H et al. 2014. Unobtrusive sensing and wearable devices for health informatics. IEEE Trans. Biomed. Eng. 61:51538–54
    [Google Scholar]
  53. 53.
    Reisner A, Shaltis PA, McCombie D, Asada HH. 2008. Utility of the photoplethysmogram in circulatory monitoring. Anesthesiology 108:5950–58
    [Google Scholar]
  54. 54.
    Allen J. 2007. Photoplethysmography and its application in clinical physiological measurement. Physiol. Meas. 28:3R1–39
    [Google Scholar]
  55. 55.
    Tamura T, Maeda Y, Sekine M, Yoshida M. 2014. Wearable photoplethysmographic sensors—past and present. Electron 3:2282–302
    [Google Scholar]
  56. 56.
    Gill RW. 1985. Measurement of blood flow by ultrasound: accuracy and sources of error. Ultrasound Med. Biol. 11:4625–41
    [Google Scholar]
  57. 57.
    Bera TK. 2014. Bioelectrical impedance methods for noninvasive health monitoring: a review. J. Med. Eng. 2014 381251
    [Google Scholar]
  58. 58.
    Patterson RP. 1989. Fundamentals of impedance cardiography. IEEE Eng. Med. Biol. Mag. 8:135–38
    [Google Scholar]
  59. 59.
    Inan OT, Migeotte PF, Park KS, Etemadi M, Tavakolian K et al. 2015. Ballistocardiography and seismocardiography: a review of recent advances. IEEE J. Biomed. Heal. Inf. 19:41414–27
    [Google Scholar]
  60. 60.
    Kim CS, Ober SL, McMurtry MS, Finegan BA, Inan OT et al. 2016. Ballistocardiogram: mechanism and potential for unobtrusive cardiovascular health monitoring. Sci. Rep. 6:31297
    [Google Scholar]
  61. 61.
    Jonathan E, Leahy M 2010. Investigating a smartphone imaging unit for photoplethysmography. Physiol. Meas. 31:11N79–83
    [Google Scholar]
  62. 62.
    Verkruysse W, Svaasand LO, Nelson JS. 2008. Remote plethysmographic imaging using ambient light. Opt. Express 16:2621434
    [Google Scholar]
  63. 63.
    Balakrishnan G, Durand F, Guttag J. 2013. Detecting pulse from head motions in video. 2013 IEEE Conference on Computer Vision and Pattern Recognition3430–37 Los Alamitos, CA: IEEE Comput. Soc.
    [Google Scholar]
  64. 64.
    Landreani F, Caiani EG. 2017. Smartphone accelerometers for the detection of heart rate. Expert Rev. Med. Devices 14:12935–48
    [Google Scholar]
  65. 65.
    Dunn J, Runge R, Snyder M. 2018. Wearables and the medical revolution. Pers. Med. 15:5429–48
    [Google Scholar]
  66. 66.
    Chung HU, Rwei AY, Hourlier-Fargette A, Xu S, Lee KH et al. 2020. Skin-interfaced biosensors for advanced wireless physiological monitoring in neonatal and pediatric intensive-care units. Nat. Med. 26:3418–29
    [Google Scholar]
  67. 67.
    Schwartz G, Tee BCK, Mei J, Appleton AL, Kim DH et al. 2013. Flexible polymer transistors with high pressure sensitivity for application in electronic skin and health monitoring. Nat. Commun. 4:1859
    [Google Scholar]
  68. 68.
    Wang C, Li X, Hu H, Zhang L, Huang Z et al. 2018. Monitoring of the central blood pressure waveform via a conformal ultrasonic device. Nat. Biomed. Eng. 2:9687–95
    [Google Scholar]
  69. 69.
    Ha T, Tran J, Liu S, Jang H, Jeong H et al. 2019. A chest-laminated ultrathin and stretchable e-tattoo for the measurement of electrocardiogram, seismocardiogram, and cardiac time intervals. Adv. Sci. 6:1900290
    [Google Scholar]
  70. 70.
