REFERENCES

1. Schwamm LH, Chumbler N, Brown E, et al. American Heart Association Advocacy Coordinating Committee. Recommendations for the implementation of telehealth in cardiovascular and stroke care: a policy statement from the american heart association. Circulation 2017;135:e24-44.

2. Omboni S, Padwal RS, Alessa T, et al. The worldwide impact of telemedicine during COVID-19: current evidence and recommendations for the future. Connect Health 2022;1:7-35.

3. Sharman JE, Tan I, Stergiou GS, et al. Automated “oscillometric” blood pressure measuring devices: how they work and what they measure. J Hum Hypertens 2023;37:93-100.

4. Mukkamala R, Stergiou GS, Avolio AP. Cuffless blood pressure measurement. Annu Rev Biomed Eng 2022;24:203-30.

5. Mukkamala R, Shroff SG, Landry C, Kyriakoulis KG, Avolio AP, Stergiou GS. The microsoft research aurora project: important findings on cuffless blood pressure measurement. Hypertension 2023;80:534-40.

6. Stergiou GS, Mukkamala R, Avolio A, Kyriakoulis KG, Mieke S, Murray A, et al. J Hypertens 2022;40:1449-60.

7. Chan G, Cooper R, Hosanee M, et al. Multi-site photoplethysmography technology for blood pressure assessment: challenges and recommendations. J Clin Med 2019;8:1827.

8. Natarajan K, Yavarimanesh M, Wang W, Mukkamala R. Chapter 6 - Camera-based blood pressure monitoring. In: Wang W, Wang X, editors. Contactless vital signs monitoring. Academic Press; 2022. p. 117-48.

9. Mieloszyk R, Twede H, Lester J, et al. A comparison of wearable tonometry, photoplethysmography, and electrocardiography for cuffless measurement of blood pressure in an ambulatory setting. IEEE J Biomed Health Inform 2022;26:2864-75.

10. Fine J, Branan KL, Rodriguez AJ, et al. Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring. Biosensors (Basel) 2021;11:126.

11. Perez MV, Mahaffey KW, Hedlin H, et al. Apple heart study investigators. Large-scale assessment of a smartwatch to identify atrial fibrillation. N Engl J Med 2019;381:1909-17.

12. Lubitz SA, Faranesh AZ, Selvaggi C, et al. Detection of atrial fibrillation in a large population using wearable devices: the fitbit heart study. Circulation 2022;146:1415-24.

13. Statista Research Department. Published Aug 22, 2022. Available from: https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/ [Last accessed on 19 Apr 2023].

14. Allado E, Poussel M, Renno J, et al. Remote photoplethysmography is an accurate method to remotely measure respiratory rate: a hospital-based trial. J Clin Med 2022;11:3647.

15. Allado E, Poussel M, Moussu A, et al. Accurate and reliable assessment of heart rate in real-life clinical settings using an imaging photoplethysmography. J Clin Med 2022;11:6101.

16. Nishidate I. Chapter 5 - Camera-based blood oxygen measurement. In: Wang W, Wang X, editors. Contactless vital signs monitoring. Academic Press; 2022. p. 99-116.

17. Couderc JP, Kyal S, Mestha LK, et al. Detection of atrial fibrillation using contactless facial video monitoring. Heart Rhythm 2015;12:195-201.

18. Yan BP, Lai WHS, Chan CKY, et al. Contact-free screening of atrial fibrillation by a smartphone using facial pulsatile photoplethysmographic signals. J Am Heart Assoc 2018;7:e008585.

19. Yan BP, Lai WHS, Chan CKY, et al. High-throughput, contact-free detection of atrial fibrillation from video with deep learning. JAMA Cardiol 2020;5:105-7.

20. Elgendi M. On the analysis of fingertip photoplethysmogram signals. Curr Cardiol Rev 2012;8:14-25.

21. Selvaraju V, Spicher N, Wang J, et al. Continuous monitoring of vital signs using cameras: a systematic review. Sensors (Basel) 2022;22:4097.

22. Molinaro N, Schena E, Silvestri S, et al. Contactless vital signs monitoring from videos recorded with digital cameras: an overview. Front Physiol 2022;13:801709.

23. Mukkamala R, Hahn JO, Inan OT, et al. Toward ubiquitous blood pressure monitoring via pulse transit time: theory and practice. IEEE Trans Biomed Eng 2015;62:1879-901.

24. Moço AV, Stuijk S, de Haan G. New insights into the origin of remote PPG signals in visible light and infrared. Sci Rep 2018;8:8501.

25. Image credits for Figure 1A: Cios A, Ciepielak M, Szymański Ł, Lewicka A, Cierniak S, Stankiewicz W, Mendrycka M, Lewicki S. CC BY 4.0 via Wikimedia Commons. Available from: https://doi.org/10.3390/ijms22052437 [Last accessed on 24 Apr 2023].

