Can Wearable Devices Accurately Measure Heart Rate Variability? A Systematic Review

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Background: A growing number of wearable devices claim to provide accurate, cheap and easily applicable heart rate variability (HRV) indices. This is mainly accomplished by using wearable photoplethysmography (PPG) and/or electrocardiography (ECG), through simple and non-invasive techniques, as a substitute of the gold standard RR interval estimation through electrocardiogram. Although the agreement between pulse rate variability (PRV) and HRV has been evaluated in the literature, the reported results are still inconclusive especially when using wearable devices.

Aim: The purpose of this systematic review is to investigate if wearable devices provide a reliable and precise measurement of classic HRV parameters in rest as well as during exercise.

Materials and methods: A search strategy was implemented to retrieve relevant articles from MEDLINE and SCOPUS databases, as well as, through internet search. The 308 articles retrieved were reviewed for further evaluation according to the predetermined inclusion/exclusion criteria.

Results: Eighteen studies were included. Sixteen of them integrated ECG - HRV technology and two of them PPG - PRV technology. All of them examined wearable devices accuracy in RV detection during rest, while only eight of them during exercise. The correlation between classic ECG derived HRV and the wearable RV ranged from very good to excellent during rest, yet it declined progressively as exercise level increased.

Conclusions: Wearable devices may provide a promising alternative solution for measuring RV. However, more robust studies in non-stationary conditions are needed using appropriate methodology in terms of number of subjects involved, acquisition and analysis techniques implied.

1. Liu AB, Wu HT, Liu CC, et al. The factors influence compatibility of pulse-pulse intervals with R-R intervals. In: EMBC 2013. Proceedings of 2013 Annual International Conference of the IEEE: Engineering in Medicine and Biology Society Piscataway, NJ: IEEE Service Center. 2013; p. 2068-71.

2. Task force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: Standards of measurement, physiological interpretation and clinical use. Circulation 1996;93(5):1043-65.

3. Buccelletti E, Gilardi E, Scaini E, et al. Heart rate variability and myocardial infarction: systematic literature review and meta-analysis. Eur Rev Med Pharmacol Sci 2009;13(4):299-307.

4. La Rovere MT, Pinna GD, Maestri R, et al. Autonomic markers and cardiovascular and arrhythmic events in heart failure patients: still a place in prognostication? Data from the GISSI-HF Trial. Eur J Heart Fail 2012;14(12):1410-9.

5. von Rosenberg W, Chanwimalueang T, Adjei T, et al. Resolving ambiguities in the LF/HF ratio: LFHF scatter plots for the categorization of mental and physical stress from HRV. Front Physiol 2017;8:360.

6. Lehrer PM, Vaschillo E, Vaschillo B, et al. Heart rate variability biofeedback increases baroreflex gain and peak expiratory flow. Psychosom Med 2003;65(5):796-805.

7. Allen J. Photoplethysmography and its application in clinical physiological measurement. Physiol Meas 2007;28:R1-39.

8. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol 2009;62(10):1006-12.

9. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol 2009;62:e1-34.

10. Wallén MB, Hasson D, Theorell T, et al. Possibilities and limitations of the Polar RS800 in measuring heart rate variability at rest. Eur J Appl Physiol 2012;112(3):1153-65.

11. Vasconcellos FV, Seabra A, Cunha FA, et al. Heart rate variability assessment with fingertip photoplethysmography and Polar RS800cx as compared with electrocardiography in obese adolescents. Blood Press Monit 2015;20(6):351-60.

12. Gamelin FX, Baquet G, Berthoin S, et al. Validity of the Polar S810 to measure R-R intervals in children. Int J Sports Med 2008;29:134-8.

13. Akintola A, van de Pol V, Bimmel D, et al. Comparative analysis of the Equivital EQ02 life monitor with holter ambulatory ECG device for continuous measurement of ECG, heart rate, and heart rate variability: A validation study for precision and accuracy. Front Physiol 2016;7:391.