    Bramwell JC, Hill AV. 1922. The velocity of pulse wave in man. Proc. R. Soc. B 93:652298–306
    [Google Scholar]
  71. 71.
    Yavarimanesh M, Chandrasekhar A, Hahn J-O, Mukkamala R. 2019. Commentary: relation between blood pressure and pulse wave velocity for human arteries. Front. Physiol. 10:1170
    [Google Scholar]
  72. 72.
    Mukkamala R, Hahn JO. 2018. Toward ubiquitous blood pressure monitoring via pulse transit time: predictions on maximum calibration period and acceptable error limits. IEEE Trans. Biomed. Eng. 65:61410–20
    [Google Scholar]
  73. 73.
    Gao M, Olivier NB, Mukkamala R. 2016. Comparison of noninvasive pulse transit time estimates as markers of blood pressure using invasive pulse transit time measurements as a reference. Physiol. Rep. 4:10e12768
    [Google Scholar]
  74. 74.
    Chiu YC, Arand PW, Shroff SG, Feldman T, Carroll JD. 1991. Determination of pulse wave velocities with computerized algorithms. Am. Heart J. 121:51460–70
    [Google Scholar]
  75. 75.
    Chandrasekhar A, Yavarimanesh M, Natarajan K, Hahn JO, Mukkamala R. 2020. PPG sensor contact pressure should be taken into account for cuff-less blood pressure measurement. IEEE Trans. Biomed. Eng. 67:113134–40
    [Google Scholar]
  76. 76.
    Mukkamala R, Hahn JO 2019. Initialization of pulse transit time-based blood pressure monitors. The Handbook of Cuffless Blood Pressure Monitoring: A Practical Guide for Clinicians, Researchers, and Engineers J Sola, R Delgado-Gonzolo 163–90 Cham, Switz.: Springer Nat.
    [Google Scholar]
  77. 77.
    Gavish B, Ben-Dov IZ, Bursztyn M 2008. Linear relationship between systolic and diastolic blood pressure monitored over 24 h: assessment and correlates. J. Hypertens. 26:2199–209
    [Google Scholar]
  78. 78.
    Master AM, Lasser RP. 1965. The relationship of pulse pressure and diastolic pressure to systolic pressure in healthy subjects, 20–94 years of age. Am. Heart J. 70:2163–71
    [Google Scholar]
  79. 79.
    McCombie DB, Shaltis PA, Reisner AT, Asada HH. 2007. Adaptive hydrostatic blood pressure calibration: development of a wearable, autonomous pulse wave velocity blood pressure monitor. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society370–73 Piscataway, NJ: IEEE
    [Google Scholar]
  80. 80.
    Butlin M, Shirbani F, Barin E, Tan I, Spronck B, Avolio AP. 2018. Cuffless estimation of blood pressure: importance of variability in blood pressure dependence of arterial stiffness across individuals and measurement sites. IEEE Trans. Biomed. Eng. 65:112377–83
    [Google Scholar]
  81. 81.
    Chen Y, Wen C, Tao G, Bi M, Li G. 2009. Continuous and noninvasive blood pressure measurement: a novel modeling methodology of the relationship between blood pressure and pulse wave velocity. Ann. Biomed. Eng. 37:112222–33
    [Google Scholar]
  82. 82.
    Payne RA, Symeonides CN, Webb DJ, J Maxwell SR 2006. Pulse transit time measured from the ECG: an unreliable marker of beat-to-beat blood pressure. J. Appl. Physiol. 100:136–41
    [Google Scholar]
  83. 83.
    Liang Y, Abbott D, Howard N, Lim K, Ward R, Elgendi M. 2019. How effective is pulse arrival time for evaluating blood pressure? Challenges and recommendations from a study using the MIMIC database. J. Clin. Med. 8:3337
    [Google Scholar]
  84. 84.
