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Evaluation of Wrist-Worn Photoplethysmography Trackers with an Electrocardiogram in Patients with Ischemic Heart Disease: A Validation Study

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Abstract

Purpose

Photoplethysmography measurement of heart rate with wrist-worn trackers has been introduced in healthy individuals. However, additional consideration is necessary for patients with ischemic heart disease, and the available evidence is limited. The study aims to evaluate the validity and reliability of heart rate measures by a wrist-worn photoplethysmography (PPG) tracker compared to an electrocardiogram (ECG) during incremental treadmill exercise among patients with ischemic heart disease.

Methods

Fifty-one participants performed the standard incremental treadmill exercise in a controlled laboratory setting with 12-lead ECG attached to the patient's body and wearing wrist-worn PPG trackers.

Results

At each stage, the absolute percentage error of the PPG was within 10% of the standard acceptable range. Further analysis using a linear mixed model, which accounts for individual variations, revealed that PPG yielded the best performance at the baseline low-intensity exercise. As the stages progressed, heart rate validity decreased but was regained during recovery. The reliability was moderate to excellent.

Conclusions

Low-cost trackers AMAZFIT Cor and Bip validity and reliability were within acceptable ranges, especially during low-intensity exercise among patients with ischemic heart disease recovering from cardiac procedures. Though using the tracker as part of the diagnosis tool still requires more supporting studies, it can potentially be used as a self-monitoring tool with precautions.

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References

  1. Paxton, M. Wearable Tech Fitness trackers on the rebound. 2020.

  2. International Data Corporation. Shipments of Wearable Devices Reach 118.9 Million Units in the Fourth Quarter and 336.5 Million for 2019. Retrieved from https://www.idc.com/getdoc.jsp?containerId=prUS46122120

  3. Research, G.V. Wearable Technology Market Size, Share & Trends Analysis Report By Product (Head & Eyewear, Wristwear), By Application (Consumer Electronics, Healthcare), By Region (Asia Pacific, Europe), And Segment Forecasts, 2023-2030. 2023.

  4. Thompson, W. R. Worldwide survey of fitness trends for 2020. ACSM’s Health Fitness J. 23(6):45, 2019.

    Article  Google Scholar 

  5. Allen, J. Photoplethysmography and its application in clinical physiological measurement. Physiol. Meas. 28(3):R1-39, 2007.

    Article  ADS  PubMed  Google Scholar 

  6. Plews, D. J., et al. Comparison of heart-rate-variability recording with smartphone photoplethysmography, polar H7 chest strap, and electrocardiography. Int. J. Sports Physiol. Perform. 12(10):1324–1328, 2017.

    Article  PubMed  Google Scholar 

  7. Jachymek, M., et al. Wristbands in home-based rehabilitation: validation of heart rate measurement. Sensors. 2022. https://doi.org/10.3390/s22010060.

    Article  Google Scholar 

  8. Winzer Ephraim, B., F. Woitek, and A. Linke. Physical activity in the prevention and treatment of coronary artery disease. J. Am. Heart Assoc. 7(4):007725, 2018.

    Google Scholar 

  9. McMahon, S. R., P. A. Ades, and P. D. Thompson. The role of cardiac rehabilitation in patients with heart disease. Trends Cardiovasc. Med. 27(6):420–425, 2017.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Van Iterson, E. H., et al. Cardiac rehabilitation is essential in the COVID-19 era: delivering uninterrupted heart care based on the cleveland clinic experience. J. Cardiopulm. Rehabil. Prev. 41(2):88–92, 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Wongvibulsin, S., et al. Digital health interventions for cardiac rehabilitation: systematic literature review. J. Med. Internet Res. 23(2):e18773, 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Batalik, L., et al. Benefits and effectiveness of using a wrist heart rate monitor as a telerehabilitation device in cardiac patients: A randomized controlled trial. Medicine (Baltimore). 99(11):e19556, 2020.

    Article  PubMed  Google Scholar 

  13. Sapra, A., A. Malik, and P. Bhandari. Vital Sign Assessment, in StatPearls. 2022, StatPearls Publishing Copyright © 2022, StatPearls Publishing LLC.: Treasure Island (FL).

  14. Munos, B., et al. Mobile health: the power of wearables, sensors, and apps to transform clinical trials. Ann. N. Y. Acad. Sci. 1375(1):3–18, 2016.