26. Hertzman AB. The blood supply of various skin areas as estimated by the photoelectric plethysmograph. AM J Physiol 1938;124:328-40.

27. Kamshilin AA, Nippolainen E, Sidorov IS, et al. A new look at the essence of the imaging photoplethysmography. Sci Rep 2015;5:10494.

28. Balmer J, Pretty C, Davidson S, et al. Pre-ejection period, the reason why the electrocardiogram Q-wave is an unreliable indicator of pulse wave initialization. Physiol Meas 2018;39:095005.

29. Etemadi M, Inan OT. Wearable ballistocardiogram and seismocardiogram systems for health and performance. J Appl Physiol (1985) 2018;124:452-61.

30. Steinman J, Barszczyk A, Sun HS, Lee K, Feng ZP. Smartphones and video cameras: future methods for blood pressure measurement. Front Digit Health 2021;3:770096.

31. Fleischhauer V, Feldheiser A, Zaunseder S. Beat-to-beat blood pressure estimation by photoplethysmography and its interpretation. Sensors (Basel) 2022;22:7037.

32. Hill BL, Rakocz N, Rudas Á, et al. Imputation of the continuous arterial line blood pressure waveform from non-invasive measurements using deep learning. Sci Rep 2021;11:15755.

33. Mukkamala R, Hahn JO. Toward ubiquitous blood pressure monitoring via pulse transit time: predictions on maximum calibration period and acceptable error limits. IEEE Trans Biomed Eng 2018;65:1410-20.

34. Valencell. “Valencell unveils calibration free cuffless blood pressure monitoring solution targeting over the counter use”. Available from: https://valencell.com/news/valencell-unveils-calibration-free-cuffless-blood-pressure-monitoring-solution-targeting-over-the-counter-use/ [Last accessed on 19 Apr 2023].

35. Shao D, Yang Y, Liu C, Tsow F, Yu H, Tao N. Noncontact monitoring breathing pattern, exhalation flow rate and pulse transit time. IEEE Trans Biomed Eng 2014;61:2760-7.

36. Wang Y, Liu Z, Ma S. Cuff-less blood pressure measurement from dual-channel photoplethysmographic signals via peripheral pulse transit time with singular spectrum analysis. Physiol Meas 2018;39:025010.

37. Shao D, Tsow F, Liu C, Yang Y, Tao N. Simultaneous Monitoring of Ballistocardiogram and Photoplethysmogram Using a Camera. IEEE Trans Biomed Eng 2017;64:1003-10.

38. Chan A, Chan D, Lee H, Ng CC, Yeo AHL. Reporting adherence, validity and physical activity measures of wearable activity trackers in medical research: a systematic review. Int J Med Inform 2022;160:104696.

39. Östlind E, Sant'Anna A, Eek F, Stigmar K, Ekvall Hansson E. Physical activity patterns, adherence to using a wearable activity tracker during a 12-week period and correlation between self-reported function and physical activity in working age individuals with hip and/or knee osteoarthritis. BMC Musculoskelet Disord 2021;22:450.

40. Haan G, Jeanne V. Robust pulse rate from chrominance-based rPPG. IEEE Trans Biomed Eng 2013;60:2878-86.

41. Zhou Y, Ni H, Zhang Q, Wu Q. The noninvasive blood pressure measurement based on facial images processing. IEEE Sensors J 2019;19:10624-34.

42. Blackford E, Estepp J, McDuff D. Remote spectral measurements of the blood volume pulse with applications for imaging photoplethysmography. Proc. SPIE 10501, Optical Diagnostics and Sensing XVIII: toward point-of-care diagnostics.

43. Verkruysse W, Svaasand LO, Nelson JS. Remote plethysmographic imaging using ambient light. Opt Express 2008;16:21434-45.

44. Shirbani F, Hui N, Tan I, Butlin M, Avolio AP. Effect of ambient lighting and skin tone on estimation of heart rate and pulse transit time from video plethysmography. Annu Int Conf IEEE Eng Med Biol Soc 2020;2020:2642-5.

45. McDuff D, Gontarek S, Picard RW. Improvements in remote cardiopulmonary measurement using a five band digital camera. IEEE Trans Biomed Eng 2014;61:2593-601.

46. McDuff D, Gontarek S, Picard RW. Remote detection of photoplethysmographic systolic and diastolic peaks using a digital camera. IEEE Trans Biomed Eng 2014;61:2948-54.

47. Wieringa FP, Mastik F, van der Steen AF. Contactless multiple wavelength photoplethysmographic imaging: a first step toward "SpO2 camera" technology. Ann Biomed Eng 2005;33:1034-41.