    Yoon YZ, Kang JM, Kwon Y, Park S, Noh S et al. 2018. Cuff-less blood pressure estimation using pulse waveform analysis and pulse arrival time. IEEE J. Biomed. Heal. Inf. 22:41068–74
    [Google Scholar]
  85. 85.
    Sharwood-Smith G, Bruce J, Drummond G 2006. Assessment of pulse transit time to indicate cardiovascular changes during obstetric spinal anaesthesia. Br. J. Anaesth. 96:1100–5
    [Google Scholar]
  86. 86.
    Lee J, Yang S, Lee S, Kim HC 2019. Analysis of pulse arrival time as an indicator of blood pressure in a large surgical biosignal database: recommendations for developing ubiquitous blood pressure monitoring methods. J. Clin. Med. 8:111773
    [Google Scholar]
  87. 87.
    Kim CS, Carek AM, Inan OT, Mukkamala R, Hahn JO. 2018. Ballistocardiogram-based approach to cuffless blood pressure monitoring: proof of concept and potential challenges. IEEE Trans. Biomed. Eng. 65:112384–91
    [Google Scholar]
  88. 88.
    Block RC, Yavarimanesh M, Natarajan K, Carek A, Mousavi A et al. 2020. Conventional pulse transit times as markers of blood pressure changes in humans. Sci. Rep. 10:16373
    [Google Scholar]
  89. 89.
    Di Rienzo M, Avolio A, Rizzo G, Isilay Zeybek ZM, Cucugliato L 2022. Multi-site pulse transit times, beat-to-beat blood pressure, and isovolumic contraction time at rest and under stressors. IEEE J. Biomed. Health Inform. 26:2561–71
    [Google Scholar]
  90. 90.
    Flügge W. 1975. Viscoelasticity Heidelberg, Ger: Springer-Verlag
    [Google Scholar]
  91. 91.
    Natarajan K, Block RC, Yavarimanesh M, Chandrasekhar A, Mestha LK et al. 2022. Photoplethysmography fast upstroke time intervals can be useful features for cuff-less measurement of blood pressure changes in humans. IEEE Trans. Biomed. Eng 69:153–62
    [Google Scholar]
  92. 92.
    Fortin J, Rogge DE, Fellner C, Flotzinger D, Grond J et al. 2021. A novel art of continuous noninvasive blood pressure measurement. Nat. Commun. 12:1387
    [Google Scholar]
  93. 93.
    Elgendi M. 2012. On the analysis of fingertip photoplethysmogram signals. Curr. Cardiol. Rev. 8:114–25
    [Google Scholar]
  94. 94.
    Addison PS. 2016. Slope transit time (STT): a pulse transit time proxy requiring only a single signal fiducial point. IEEE Trans. Biomed. Eng. 63:112441–44
    [Google Scholar]
  95. 95.
    Baruch MC, Warburton DER, Bredin SSD, Cote A, Gerdt DW, Adkins CM. 2011. Pulse decomposition analysis of the digital arterial pulse during hemorrhage simulation. Nonlinear Biomed. Phys. 5:1
    [Google Scholar]
  96. 96.
    Mukkamala R, Yavarimanesh M, Natarajan K, Hahn J-O, Kyriakoulis KG et al. 2021. Evaluation of the accuracy of cuffless blood pressure measurement devices: challenges and proposals. Hypertension 78:1161–67
    [Google Scholar]
  97. 97.
    Xing X, Ma Z, Zhang M, Zhou Y, Dong W, Song M 2019. An unobtrusive and calibration-free blood pressure estimation method using photoplethysmography and biometrics. Sci. Rep. 9:8611
    [Google Scholar]
  98. 98.
    Ruiz-Rodríguez JC, Ruiz-Sanmartín A, Ribas V, Caballero J, García-Roche A et al. 2013. Innovative continuous non-invasive cuffless blood pressure monitoring based on photoplethysmography technology. Intensive Care Med 39:91618–25
    [Google Scholar]
  99. 99.
