Skip to main content

Advertisement

SpringerLink
Log in

Wearing Your Heart on Your Sleeve: the Future of Cardiac Rhythm Monitoring

  • Invasive Electrophysiology and Pacing (EK Heist, Section Editor)
  • Published:
Current Cardiology Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

This review describes the novel category of wearable ECG monitors and identifies where patients, healthcare providers, and device manufacturers should focus efforts to maximize the clinical benefit of these devices.

Recent Findings

Notable wearable ECG monitors include the AliveCor Kardia devices, Apple Watch Series 4, and several others. The most common use case is monitoring for atrial fibrillation. The available evidence validates the ability of the Kardia devices and Apple Watch to distinguish atrial fibrillation from sinus rhythm. Key questions for manufacturers include how to calibrate each device’s algorithms and streamline workflows for healthcare providers.

Summary

Wearable ECG monitors are currently most useful to detect atrial fibrillation. Further study is needed to demonstrate whether wearable ECG monitors improve patient outcomes, and to expand their use into other indications. Device manufacturers and healthcare providers must work together to establish new workflows to process and act on wearable ECG data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Gates B, Myhrvold N, Rinearson P. The road ahead: Viking Press; 1995.

  2. Apple Watch Series 4 Health [Internet]. Apple. [cited 2019 May 2]. Available from: https://www.apple.com/apple-watch-series-4/health/.

  3. KardiaBand [Internet]. AliveCor. [cited 2019 May 2]. Available from: https://store.alivecor.com/products/kardiaband.

  4. KardiaMobile [Internet]. AliveCor. [cited 2019 May 2]. Available from: https://store.alivecor.com/products/kardiamobile.

  5. QardioCore [Internet]. GetQardio [cited 2019 May 2]. Available from: https://www.getqardio.com/qardiocore-wearable-ecg-ekg-monitor-iphone/.

  6. Hexoskin [Internet]. Hexoskin. [cited 2019 May 2]. Available from: https://www.hexoskin.com.

  7. Withings Move ECG [Internet]. Withings. [cited 2019 May 2]. Available from: https://www.withings.com/us/en/move-ecg?gclid=EAIaIQobChMI6-ju_7_94QIVg0wNCh1ghQKnEAAYASAAEgLzRfD_BwEgclsrc=aw.ds.

  8. Introducing Verily Study Watch [Internet]. Verily Blog. 2017 [cited 2019 May 16]. Available from: https://blog.verily.com/2017/04/introducing-verily-study-watch.html.

  9. New Health Band Takes ECG Tracking to Heart [Internet]. Amazfit Blog. 2017 [cited 2019 May 2]. Available from: https://us.amazfit.com/blog/health-band.

  10. KardiaAI 510(k) Notification K181823 [Internet]. Food and Drug Administration; 2019 [cited 2019 Jun 15]. Available from: https://www.accessdata.fda.gov/cdrh_docs/pdf18/K181823.pdf.

  11. Kardia Band System 510(k) Notification K171816 [Internet]. Food and Drug Administration; 2017 [cited 2019 Jun 15]. Available from: https://www.accessdata.fda.gov/cdrh_docs/pdf17/K171816.pdf.

  12. AliveCor Heart Monitor 510(k) Premarket Notification K142743 [Internet]. Food and Drug Administration; 2014 [cited 2019 Jun 15]. Available from: https://www.accessdata.fda.gov/cdrh_docs/pdf14/K142743.pdf.

  13. De Novo classification request for ECG App DEN180044 [Internet]. Food and Drug Administration; 2018 [cited 2019 May 27]. Available from: https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN180044.pdf.

  14. De Novo classification request for irregular rhythm notification feature DEN180042 [Internet]. Food and Drug Administration; 2018 [cited 2019 May 27]. Available from: https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN180042.pdf.