48. Poh MZ, McDuff DJ, Picard RW. Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Opt Express 2010;18:10762-74.

49. Jeong IC, Finkelstein J. Introducing Contactless Blood Pressure Assessment Using a High Speed Video Camera. J Med Syst 2016;40:77.

50. Frey L, Menon C, Elgendi M. Blood pressure measurement using only a smartphone. NPJ Digit Med 2022;5:86.

51. Jain M, Deb S, Subramanyam AV. Face video based touchless blood pressure and heart rate estimation. 2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP). 2016; p. 1-5.

52. Secerbegovic A, Bergsland J, Halvorsen PS, Suljanovic N, Mujcic A, Balasingham I. Blood pressure estimation using video plethysmography. Conference Proceedings: 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI). 2016; p. 461-4.

53. Khong WL, Rao NSVK, Mariappan M. Blood pressure measurements using non-contact video imaging techniques. Conference Proceedings: 2017 IEEE 2nd International Conference on Automatic Control and Intelligent Systems (I2CACIS). 2017; p. 35-40.

54. Adachi Y, Edo Y, Ogawa R, Tomizawa R, Iwai Y, Okumura T. Noncontact blood pressure monitoring technology using facial photoplethysmograms. Annu Int Conf IEEE Eng Med Biol Soc 2019;2019:2411-5.

55. Luo H, Yang D, Barszczyk A, et al. Smartphone-based blood pressure measurement using transdermal optical imaging technology. Circ Cardiovasc Imaging 2019;12:e008857.

56. Fan X, Ye Q, Yang X, Choudhury SD. Robust blood pressure estimation using an RGB camera. J Ambient Intell Human Comput 2020;11:4329-36.

57. Rong M, Li K. A blood pressure prediction method based on imaging photoplethysmography in combination with machine learning. Biomed Signal Process Control 2021;64:102328.

58. Stergiou GS, Alpert B, Mieke S, et al. 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. J Hypertens 2018;36:472-8.

59. Block RC, Yavarimanesh M, Natarajan K, et al. Conventional pulse transit times as markers of blood pressure changes in humans. Sci Rep 2020;10:16373.

60. Oiwa K, Bando S, Nozawa A. Contactless blood pressure sensing using facial visible and thermal images. Artif Life Robotics 2018;23:387-94.

61. Shirbani F, Blackmore C, Kazzi C, Tan I, Butlin M, Avolio AP. Sensitivity of video-based pulse arrival time to dynamic blood pressure changes. Annu Int Conf IEEE Eng Med Biol Soc 2018;2018:3639-41.

62. Chen W, McDuff D. DeepPhys: video-based physiological measurement using convolutional attention networks. ECCV 2018: European Conference on Computer Vision; 2018 Sept 8 - 14.

63. Viejo C, Fuentes S, Torrico DD, Dunshea FR. Non-contact heart rate and blood pressure estimations from video analysis and machine learning modelling applied to food sensory responses: a case study for chocolate. Sensors (Basel) 2018;18:1802.

64. Pickering TG, Hall JE, Appel LJ, et al. Recommendations for blood pressure measurement in humans and experimental animals: part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. Circulation 2005;111:697-716.

65. Pagonas N, Schmidt S, Eysel J, et al. Impact of atrial fibrillation on the accuracy of oscillometric blood pressure monitoring. Hypertension 2013;62:579-84.

66. Pilz N, Patzak A, Bothe TL. Continuous cuffless and non-invasive measurement of arterial blood pressure-concepts and future perspectives. Blood Press 2022;31:254-69.

67. Qin C, Wang X, Xu G, Ma X. Advances in cuffless continuous blood pressure monitoring technology based on PPG signals. Biomed Res Int 2022;2022:8094351.

68. Registry of Open Data on AWS. MIMIC-III (“Medical Information Mart for Intensive Care”), 2022. Available from: https://registry.opendata.aws/mimiciii [Last accessed on 19 Apr 2023].

69. McDuff D, Wander M, Liu X, Hill BL, Hernandez J, Lester J, Baltrusaitis T. SCAMPS: synthetics for camera measurement of physiological signals. In Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track.

70. Singh A, Mountjoy N, McElroy D, et al. Patient perspectives with telehealth visits in cardiology during COVID-19: online patient survey study. JMIR Cardio 2021;5:e25074.

71. Yuan N, Pevnick JM, Botting PG, et al. Patient use and clinical practice patterns of remote cardiology clinic visits in the era of COVID-19. JAMA Netw Open 2021;4:e214157.

72. Forouzanfar MH, Liu P, Roth GA, et al. Global burden of hypertension and systolic blood pressure of at least 110 to 115 mm Hg, 1990-2015. JAMA 2017;317:165-82.