    Xing X, Ma Z, Zhang M, Gao X, Li Y et al. 2020. Robust blood pressure estimation from finger photoplethysmography using age-dependent linear models. Physiol. Meas. 41:025007
    [Google Scholar]
  100. 100.
    Radha M, De Groot K, Rajani N, Wong CCP, Kobold N et al. 2019. Estimating blood pressure trends and the nocturnal dip from photoplethysmography. Physiol. Meas. 40:025006
    [Google Scholar]
  101. 101.
    Mukkamala R. 2019. Blood pressure with a click of a camera?. Circ. Cardiovasc. Imaging 12:8e009531
    [Google Scholar]
  102. 102.
    Viola P, Jones M. 2001. Rapid object detection using a boosted cascade of simple features. 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition: CVPR 2001I–511–18 Los Alamitos, CA: IEEE Comput. Soc.
    [Google Scholar]
  103. 103.
    Wang W, Den Brinker AC, Stuijk S, De Haan G 2017. Algorithmic principles of remote PPG. IEEE Trans. Biomed. Eng. 64:71479–91
    [Google Scholar]
  104. 104.
    Bouguet J-Y. 2001. Pyramidal implementation of the affine Lucas Kanade feature tracker description of the algorithm Rep., Intel. Corp. Santa Clara, CA:
    [Google Scholar]
  105. 105.
    Jeong IC, Finkelstein J. 2016. Introducing contactless blood pressure assessment using a high speed video camera. J. Med. Syst. 40:477
    [Google Scholar]
  106. 106.
    Luo H, Yang D, Barszczyk A, Vempala N, Wei J et al. 2019. Smartphone-based blood pressure measurement using transdermal optical imaging technology. Circ. Cardiovasc. Imaging 12:8e008857
    [Google Scholar]
  107. 107.
    Poplin R, Varadarajan AV, Blumer K, Liu Y, McConnell MV et al. 2018. Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nat. Biomed. Eng. 2:3158–64
    [Google Scholar]
  108. 108.
    Shaltis PA, Reisner AT, Asada HH. 2008. Cuffless blood pressure monitoring using hydrostatic pressure changes. IEEE Trans. Biomed. Eng. 55:61775–77
    [Google Scholar]
  109. 109.
    Chandrasekhar A, Kim CS, Naji M, Natarajan K, Hahn JO, Mukkamala R. 2018. Smartphone-based blood pressure monitoring via the oscillometric finger-pressing method. Sci. Transl. Med. 10:431 https://doi.org/10.1126/scitranslmed.aap8674
    [Crossref] [Google Scholar]
  110. 110.
    Chandrasekhar A, Natarajan K, Yavarimanesh M, Mukkamala R. 2018. An iPhone application for blood pressure monitoring via the oscillometric finger pressing method. Sci. Rep. 8:13136
    [Google Scholar]
  111. 111.
    Chandrasekhar A, Yavarimanesh M, Hahn JO, Sung SH, Chen CH et al. 2019. Formulas to explain popular oscillometric blood pressure estimation algorithms. Front. Physiol. 10:1415
    [Google Scholar]
  112. 112.
    Liu J, Cheng HM, Chen CH, Sung SH, Hahn JO, Mukkamala R. 2017. Patient-specific oscillometric blood pressure measurement: validation for accuracy and repeatability. IEEE J. Transl. Eng. Heal. Med. 5:1900110
    [Google Scholar]
  113. 113.
    Babbs CF. 2012. Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model. Biomed. Eng. Online 11:56
    [Google Scholar]
  114. 114.
    Panula T, Koivisto T, Pänkäälä M, Niiranen T, Kantola I, Kaisti M. 2020. An instrument for measuring blood pressure and assessing cardiovascular health from the fingertip. Biosens. Bioelectron. 167:112483
    [Google Scholar]
  115. 115.
