1. Tuckson, R. V., Edmunds, M. & Hodgkins, M. L. Telehealth. N. Engl. J. Med. 377, 1585–1592 (2017).
2. Benziger, C. P., Huffman, M. D., Sweis, R. N. & Stone, N. J. The Telehealth Ten: A Guide for a Patient-Assisted Virtual Physical Examination. Am. J. Med. 134, 48–51 (2021).
3. Hyman, P. The Disappearance of the Primary Care Physical Examination-Losing Touch. JAMA Intern. Med. (2020) doi:10.1001/jamainternmed.2020.3546.
4. Hollander, J. E. & Carr, B. G. Virtually Perfect? Telemedicine for Covid-19. N. Engl. J. Med. 382, 1679–1681 (2020).
5. Cutler, D. M., Nikpay, S. & Huckman, R. S. The Business of Medicine in the Era of COVID-19. JAMA 323, 2003–2004 (2020).
6. Rowland, S. P., Fitzgerald, J. E., Holme, T., Powell, J. & McGregor, A. What is the clinical value of mHealth for patients? NPJ Digit Med 3, 4 (2020).
7. Contributors to Wikimedia projects. List of countries by smartphone penetration. https://en.wikipedia.org/wiki/List_of_countries_by_smartphone_penetration (2014).
8. Shao, D., Liu, C. & Tsow, F. Noncontact Physiological Measurement Using a Camera: A Technical Review and Future Directions. ACS Sensors (2020) doi:10.1021/acssensors.0c02042.
9. De Ridder, B., Van Rompaey, B., Kampen, J. K., Haine, S. & Dilles, T. Smartphone Apps Using Photoplethysmography for Heart Rate Monitoring: Meta-Analysis. JMIR Cardio 2, e4 (2018).
10. Sun, Y. & Thakor, N. Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging. IEEE Trans. Biomed. Eng. 63, 463–477 (2016).
11. Allen, J. Photoplethysmography and its application in clinical physiological measurement. Physiol. Meas. 28, R1–39 (2007).
12. Poh, M.-Z., McDuff, D. J. & Picard, R. W. Advancements in noncontact, multiparameter physiological measurements using a webcam. IEEE Trans. Biomed. Eng. 58, 7–11 (2011).
13. Koetsier, J. The Top 10 Health & Fitness Apps Of 2020 Have One Thing In Common (Mostly). Forbes https://www.forbes.com/sites/johnkoetsier/2020/10/05/the-top-10-health--fitness-apps-of-2020-have-one-thing-in-common-mostly/ (2020).
14. Hertzman, A. B. The Blood Supply of Various Skin Areas as Estimated by the Photoelectric Plethysmograph. (1938).
15. Coppetti, T. et al. Accuracy of smartphone apps for heart rate measurement. Eur. J. Prev. Cardiol. 24, 1287–1293 (2017).
16. American National Standards Institute. & Association for the Advancement of Medical Instrumentation. Cardiac monitors, heart rate meters, and alarms. (Arlington, Va. : Association for the Advancement of Medical Instrumentation, ©2002., 2002).
17. CONSUMER TECHNOLOGY ASSOCIATION. Physical Activity Monitoring for Heart Rate (ANSI/CTA-2065). https://shop.cta.tech/products/physical-activity-monitoring-for-heart-rate.
18. Bent, B., Goldstein, B. A., Kibbe, W. A. & Dunn, J. P. Investigating sources of inaccuracy in wearable optical heart rate sensors. NPJ Digit Med 3, 18 (2020).
19. Shcherbina, A. et al. Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort. J Pers Med 7, (2017).
20. Bickler, P. E., Feiner, J. R. & Severinghaus, J. W. Effects of skin pigmentation on pulse oximeter accuracy at low saturation. Anesthesiology 102, 715–719 (2005).
21. Sjoding, M. W., Dickson, R. P., Iwashyna, T. J., Gay, S. E. & Valley, T. S. Racial Bias in Pulse Oximetry Measurement. N. Engl. J. Med. 383, 2477–2478 (2020).