    Article  ADS  PubMed  Google Scholar 

  15. Germini, F., et al. Accuracy and acceptability of wrist-wearable activity-tracking devices: systematic review of the literature. J. Med. Internet Res. 24(1):e30791, 2022.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Fuller, D., et al. Reliability and validity of commercially available wearable devices for measuring steps, energy expenditure, and heart rate: systematic review. JMIR Mhealth Uhealth. 8(9):e18694, 2020.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Force, U. P. S. T. Screening for cardiovascular disease risk with electrocardiography: US preventive services task force recommendation statement. JAMA. 319(22):2308–2314, 2018.

    Article  Google Scholar 

  18. Jeet. Amazfit beats Huawei to become the third-largest smartwatch brand globally. 2021; Available from: https://www.gizmochina.com/2021/11/30/amazfit-becomes-third-largest-smartwatch-brand/.

  19. Cupertino, Amazfit Ranked Third in Global Smartwatch Shipments in Q3 2021. 2021.

  20. Zhang, S., et al. The auxiliary diagnostic value of a novel wearable electrocardiogram-recording system for arrhythmia detection: diagnostic trial. Front Med (Lausanne). 8:685999, 2021.

    Article  PubMed  Google Scholar 

  21. Düking, P., et al. Behavior change techniques in wrist-worn wearables to promote physical activity: content analysis. JMIR Mhealth Uhealth. 8(11):e20820, 2020.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Chen, E., et al. A new smart wristband equipped with an artificial intelligence algorithm to detect atrial fibrillation. Heart Rhythm. 17(5):847–853, 2020.

    Article  PubMed  Google Scholar 

  23. Rozanski, G. M., et al. Consumer wearable devices for activity monitoring among individuals after a stroke: a prospective comparison. JMIR Cardio. 2(1):e1, 2018.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Sprint, G., et al. Analyzing sensor-based time series data to track changes in physical activity during inpatient rehabilitation. Sensors (Basel). 17(10):48, 2017.

    Article  Google Scholar 

  25. Falter, M., et al. Accuracy of apple watch measurements for heart rate and energy expenditure in patients with cardiovascular disease: cross-sectional study. JMIR mHealth uHealth. 7(3):e11889–e11889, 2019.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Etiwy, M., et al. Accuracy of wearable heart rate monitors in cardiac rehabilitation. Cardiovasc Diagn Ther. 9(3):262–271, 2019.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Mühlen, J. M., et al. Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network. Br. J. Sports Med. 55(14):767, 2021.

    Article  PubMed  Google Scholar 

  28. O’Driscoll, R., et al. The validity of two widely used commercial and research-grade activity monitors, during resting, household and activity behaviours. Health Technol. 10(3):637–648, 2020.

    Article  Google Scholar 

  29. Shumate, T., et al. Validity of the Polar Vantage M watch when measuring heart rate at different exercise intensities. PeerJ. 9:e10893, 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Fan, Y. Y., et al. Diagnostic performance of a smart device with photoplethysmography technology for atrial fibrillation detection: pilot study (Pre-mAFA II registry). JMIR Mhealth Uhealth. 7(3):e11437, 2019.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Inui, T., et al. Use of a smart watch for early detection of paroxysmal atrial fibrillation: validation study. JMIR Cardio. 4(1):e14857, 2020.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Kooiman, T. J. M., et al. Reliability and validity of ten consumer activity trackers. BMC Sports Sci. Med. Rehabil. 7:24, 2015. https://doi.org/10.1186/s13102-015-0018-5.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Shcherbina, A., et al. Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort. J. Person. Med. 7(2):48, 2017.

    Article  Google Scholar 

  34. Gordon, W. J., and R. S. Rudin. Why APIs? Anticipated value, barriers, and opportunities for standards-based application programming interfaces in healthcare: perspectives of US thought leaders. JAMIA Open. 5(2):023, 2022.

    Article  Google Scholar 

  35. Dullabh, P., et al. Application programming interfaces in health care: findings from a current-state sociotechnical assessment. Appl. Clin. Inform. 11(1):59–69, 2020.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Thiebaud, R. S., et al. Validity of wrist-worn consumer products to measure heart rate and energy expenditure. Digital Health. 4:2055207618770322, 2018.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Harb, S. C., et al. Prognostic value of functional capacity in different exercise protocols. J. Am. Heart Assoc. 9(13):e015986, 2020.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Fitzpatrick, T. B. The validity and practicality of sun-reactive skin types I through VI. Arch. Dermatol. 124(6):869–871, 1988.