  15. KardiaMobile 6L [Internet]. AliveCor. [cited 2019 May 20]. Available from: https://www.alivecor.com/kardiamobile6l/.

  16. CALM-M for healthcare [Internet]. CALM Health. [cited 2019 May 16]. Available from: https://www.calm-health.com/calm-healthcare/.

  17. HeartBit - technology [Internet]. HeartBit. [cited 2019 May 16]. Available from: https://theheartbit.com/technology/.

  18. Revolutionary solution for exercise ECG detection [Internet]. Heartbit; 2018 [cited 2019 Jun 15]. Available from: https://drive.google.com/drive/folders/1TtJqy593UTSGUXS7UFETNgrFh1SiXC4e.

  19. Study Watch Traditional 510(k) Premarket Notification K182456 [Internet]. Food and Drug Administration; 2019 [cited 2019 May 26]. Available from: http://www.accessdata.fda.gov/cdrh_docs/pdf18/K182456.pdf.

  20. Triangle System 510(k) Premarket notification K142743 [Internet]. Food and Drug Administration; 2019 [cited 2019 Jun 15]. Available from: https://www.accessdata.fda.gov/cdrh_docs/pdf18/K183319.pdf.

  21. Christensen CM. The innovators dilemma: when new technologies cause great firms to fail: Harvard Business Review Press; 2013.

  22. Heart rate notifications on your Apple Watch [Internet]. Apple Support. [cited 2019 May 2]. Available from: https://support.apple.com/en-us/HT208931.

  23. Overview of device regulation [Internet]. US Food and Drug Administration. [cited 2019 Jun 28]. Available from: https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/overview-device-regulation.

  24. US Preventive Services Task Force, Curry SJ, Krist AH, Owens DK, Barry MJ, Caughey AB, et al. Screening for atrial fibrillation with electrocardiography: US Preventive Services Task Force recommendation statement. JAMA. 2018;320:478.

    Article  Google Scholar 

  25. Kirchhof P, Benussi S, Kotecha D, Ahlsson A, Atar D, Casadei B, et al. 2016 ESC guidelines for the management of atrial fibrillation developed in collaboration with EACTS. Eur Heart J. 2016;37:2893–962.

    Article  Google Scholar 

  26. Tarakji KG, Wazni OM, Callahan T, Kanj M, Hakim AH, Wolski K, et al. Using a novel wireless system for monitoring patients after the atrial fibrillation ablation procedure: the iTransmit study. Heart Rhythm. 2015;12:554–9.

    Article  Google Scholar 

  27. Chung EH, Guise KD. QTC intervals can be assessed with the AliveCor heart monitor in patients on dofetilide for atrial fibrillation. J Electrocardiol. 2015;48:8–9.

    Article  Google Scholar 

  28. Turakhia MP, Perez MV. Results of a large-scale, App-based study to identify atrial fibrillation using a smartwatch: the Apple Heart Study. Oral session presented at: American College of Cardiology Scientific Sessions 2019. 2019 Mar 16–18. New Orleans, LA.

  29. Lau JK, Lowres N, Neubeck L, Brieger DB, Sy RW, Galloway CD, et al. iPhone ECG application for community screening to detect silent atrial fibrillation: a novel technology to prevent stroke. Int J Cardiol. 2013;165:193–4.

    Article  Google Scholar 

  30. William AD, Kanbour M, Callahan T, Bhargava M, Varma N, Rickard J, et al. Assessing the accuracy of an automated atrial fibrillation detection algorithm using smartphone technology: the iREAD study. Heart Rhythm. 2018;15:1561–5.

    Article  Google Scholar 

  31. • Koshy AN, Sajeev JK, Negishi K, Wong MC, Pham CB, Cooray SP, et al. Accuracy of blinded clinician interpretation of single-lead smartphone electrocardiograms and a proposed clinical workflow. Am Heart J. 2018;205:149–53 This study compared the test characteristics of the AliveCor rhythm classification algorithm to interpretation of single-lead AliveCor tracings by primary care providers and electrophysiologists in a sample of 100 individuals undergoing cardioversion with gold-standard 12-lead ECGs. The study demonstrated that supplementing device algorithms with physician interpretation improves AF detection over either alone.