22. Ries, A. L., Prewitt, L. M. & Johnson, J. J. Skin color and ear oximetry. Chest 96, 287–290 (1989).
23. Fallow, B. A., Tarumi, T. & Tanaka, H. Influence of skin type and wavelength on light wave reflectance. J. Clin. Monit. Comput. 27, 313–317 (2013).
24. Nam, Y., Lee, J. & Chon, K. H. Respiratory rate estimation from the built-in cameras of smartphones and tablets. Ann. Biomed. Eng. 42, 885–898 (2014).
25. Consumer Technology Association: CTA Committees, Subcommittees and Working Groups. https://standards.cta.tech/kwspub/home/Committees/.
26. U.S. Food & Drug Administration. 510(k) Premarket Notification: Philips Biosensor BX100. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K192875.
27. U.S. Food and Drug Administration. The C100 Contactless Breathing Monitor: 510(k) Premarket Notification. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K200445.
28. MightySatTM Rx Fingertip Pulse Oximeter. https://techdocs.masimo.com/globalassets/techdocs/pdf/lab-10169a_master.pdf.
29. Li, T. et al. A pilot study of respiratory rate derived from a wearable biosensor compared with capnography in emergency department patients. Open Access Emerg. Med. 11, 103–108 (2019).
30. Jensen, M. T., Suadicani, P., Hein, H. O. & Gyntelberg, F. Elevated resting heart rate, physical fitness and all-cause mortality: a 16-year follow-up in the Copenhagen Male Study. Heart 99, 882–887 (2013).
31. Cole, C. R., Blackstone, E. H., Pashkow, F. J., Snader, C. E. & Lauer, M. S. Heart-rate recovery immediately after exercise as a predictor of mortality. N. Engl. J. Med. 341, 1351–1357 (1999).
32. Flores Mateo, G., Granado-Font, E., Ferré-Grau, C. & Montaña-Carreras, X. Mobile Phone Apps to Promote Weight Loss and Increase Physical Activity: A Systematic Review and Meta-Analysis. J. Med. Internet Res. 17, e253 (2015).
33. Wu, Y. et al. Mobile App-Based Interventions to Support Diabetes Self-Management: A Systematic Review of Randomized Controlled Trials to Identify Functions Associated with Glycemic Efficacy. JMIR Mhealth Uhealth 5, e35 (2017).
34. Cadmus-Bertram, L. A., Marcus, B. H., Patterson, R. E., Parker, B. A. & Morey, B. L. Randomized Trial of a Fitbit-Based Physical Activity Intervention for Women. Am. J. Prev. Med. 49, 414–418 (2015).
35. U.S. Department of Health and Human Services. Physical Activity Guidelines for Americans, 2nd edition. https://health.gov/sites/default/files/2019-09/Physical_Activity_Guidelines_2nd_edition.pdf.
36. Centers for Disease Control and Prevention. Target Heart Rate and Estimated Maximum Heart Rate. Centers for Disease Control and Prevention https://www.cdc.gov/physicalactivity/basics/measuring/heartrate.htm (2020).
37. Arnett, D. K. et al. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 140, e596–e646 (2019).
38. Webster, D. E. et al. Heart Snapshot: a broadly validated smartphone measure of VO2max for collection of real world data. bioRxiv (2020) doi:10.1101/2020.07.02.185314.
39. Reilly, B. M. Physical examination in the care of medical inpatients: an observational study. Lancet 362, 1100–1105 (2003).
40. Verghese, A., Charlton, B., Kassirer, J. P., Ramsey, M. & Ioannidis, J. P. A. Inadequacies of Physical Examination as a Cause of Medical Errors and Adverse Events: A Collection of Vignettes. Am. J. Med. 128, 1322–4.e3 (2015).