    Article  CAS  PubMed  Google Scholar 

  39. MD-Isa, Z., et al. The reliability of Fitzpatrick Skin Type Chart Comparing to Mexameter (Mx 18) in measuring skin color among first trimester pregnant mothers in Petaling District Malaysia. . Malays. J. Public Health Med. 16:59–65, 2016.

    Google Scholar 

  40. Meteyard, L., and R. A. I. Davies. Best practice guidance for linear mixed-effects models in psychological science. J. Mem. Language. 112:104092, 2020.

    Article  Google Scholar 

  41. Liljequist, D., B. Elfving, and K. S. Roaldsen. Intraclass correlation: a discussion and demonstration of basic features. PLoS ONE. 14(7):0219854, 2019.

    Article  Google Scholar 

  42. Portney, L.G. and M.P. Watkins. Foundations of clinical research: applications to practice. Vol. 892. 2009: Pearson/Prentice Hall Upper Saddle River, NJ.

  43. Chen, G., et al. Intraclass correlation: Improved modeling approaches and applications for neuroimaging. Hum. Brain Map. 39(3):1187–1206, 2018.

    Article  Google Scholar 

  44. Taylor, J. L., A. R. Bonikowske, and T. P. Olson. Optimizing outcomes in cardiac rehabilitation: the importance of exercise intensity. Front. Cardiovasc. Med. 8:734278, 2021.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Dooley, E. E., N. M. Golaszewski, and J. B. Bartholomew. Estimating accuracy at exercise intensities: a comparative study of self-monitoring heart rate and physical activity wearable devices. JMIR Mhealth Uhealth. 5(3):e34, 2017.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Gillinov, A. M., et al. Variable accuracy of commercially available wearable heart rate monitors. J. Am. Coll. Cardiol. 69(11):336, 2017.

    Article  Google Scholar 

  47. Kobayashi, M., T. Shinohara, and S. Usuda. Accuracy of wrist-worn heart rate monitors during physical therapy sessions among hemiparetic inpatients with stroke. J. Phys. Therapy Sci. 33(1):45–51, 2021.

    Article  Google Scholar 

  48. Jachymek, M., et al. Wristbands in home-based rehabilitation-validation of heart rate measurement. Sensors (Basel). 22(1):7, 2021.

    Article  Google Scholar 

  49. Chow, H. W., and C. C. Yang. Accuracy of optical heart rate sensing technology in wearable fitness trackers for young and older adults: validation and comparison study. JMIR Mhealth Uhealth. 8(4):e14707, 2020.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Fokkema, T., et al. Reliability and validity of ten consumer activity trackers depend on walking speed. Med Sci Sports Exerc. 49(4):793–800, 2017.

    Article  PubMed  Google Scholar 

  51. Nelson, M. B., et al. Validity of consumer-based physical activity monitors for specific activity types. Med. Sci. Sports Exerc. 48(8):1619–1628, 2016.

    Article  PubMed  Google Scholar 

  52. Chowdhury, E. A., et al. Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors. PLoS ONE. 12(2):e0171720, 2017.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Hoevenaars, D., et al. Accuracy of heart rate measurement by the fitbit charge 2 during wheelchair activities in people with spinal cord injury: instrument validation study. JMIR Rehabil. Assist. Technol. 9(1):e27637, 2022.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Nelson, B. W., and N. B. Allen. Accuracy of consumer wearable heart rate measurement during an ecologically valid 24-hour period: intraindividual validation study. JMIR Mhealth Uhealth. 7(3):e10828, 2019.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Sjöberg, V., et al. Wrist-worn activity trackers in laboratory and free-living settings for patients with chronic pain: criterion validity study. JMIR Mhealth Uhealth. 9(1):e24806, 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Bent, B., et al. Investigating sources of inaccuracy in wearable optical heart rate sensors. NPJ. Digital Med. 3(1):18, 2020.

    Article  Google Scholar 

  57. Alzahrani, A., et al. A multi-channel opto-electronic sensor to accurately monitor heart rate against motion artefact during exercise. Sensors (Basel, Switzerland). 15(10):25681–25702, 2015.

    Article  ADS  PubMed  Google Scholar 

  58. Sartor, F., et al. Wrist-worn optical and chest strap heart rate comparison in a heterogeneous sample of healthy individuals and in coronary artery disease patients. BMC Sports Sci. Med. Rehabil. 10(1):10, 2018.

    Article  MathSciNet  PubMed  PubMed Central  Google Scholar 

  59. Gillinov, S., et al. Variable accuracy of wearable heart rate monitors during aerobic exercise. Med. Sci. Sports Exerc. 49(8):1697–1703, 2017.