14. Flatt A, Esco MR. Validity of the Ithlete™ smart phone application for determining ultra-short-term heart rate variability. J Hum Kinet 2013;39:85-92.

15. Gamelin FX, Berthoin S, Bosquet L. Validity of the Polar S810 heart rate monitor to measure R-R intervals at rest. Med Sci Sports Exerc 2006;38:887-93.

16. Giles D, Draper N, Neil W. Validity of the Polar V800 heart rate monitor to measure RR intervals at rest. Eur J Appl Physiol 2016;116:563-71.

17. Hernando D, Garatachea N, Almeida R, et al. Validation of heart rate monitor Polar RS800 for heart rate variability analysis during exercise. J Strength Cond Res 2016; doi: 10.1519/JSC.0000000000001662.

18. Hong S, Yang Y, Kim S, et al. Performance study of the wearable one-lead wireless electrocardio-graphic monitoring system. Telemed J E Health 2009;15:166-75.

19. Kingsley M, Lewis MJ, Marson RE. Comparison of Polar 810s and an ambulatory ECG system for RR interval measurement during progressive exercise. Int J Sports Med 2005;26:39-44.

20. Nunan D, Jakovljevic DG, Donovan G, et al. Levels of agreement for RR intervals and short-term heart rate variability obtained from the Polar S810 and an alternative system. Eur J Appl Physiol 2008:103:529-37.

21. Nunan D, Donovan G, Jakovljevic DG, et al. Validity and reliability of short-term heart-rate variability from the Polar S810. Med Sci Sports Exerc 2009;41:243-50.

22. Plews DJ, Scott B, Altini M, et al. Comparison of heart rate variability recording with smart phone photoplethysmographic, Polar H7 chest strap and electrocardiogram methods. Int J Sports Physiol Perform 2017;12(10):1324-8.

23. Romagnoli M, Alis R, Guillen J, et al. A novel device based on smart textile to control heart’s activity during exercise. Australas Phys Eng Sci Med 2014;37:377-84.

24. Vanderlei LC, Silva RA, Pastre CM, et al. Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains. Braz J Med Biol Res 2008;41:854-9.

25. Weippert M, Kumar M, Kreuzfeld S, et al. Comparison of three mobile devices for measuring R-R intervals and heart rate variability: Polar S810i, Suunto t6 and an ambulatory ECG system. Eur J Appl Physiol 2010;109:779-86.

26. Esco MR, Flatt AA, Nakamura FY. Agreement between a smartphone pulse sensor application and electrocardiography for determining lnRMSSD. J Strength Cond Res 2017;31:380-5.

27. Heathers JA. Smartphone-enabled pulse rate variability: an alternative methodology for the collection of heart rate variability in psychophysiological research. Int J Psychophysiol 2013;89:297-304.

28. Weinschenk SW, Beise RD, Lorenz, J. Heart rate variability (HRV) in deep breathing tests and 5-min short-term recordings: agreement of ear photoplethysmography with ECG measurements, in 343 subjects. Eur J Appl Physiol 2016;116:1527-35.

29. Drinnan MJ, Allen J, Murray A. Relation between heart rate and pulse transit time during paced respiration. Physiol Meas 2001;22(3):425-32.

30. Gisselman AS, D’Amico M, Smoliga JM. Optimizing inter-session reliability of heart rate variability - the effects of artifact correction and breathing type. J Strength Cond Res 2017. doi: 10.1519/JSC.0000000000002258.

31. Maheshwari A, Norby FL, Soliman EZ, et al. Low heart rate variability in a 2-minute electrocardiogram recording is associated with an increased risk of sudden cardiac death in the general population: the atherosclerosis risk in communities study. PLos One 2016;11(8):e0161648.

32. Georgiou K, Larentzakis A, Papavassiliou A. Surgeons and surgical trainees acute stress in real operations or simulation: a systematic review. Surgeon 2017;15(6):355-65.