41. Bickley, L. S. Bates’ Guide to Physical Examination and History Taking. (Lippincott Raven, 2007).
42. Bickley, L. & Szilagyi, P. G. Bates’ Guide to Physical Examination and History-Taking. (Lippincott Williams & Wilkins, 2012).
43. Nakajima, K., Tamura, T. & Miike, H. Monitoring of heart and respiratory rates by photoplethysmography using a digital filtering technique. Med. Eng. Phys. 18, 365–372 (1996).
44. Hill, A., Kelly, E., Horswill, M. S. & Watson, M. O. The effects of awareness and count duration on adult respiratory rate measurements: An experimental study. J. Clin. Nurs. 27, 546–554 (2018).
45. Chong, J. W., Esa, N., McManus, D. D. & Chon, K. H. Arrhythmia discrimination using a smart phone. IEEE J Biomed Health Inform 19, 815–824 (2015).
46. Zaman, R. et al. Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone. Sensors 17, (2017).
47. Chatterjee, A. & Prinz, A. Image Analysis on Fingertip Video to Obtain PPG. Biomedical and Pharmacology Journal 11, 1811–1827 (2018).
48. Wang, W., den Brinker, A. C., Stuijk, S. & de Haan, G. Algorithmic Principles of Remote PPG. IEEE Trans. Biomed. Eng. 64, 1479–1491 (2017).
49. Karlen, W., Ansermino, J. M., Dumont, G. A. & Scheffer, C. Detection of the optimal region of interest for camera oximetry. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2013, 2263–2266 (2013).
50. Del Bino, S. & Bernerd, F. Variations in skin colour and the biological consequences of ultraviolet radiation exposure. Br. J. Dermatol. 169 Suppl 3, 33–40 (2013).
51. Kinyanjui, N. M. et al. Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets. (2019).
52. Bohnhorst, B., Peter, C. S. & Poets, C. F. Pulse oximeters’ reliability in detecting hypoxemia and bradycardia: comparison between a conventional and two new generation oximeters. Crit. Care Med. 28, 1565–1568 (2000).
53. Altman, D. G. & Bland, J. M. Measurement in Medicine: The Analysis of Method Comparison Studies. The Statistician vol. 32 307 (1983).
54. Jorge, J. et al. Non-Contact Monitoring of Respiration in the Neonatal Intensive Care Unit. 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017) (2017) doi:10.1109/fg.2017.44.
55. Massaroni, C., Lopes, D. S., Lo Presti, D., Schena, E. & Silvestri, S. Contactless Monitoring of Breathing Patterns and Respiratory Rate at the Pit of the Neck: A Single Camera Approach. Journal of Sensors vol. 2018 1–13 (2018).
56. Al-Naji, A. & Chahl, J. Simultaneous Tracking of Cardiorespiratory Signals for Multiple Persons Using a Machine Vision System With Noise Artifact Removal. IEEE J Transl Eng Health Med 5, 1900510 (2017).
57. Yang, Q. et al. HealCam: Energy-efficient and privacy-preserving human vital cycles monitoring on camera-enabled smart devices. Computer Networks vol. 138 192–200 (2018).
58. Chatterjee, A., Prathosh, A. P. & Praveena, P. Real-time respiration rate measurement from thoracoabdominal movement with a consumer grade camera. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2016, 2708–2711 (2016).
59. Janssen, R., Wang, W., Moço, A. & de Haan, G. Video-based respiration monitoring with automatic region of interest detection. Physiol. Meas. 37, 100–114 (2016).
60. Wadhwa, N., Rubinstein, M., Durand, F. & Freeman, W. T. Riesz pyramids for fast phase-based video magnification. 2014 IEEE International Conference on Computational Photography (ICCP) (2014) doi:10.1109/iccphot.2014.6831820.
61. Ragan-Kelley, J. et al. Halide: a language and compiler for optimizing parallelism, locality, and recomputation in image processing pipelines. in Proceedings of the 34th ACM SIGPLAN Conference on Programming Language Design and Implementation 519–530 (Association for Computing Machinery, 2013).