    Kario K, Shimbo D, Tomitani N, Kanegae H, Schwartz JE, Williams B. 2020. The first study comparing a wearable watch-type blood pressure monitor with a conventional ambulatory blood pressure monitor on in-office and out-of-office settings. J. Clin. Hypertens. 22:2135–41
    [Google Scholar]
  116. 116.
    Beulen BWAMM, Bijnens N, Koutsouridis GG, Brands PJ, Rutten MCM, van de Vosse FN. 2011. Toward noninvasive blood pressure assessment in arteries by using ultrasound. Ultrasound Med. Biol. 37:5788–97
    [Google Scholar]
  117. 117.
    Gao M, Cheng HM, Sung SH, Chen CH, Olivier NB, Mukkamala R. 2017. Estimation of pulse transit time as a function of blood pressure using a nonlinear arterial tube-load model. IEEE Trans. Biomed. Eng. 64:71524–34
    [Google Scholar]
  118. 118.
    Seo J, Pietrangelo SJ, Lee HS, Sodini CG. 2015. Noninvasive arterial blood pressure waveform monitoring using two-element ultrasound system. IEEE Trans. Ultrason. Ferroelectr. Freq. Control. 62:4776–84
    [Google Scholar]
  119. 119.
    Vappou J, Luo J, Okajima K, Di Tullio M, Konofagou EE. 2011. Non-invasive measurement of local pulse pressure by pulse wave-based ultrasound manometry (PWUM). Physiol. Meas. 32:101653–62
    [Google Scholar]
  120. 120.
    Joseph J, Nabeel PM, Shah MI, Sivaprakasam M. 2018. Arterial compliance probe for cuffless evaluation of carotid pulse pressure. PLOS ONE 13:8e0202480
    [Google Scholar]
  121. 121.
    Vlachopoulos C, Aznaouridis K, O'Rourke MF, Safar ME, Baou K, Stefanadis C 2010. Prediction of cardiovascular events and all-cause mortality with central haemodynamics: a systematic review and meta-analysis. Eur. Heart J. 31:151865–71
    [Google Scholar]
  122. 122.
    Seo J, Lee HS, Sodini CG. 2021. Non-invasive evaluation of a carotid arterial pressure waveform using motion-tolerant ultrasound measurements during the Valsalva maneuver. IEEE J. Biomed. Heal. Inf. 25:1163–74
    [Google Scholar]
  123. 123.
    Nabeel PM, Joseph J, Karthik S, Sivaprakasam M, Chenniappan M. 2018. Bi-modal arterial compliance probe for calibration-free cuffless blood pressure estimation. IEEE Trans. Biomed. Eng. 65:112392–404
    [Google Scholar]
  124. 124.
    Liu J, Hahn JO, Mukkamala R. 2013. An initial step towards improving the accuracy of the oscillometric blood pressure measurement. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)4082–85 Piscataway, NJ: IEEE
    [Google Scholar]
  125. 125.
    Zakrzewski AM, Huang AY, Zubajlo R, Anthony BW. 2018. Real-time blood pressure estimation from force-measured ultrasound. IEEE Trans. Biomed. Eng. 65:112405–16
    [Google Scholar]
  126. 126.
    Johnson AEW, Pollard TJ, Shen L, Lehman LWH, Feng M et al. 2016. MIMIC-III, a freely accessible critical care database. Sci. Data 3:160035
    [Google Scholar]
  127. 127.
    van Helmond N, Martin SS, Plante TB. 2020. Is cuffless blood pressure measurement already here?. J. Hypertens. 38:4774–75
    [Google Scholar]
  128. 128.
    IEEE 2014. IEEE Standard for Wearable Cuffless Blood Pressure Measuring Devices New York: IEEE38 pp.
    [Google Scholar]
  129. 129.
    IEEE 2019. IEEE Standard for Wearable, Cuffless Blood Pressure Measuring Devices - Amendment 1 New York: IEEE 35 pp.
    [Google Scholar]
/content/journals/10.1146/annurev-bioeng-110220-014644
Loading
/content/journals/10.1146/annurev-bioeng-110220-014644
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error