    Article  Google Scholar 

  32. Desteghe L, Raymaekers Z, Lutin M, Vijgen J, Dilling-Boer D, Koopman P, et al. Performance of handheld electrocardiogram devices to detect atrial fibrillation in a cardiology and geriatric ward setting. Europace. 2016;19:29–39.

    PubMed  Google Scholar 

  33. Brasier N, Raichle CJ, Dörr M, Becke A, Nohturfft V, Weber S, et al. Detection of atrial fibrillation with a smartphone camera: first prospective, international, two-centre, clinical validation study (DETECT AF PRO). EP Europace. 2019;21:41–7.

    Article  Google Scholar 

  34. Lowres N, Neubeck L, Salkeld G, Krass I, McLachlan AJ, Redfern J, et al. Feasibility and cost-effectiveness of stroke prevention through community screening for atrial fibrillation using iPhone ECG in pharmacies. Thromb Haemost. 2014;111:1167–76.

    Article  CAS  Google Scholar 

  35. Using Apple Watch for arrhythmia detection December 2018 [Internet]. 2018 [cited 2019 May 16]. Available from: https://www.apple.com/healthcare/site/docs/Apple_Watch_Arrhythmia_Detection.pdf.

  36. Bumgarner JM, Lambert CT, Hussein AA, Cantillon DJ, Baranowski B, Wolski K, et al. Smartwatch algorithm for automated detection of atrial fibrillation. J Am Coll Cardiol. 2018;71:2381–8.

    Article  Google Scholar 

  37. • Wasserlauf J, You C, Patel R, Valys A, Albert D, Passman R. Smartwatch performance for the detection and quantification of atrial fibrillation. Circulation: Arrhythmia and Electrophysiology [Internet]. 2019 [cited 2019 May 29];12. Available from: https://www.ahajournals.org/doi/10.1161/CIRCEP.118.006834 This study compared the KardiaBand device to conventional implantable cardiac monitors in 24 patients with paroxysmal AF, finding that the KardiaBand is highly sensitive for detecting episodes of AF lasting more than 1 h. The results suggest that wearable devices may be useful for long-term noninvasive monitoring for AF.

  38. Chan P-H, Wong C-K, Pun L, Wong Y-F, Wong MM-Y, Chu DW-S, et al. Head-to-head comparison of the AliveCor heart monitor and microlife WatchBP office AFIB for atrial fibrillation screening in a primary care setting. Circulation. 2017;135:110–2.

    Article  Google Scholar 

  39. Alonso A, Roetker NS, Soliman EZ, Chen LY, Greenland P, Heckbert SR. Prediction of atrial fibrillation in a racially diverse cohort: the Multi-Ethnic Study of Atherosclerosis (MESA). J Am Heart Assoc. 2016;5.

  40. FDA permits marketing of artificial intelligence-based device to detect certain diabetes-related eye problems [Internet]. FDA Newsroom. 2018. Available from: https://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm604357.htm.

  41. Kapoor A, Amroze A, Golden J, Crawford S, O’Day K, Elhag R, et al. SUPPORT-AF: piloting a multi-faceted, electronic medical record-based intervention to improve prescription of anticoagulation. J Am Heart Assoc [Internet]. 2018 [cited 2019 Jun 28];7. Available from: https://www.ahajournals.org/doi/10.1161/JAHA.118.009946.

  42. Lip GYH, Nieuwlaat R, Pisters R, Lane DA, Crijns HJGM. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach. Chest. 2010;137:263–72.

    Article  Google Scholar 

  43. Pisters R, Lane DA, Nieuwlaat R, de Vos CB, Crijns HJGM, Lip GYH. A novel user-friendly score (HAS-BLED) to assess 1-year risk of major bleeding in patients with atrial fibrillation: the Euro Heart Survey. Chest. 2010;138:1093–100.