33. Shaffer F, Ginsberg JP. An overview of heart rate variability metrics and norms. Front Public Health 2017;5:258.

34. Pérez-Riera AR, Barbosa-Barros R, Daminello-Raimundo R, et al. Main artifacts in electrocardiography. Ann Noninvasive Electrocardiol 2017; doi:10.1111/anec.12494.

35. Gambarotta N, Aletti F, Baselli G, et al. A review of methods for the signal quality assessment to improve reliability of heart rate and blood pressures derived parameters. Med Biol Eng Comput 2016;54:1025-35.

36. Schäfer A, Vagedes J. How accurate is pulse rate variability as an estimate of heart rate variability? A review on studies comparing photoplethysmographic technology with an electrocardiogram. Int J Cardiol 2013;166:15-29

37. Selvaraj N, Jaryal A, Santhosh J, et al. Assessment of heart rate variability derived from finger-tip photoplethysmography as compared to electrocardiography. J Med Eng Technol 2008;32(6):479-84.

38. Shin H. Ambient temperature effect on pulse rate variability as an alternative to heart rate variability in young adult. J Clin Monit Comput 2016;30(6):939-48.

39. Lee J, Matsumura K, Yamakoshi K, et al. Comparison between red, green and blue light reflection photoplethysmography for heart rate monitoring during motion. Conf Proc IEEE Eng Med Biol Soc 2013;2013:1724-7.

40. Wong JS, Lu WA, Wu KT, et al. A comparative study of pulse rate variability and heart rate variability in healthy subjects. J Clin Monit Comput 2012;26(2):107-14.

41. Pinheiro N, Couceiro R, Henriques J, et al. Can PPG be used for HRV analysis? Conf Proc IEEE Eng Med Biol Soc 2016;2016:2945-9.

42. Lee ES, Lee JS, Joo MC, et al. Accuracy of heart rate measurement using smart phones during treadmill exercise in male patients with ischemic heart disease. Ann Rehabil Med 2017;41(1):129-37.

43. Sun Y, Thakor N. Photoplethysmography revisited: from contact to noncontact, from point to imaging. IEEE Trans Biomed Eng 2016;63(3):463-77.

44. Chen X, Huang Y, Yun F, et al. Effect of changes in sympathovagal balance on the accuracy of heart rate variability obtained from photoplethysmography. Exp Ther Med 2015;10(6):2311-8.

45. Gil E, Orini M, Bailón R, et al. Photoplethysmography pulse rate variability as a surrogate measurement of heart rate variability during non-stationary conditions. Physiol Meas 2010;31(9):1271-90.

46. Tarvainen MP, Niskanen JP, Lipponen JA, et al. Kubios HRV–heart rate variability analysis software. Comput Methods Programs Biomed 2014;113(1):210-20.

47. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307-10.

48. Qiu Y, Cai Y, Zhu Y, et al. Poincaré plot analysis for pulse interval extracted from non-contact photoplethysmography. Conf Proc IEEE Eng Med Biol Soc 2005;2:1964-7.

49. Chreiteh S, Belhage B, Hoppe K, et al. Sternal pulse rate variability compared with heart rate variability on healthy subjects. Conf Proc IEEE Eng Med Biol Soc 2014;2014:3394-7.

50. Blackford EB, Estep JR. Effects of frame rate and image resolution on pulse rate measured using multiple camera imaging photoplethysmography. In: B. Gimi, & R. C. Molthen, (Eds.). Proceedings of SPIE 9417, Medical imaging 2015: Biomedical applications in molecular structural and functional imaging. 2015. p. 1-14.

51. Iozzia L, Cerina L, Mainardi L. Relationships between heart-rate variability and pulse-rate variability obtained from video-PPG signal using ZCA. Physiol Meas 2016;37(11):1934-44.

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The Journal of Medical University-Plovdiv

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