    Article  PubMed  Google Scholar 

  60. Wang, R., et al. Accuracy of wrist-worn heart rate monitors. JAMA Cardiol. 2(1):104–106, 2017.

    Article  PubMed  Google Scholar 

  61. Bunn, J. A., et al. Current state of commercial wearable technology in physical activity monitoring 2015–2017. Int. J. Exercise Sci. 11(7):503–515, 2018.

    Google Scholar 

  62. Stone, J. D., et al. Assessing the accuracy of popular commercial technologies that measure resting heart rate and heart rate variability. Front. Sports Act. Living. 3:585870, 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Nelson, B. W., et al. Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research. NPJ Digital Med. 3(1):90, 2020.

    Article  Google Scholar 

  64. Spadaccio, C., and U. Benedetto. Coronary artery bypass grafting (CABG) vs percutaneous coronary intervention (PCI) in the treatment of multivessel coronary disease: quo vadis? -a review of the evidences on coronary artery disease. Ann. Cardiothorac. Surg. 7(4):506–515, 2018.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Stahl, S. E., et al. How accurate are the wrist-based heart rate monitors during walking and running activities? Are they accurate enough? BMJ Open Sport Exercise Med. 2(1):e000106, 2016.

    Article  Google Scholar 

  66. Boudreaux, B. D., et al. Validity of wearable activity monitors during cycling and resistance exercise. Med. Sci. Sports Exercise. 50(3):8, 2018.

    Article  Google Scholar 

  67. Jo, E., et al. Validation of biofeedback wearables for photoplethysmographic heart rate tracking. J. Sports Sci. Med. 15(3):540–547, 2016.

    PubMed  PubMed Central  Google Scholar 

  68. Dondzila, C. J., et al. Congruent accuracy of wrist-worn activity trackers during controlled and free-living conditions. Int. J. Exercise Sci. 11:575–584, 2018.

    Google Scholar 

  69. Hannan, M., et al. Behavioral medicine for sedentary behavior, daily physical activity, and exercise to prevent cardiovascular disease: a review. Curr. Atheroscler. Rep. 23(9):48, 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Wallen, M. P., et al. Accuracy of heart rate watches: implications for weight management. PLoS ONE. 11(5):e0154420, 2016.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Degroote, L., et al. Low-cost consumer-based trackers to measure physical activity and sleep duration among adults in free-living conditions: validation study. JMIR Mhealth Uhealth, 8(5):e16674, 2020.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Delgado-Gonzalo, R., et al. Evaluation of accuracy and reliability of PulseOn optical heart rate monitoring device. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2015:430–433, 2015.

    PubMed  Google Scholar 

  73. Tang, M. S. S., et al. Effectiveness of Wearable trackers on physical activity in healthy adults: systematic review and meta-analysis of randomized controlled trials. JMIR mHealth and uHealth. 8(7):e15576–e15576, 2020.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Dagan, A., and O. J. Mechanic. Use of ultra-low cost fitness trackers as clinical monitors in low resource emergency departments. Clin. Exp. Emergency Med. 7(3):144–149, 2020.

    Article  Google Scholar 

  75. Bai, Y., et al. Comparative evaluation of heart rate-based monitors: apple watch vs fitbit charge HR. J. Sports Sci. 36(15):1734–1741, 2018.

    Article  PubMed  Google Scholar 

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Acknowledgements

The study was partially funded by a Research Grant from the Universiti Malaya (RF009C-2018). Any other parties provided no other grants or funds. Special thanks to all the participants from the Universiti Malaya Medical Centre (UMMC) Rehabilitation Medicine Clinic and the UMMC Stress Test Lab physicians and technicians for their assistance in data collection.

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AS, RS, WLL, and NSI have contributed substantially to the research design, NSI collecting of the data, NSI and RS analyzing and interpreting the data. NSI and EWP have participated in drafting the manuscript. All authors have read and approved the final version.

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Correspondence to Sanjay Rampal or Anwar Suhaimi.

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Associate Editor Christian Zemlin oversaw the review of this article.

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Ibrahim, N.S., Rampal, S., Lee, W.L. et al. Evaluation of Wrist-Worn Photoplethysmography Trackers with an Electrocardiogram in Patients with Ischemic Heart Disease: A Validation Study. Cardiovasc Eng Tech 15, 12–21 (2024). https://doi.org/10.1007/s13239-023-00693-z

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