    Article  Google Scholar 

  44. Institutions that support health records on iPhone (beta) [Internet]. Apple Support. 2019 [cited 2019 May 16]. Available from: https://support.apple.com/en-us/HT208647.

  45. VA to provide capability for veterans to access their VA health data on Apple iPhones [Internet]. U.S. Department of Veteran Affairs News Releases. 2019 [cited 2019 May 16]. Available from: https://www.va.gov/opa/pressrel/pressrelease.cfm?id=5199.

  46. Fitbit and Google announce collaboration to accelerate innovation in digital health and wearables [Internet]. Fitbit Press Releases. 2018 [cited 2019 Jun 28]. Available from: https://investor.fitbit.com/press/press-releases/press-release-details/2018/Fitbit-and-Google-Announce-Collaboration-to-Accelerate-Innovation-in-Digital-Health-and-Wearables/default.aspx.

  47. AMA, Google launch health care interoperability & innovation challenge [Internet]. AMA Press Releases. 2018 [cited 2019 Jun 28]. Available from: https://www.ama-assn.org/press-center/press-releases/ama-google-launch-health-care-interoperability-innovation-challenge.

  48. KardiaPro [Internet]. AliveCor. [cited 2019 May 2]. Available from: https://clinicians.alivecor.com.

  49. QardioMD [Internet]. GetQardio. [cited 2019 May 2]. Available from: https://www.getqardio.com/qardiomd-heart-health/.

  50. Bogun F, Anh D, Kalahasty G, Wissner E, Bou Serhal C, Bazzi R, et al. Misdiagnosis of atrial fibrillation and its clinical consequences. Am J Med. 2004;117:636–42.

    Article  Google Scholar 

  51. Welton NJ, McAleenan A, Thom HH, Davies P, Hollingworth W, Higgins JP, et al. Screening strategies for atrial fibrillation: a systematic review and cost-effectiveness analysis. Health Technol Assess. 2017;21:1–236.

    Article  Google Scholar 

  52. Turakhia MP, Desai M, Hedlin H, Rajmane A, Talati N, Ferris T, et al. Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: the Apple Heart Study. Am Heart J. 2019;207:66–75.

    Article  Google Scholar 

  53. Tison GH, Sanchez JM, Ballinger B, Singh A, Olgin JE, Pletcher MJ, et al. Passive detection of atrial fibrillation using a commercially available smartwatch. JAMA Cardiol. 2018;3:409–16.

    Article  Google Scholar 

  54. The HEARTLINE Study [Internet]. The HEARTLINE Study. 2019 [cited 2019 May 16]. Available from: https://www.heartline.com.

  55. •• Halcox JPJ, Wareham K, Cardew A, Gilmore M, Barry JP, Phillips C, et al. Assessment of remote heart rhythm sampling using the AliveCor heart monitor to screen for atrial fibrillation: The REHEARSE-AF Study. Circulation. 2017;136:1784–94 This randomized controlled trial compared screening with intermittent twice weekly handheld AliveCor Kardia ECGs for 12 months to usual care, and found that intermittent screening was more likely to detect incident AF in patients ≥ 65 years of age. It also estimated cost-effectiveness of such ambulatory screening, suggesting a cost per diagnosis of $10,780.

    Article  Google Scholar 

  56. Hickey KT, Hauser NR, Valente LE, Riga TC, Frulla AP, Creber RM, Whang W, Garan H, Jia H, Sciacca RR, Wang DY A single-center randomized, controlled trial investigating the efficacy of a mHealth ECG technology intervention to improve the detection of atrial fibrillation: the iHEART study protocol. BMC Cardiovasc Disord [Internet]. 2016 [cited 2019 Mar 5];16. Available from: http://bmccardiovascdisord.biomedcentral.com/articles/10.1186/s12872-016-0327-y

  57. Muhlestein JB, Le V, Albert D, Moreno FL, Anderson JL, Yanowitz F, et al. Smartphone ECG for evaluation of STEMI: results of the ST LEUIS Pilot Study. J Electrocardiol. 2015;48:249–59.