73. Turner JR, Viera AJ, Shimbo D. Ambulatory blood pressure monitoring in clinical practice: a review. Am J Med 2015;128:14-20.

74. Margolis KL, Dehmer SP, Sperl-Hillen J, et al. Cardiovascular events and costs with home blood pressure telemonitoring and pharmacist management for uncontrolled hypertension. Hypertension 2020;76:1097-103.

75. Wang X, Shao D. Chapter 1 - Human physiology and contactless vital signs monitoring using camera and wireless signals. Contactless Vital Signs Monitoring. Academic Press; 2022. p. 1-24.

76. Pokee D, Barbosa Pereira W, Mösch L, Follmann A, Czaplik M. Consciousness detection on injured simulated patients using manual and automatic classification via visible and infrared imaging. Sensors (Basel) 2021;21:8455.

77. Bragazzi NL, Zhong W, Shu J, et al. Burden of heart failure and underlying causes in 195 countries and territories from 1990 to 2017. Eur J Prev Cardiol 2021;28:1682-90.

78. Mishra K, Edwards B. Cardiac outpatient care in a digital age: remote cardiology clinic visits in the era of COVID-19. Curr Cardiol Rep 2022;24:1-6.

79. Kitsiou S, Vatani H, Paré G, et al. Effectiveness of mobile health technology interventions for patients with heart failure: systematic review and meta-analysis. Can J Cardiol 2021;37:1248-59.

80. Liu S, Li J, Wan DY, et al. Effectiveness of eHealth self-management interventions in patients with heart failure: systematic review and meta-analysis. J Med Internet Res 2022;24:e38697.

81. Amelard R, Hughson RL, Greaves DK, et al. Non-contact hemodynamic imaging reveals the jugular venous pulse waveform. Sci Rep 2017;7:40150.

82. Yang SS, Park KM, Kim YW, Kim DI. Three-grade classification of photoplethysmography for evaluating the effects of treatment in Raynaud phenomenon. Angiology 2013;64:609-13.

83. Guo A, Pasque M, Loh F, et al. Heart failure diagnosis, readmission, and mortality prediction using machine learning and artificial intelligence models. Curr Epidemiol Rep 2020;7:212-219.

84. Norman GA. Decentralized clinical trials: the future of medical product development? JACC Basic Transl Sci 2021;6:384-7.

85. Weenk M, Bredie SJ, Koeneman M, Hesselink G, van Goor H, van de Belt TH. Continuous monitoring of vital signs in the general ward using wearable devices: randomized controlled trial. J Med Internet Res 2020;22:e15471.

86. Sun L, Joshi M, Khan SN, Ashrafian H, Darzi A. Clinical impact of multi-parameter continuous non-invasive monitoring in hospital wards: a systematic review and meta-analysis. J R Soc Med 2020;113:217-24.

87. Areia C, Biggs C, Santos M, et al. The impact of wearable continuous vital sign monitoring on deterioration detection and clinical outcomes in hospitalised patients: a systematic review and meta-analysis. Crit Care 2021;25:351.

88. Leenen JPL, Leerentveld C, van Dijk JD, van Westreenen HL, Schoonhoven L, Patijn GA. Current evidence for continuous vital signs monitoring by wearable wireless devices in hospitalized adults: systematic review. J Med Internet Res 2020;22:e18636.

89. Mankidy B, Howard C, Morgan CK, et al. Reduction of in-hospital cardiac arrest with sequential deployment of rapid response team and medical emergency team to the emergency department and acute care wards. PLoS One 2020;15:e0241816.

90. Pronovost PJ, Cole MD, Hughes RM. Remote patient monitoring during COVID-19: an unexpected patient safety benefit. JAMA 2022;327:1125-6.

91. Capraro GA, Balmaekers B, den Brinker AC, et al. Contactless vital signs acquisition using video photoplethysmography, motion analysis and passive infrared thermography devices during emergency department walk-in triage in pandemic conditions. J Emerg Med 2022;63:115-29.

92. Rasche S, Trumpp A, Schmidt M, et al. Remote photoplethysmographic assessment of the peripheral circulation in critical care patients recovering from cardiac surgery. Shock 2019;52:174-82.

93. Jorge J, Villarroel M, Tomlinson H, et al. Non-contact physiological monitoring of post-operative patients in the intensive care unit. NPJ Digit Med 2022;5:4.

94. Svoboda L, Sperrhake J, Nisser M, Zhang C, Notni G, Proquitté H. Contactless heart rate measurement in newborn infants using a multimodal 3D camera system. Front Pediatr 2022;10:897961.

95. Villarroel M, Jorge J, Meredith D, Sutherland S, Pugh C, Tarassenko L. Non-contact vital-sign monitoring of patients undergoing haemodialysis treatment. Sci Rep 2020;10:18529.

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