    Article  Google Scholar 

  58. Galloway CD, Valys AV, Shreibati JB, Treiman DL, Petterson FL, Gundotra VP, et al. Development and validation of a deep-learning model to screen for hyperkalemia from the electrocardiogram. JAMA Cardiology [Internet]. 2019 [cited 2019 May 6]; Available from: http://cardiology.jamanetwork.com/article.aspx?doi=10.1001/jamacardio.2019.0640.

  59. Medicare Program; Revisions to payment policies under the physician fee schedule and other revisions to part B for CY 2019; Medicare Shared Savings program Requirements; Quality Payment Program; Medicaid Promoting Interoperability Program; Quality Payment Program--extreme and uncontrollable circumstance policy for the 2019 MIPS payment year; provisions from the Medicare Shared Savings Program--accountable care organizations--pathways to success; and expanding the use of telehealth services for the treatment of opioid use disorder under the substance use-disorder prevention that promotes opioid recovery and treatment (SUPPORT) for patients and communities act [internet]. Centers for Medicare & Medicaid Services; 2018 Nov. Available from: https://s3.amazonaws.com/public-inspection.federalregister.gov/2018-24170.pdf.

  60. Thornton RG. The learned intermediary doctrine and its effects on prescribing physicians. Proc (Bayl Univ Med Cent). 2003;16:359–61.

    Article  Google Scholar 

  61. Sullivan HR, Schweikart SJ. Are current tort liability doctrines adequate for addressing injury caused by AI? AMA J Ethics. 2019;21:E160–6.

Download references

Acknowledgments

We are grateful to Daniel B. Kramer, MD, MPH, for critical review of the manuscript.

Funding

David McManus is supported by NIH grants R01HL126911, R01HL137734, R01HL137794, R01HL13660, R01HL141434, and U54HL143541.

Steven A. Lubitz is supported by NIH grant 1R01HL139731 and American Heart Association 18SFRN34250007.

Eric Ding is supported by a grant from the National Heart, Lung, Blood Institute (Grant #5T32HL120823).

Author information

Authors and Affiliations

  1. Department of Internal Medicine, Massachusetts General Hospital, Boston, MA, USA

    Mostafa A. Al-Alusi

  2. Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA

    Eric Ding

  3. Division of Cardiovascular Medicine, Department of Medicine and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA

    David D. McManus

  4. Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Simches Research Building, 185 Cambridge Street 3.188, Boston, MA, 02114, USA

    Steven A. Lubitz

Authors
  1. Mostafa A. Al-Alusi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eric Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David D. McManus
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Steven A. Lubitz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Steven A. Lubitz.

Ethics declarations

Conflict of Interest

Mostafa A. Al-Alusi and Eric Ding declare that they have no conflict of interest.

David McManus has received research support from Apple Computer, Bristol-Myers Squibb, Boehringher-Ingelheim, Flexcon, Fitbit Heart Rhythm Society, Pfizer, Samsung, Philips Healthcare, Biotronik, and has received consultancy fees or honoraria from Bristol-Myers Squibb, Pfizer, Flexcon, Boston Biomedical Associates, Samsung, and Rose Consulting.

Steven A. Lubitz receives sponsored research support from Bristol Myers Squibb / Pfizer, Bayer AG, and Boehringer Ingelheim, and has consulted for Bristol Myers Squibb / Pfizer and Bayer AG.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Invasive Electrophysiology and Pacing

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Al-Alusi, M.A., Ding, E., McManus, D.D. et al. Wearing Your Heart on Your Sleeve: the Future of Cardiac Rhythm Monitoring. Curr Cardiol Rep 21, 158 (2019). https://doi.org/10.1007/s11886-019-1223-8

Download citation

  • Published:

  • DOI: https://doi.org/10.1007/s11886-019-1223-8

Keywords

Search

Navigation