AI-Enabled Smart Watch Detection of Cardiac Arrest: A Review

Authors

  • April Liao

DOI:

https://doi.org/10.61173/b88xks63

Keywords:

Cardiac Arrest, AI, Smart Watches

Abstract

Cardiac arrest is a common cause of death, with a high mortality rate if it occurs outside of hospitals and does not receive immediate care. This paper explored the possibilities of using the widespread technology, smart watches, in the detection of cardiac arrest, with the assistance of AI and deep learning algorithms. After understanding cardiac arrest and the electrocardiogram (ECG) waves for diagnosis, current smart watch technology is more focused on other ECG readings, and despite its accuracy, it cannot support the detection of cardiac arrest. However, with the use of deep learning and generative AI, the potential of early onset cardiac arrest detection seems to be likely in the near future. Currently, smart watches are capable of capturing 3-lead ECG readings, as well as precordial ECG diagrams. With further research in AI training and hardware upgrades, early onset cardiac arrest detection is possible, and could help save many lives from cardiac arrest.

References

[1] U.S. Environmental Protection Agency. Health Status. Report on the Environment. Updated July 25, 2025. https://www.epa. gov/report-environment/health-status (accessed August 14, 2025).

[2] American Heart Association. More than half of U.S. adults don’t know heart disease is leading cause of death, despite 100- year reign. American Heart Association Newsroom. Published January 24, 2024. https://newsroom.heart.org/news/more-thanhalf-of-u-s-adults-dont-know-heart-disease-is-leading-cause-ofdeath-despite-100-year-reign (accessed August 14, 2025).

[3] Patel, K.; Hipskind, J. E. Cardiac Arrest. In StatPearls [Internet]; StatPearls Publishing: Treasure Island (FL), 2025– . Updated April 7, 2023. https://www.ncbi.nlm.nih.gov/books/ NBK534866/ (accessed August 14, 2025).

[4] Sudden Cardiac Arrest Foundation. About Sudden Cardiac Arrest. Sudden Cardiac Arrest Foundation. https://www.scaaware.org/about-sca (accessed August 14, 2025). Dean&Francis ISSN 2959-409X

[5] National Heart, Lung, and Blood Institute. Study reveals wearable device trends among U.S. adults. NHLBI, NIH. Published June 15, 2023. https://www.nhlbi.nih.gov/news/2023/ study-reveals-wearable-device-trends-among-us-adults (accessed August 14, 2025).

[6] National Heart, Lung, and Blood Institute. What Is Cardiac Arrest? NHLBI, NIH. Updated May 19, 2022. https://www. nhlbi.nih.gov/health/cardiac-arrest (accessed August 14, 2025).

[7] Mayo Clinic Staff. Ventricular fibrillation - Diagnosis & treatment. Mayo Clinic. Updated October 28, 2022. https:// www.mayoclinic.org/diseases-conditions/ventricular-fibrillation/ diagnosis-treatment/drc-20364524 (accessed August 14, 2025).

[8] Whitaker, J.; Wright, M. J.; Tedrow, U. Diagnosis and Management of Ventricular Tachycardia. Clin. Med. (Lond.) 2023, 23 [5], 442–448. https://doi.org/10.7861/clinmed.2023- 23.5.Cardio3.

[9] Institute for Quality and Efficiency in Health Care (IQWiG). In brief: What is an electrocardiogram (ECG)? InformedHealth. org [Internet]. NCBI Bookshelf. https://www.ncbi.nlm.nih.gov/ books/NBK536878/ (accessed August 15, 2025).

[10] Pepplinkhuizen, S.; Hoeksema, W. F.; van der Stuijt, W.; van Steijn, N. J.; Winter, M. M.; Wilde, A. A. M.; Smeding, L.; Knops, R. E. Accuracy and clinical relevance of the single-lead Apple Watch electrocardiogram to identify atrial fibrillation. Cardiovasc. Digit. Health J. 2022, 3 (6 Suppl), S17–S22. https:// doi.org/10.1016/j.cvdhj.2022.10.004.

[11] Shahid, S.; Iqbal, M.; Saeed, H.; Hira, S.; Batool, A.; Khalid, S.; Tahirkheli, N. K. Diagnostic accuracy of Apple Watch electrocardiogram for atrial fibrillation: A systematic review and meta-analysis. JACC Adv. 2025, 4 [2], 101538. https://doi.org/10.1016/j.jacadv.2024.101538.

[12] Perez, M. V.; Mahaffey, K. W.; Hedlin, H.; Rumsfeld, J. S.; Garcia, A.; Ferris, T.; Balasubramanian, V.; Russo, A. M.; Rajmane, A.; Cheung, L.; Hung, G.; Lee, J.; Kowey, P.; Talati, N.; Nag, D.; Gummidipundi, S. E.; Beatty, A.; True Hills, M.; Desai, S.; Granger, C. B.; et al. Large-scale assessment of a smartwatch to identify atrial fibrillation. N. Engl. J. Med. 2019, 381 [20], 1909–1917. https://doi.org/10.1056/NEJMoa1901183.

[13] U.S. Census Bureau. Race and Ethnicity in the United States: 2010 Census and 2020 Census. Census Interactive Gallery. Published August 12, 2021; page last revised November 6, 2024. https://www.census.gov/library/visualizations/ interactive/race-and-ethnicity-in-the-united-state-2010-and- 2020-census.html (accessed August 16, 2025).

[14] Vyas, R.; Jain, S.; Thakre, A.; Thotamgari, S. R.; Raina, S.; Brar, V.; Sengupta, P.; Agrawal, P. Smart watch applications in atrial fibrillation detection: Current state and future directions. J. Cardiovasc. Electrophysiol. 2024, 35 [12], 2474–2482. https:// doi.org/10.1111/jce.16451.

[15] Fiorina, L.; Chemaly, P.; Cellier, J.; Ait Said, M.; Coquard, C.; Younsi, S.; Salerno, F.; Horvilleur, J.; Lacotte, J.; Manenti, V.; Plesse, A.; Henry, C.; Lefebvre, B. Artificial intelligence–based electrocardiogram analysis improves atrial arrhythmia detection from a smartwatch electrocardiogram. Eur. Heart J. Digit. Health 2024, 5 [5], 535–541. https://doi.org/10.1093/ehjdh/ztae047.

[16] Wegner, F. K.; Plagwitz, L.; Doldi, F.; Ellermann, C.; Willy, K.; Wolfes, J.; Sandmann, S.; Varghese, J.; Eckardt, L. Machine learning in the detection and management of atrial fibrillation. Clin. Res. Cardiol. 2022, 111, 1010–1017. https:// doi.org/10.1007/s00392-022-02012-3.

[17] Hannun, A. Y.; Rajpurkar, P.; Haghpanahi, M.; Tison, G. H.; Bourn, C.; Turakhia, M. P.; Ng, A. Y. Cardiologistlevel arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nat. Med. 2019, 25, 65–69. https://doi.org/10.1038/s41591-018-0268-3.

[18] Ploux, S.; Strik, M.; Caillol, T.; Ramirez, F. D.; Abu-Alrub, S.; Marchand, H.; Buliard, S.; Haïssaguerre, M.; Bordachar, P. Beyond the wrist: Using a smartwatch electrocardiogram to detect electrocardiographic abnormalities. Arch. Cardiovasc. Dis. 2022, 115 [1], 29–36. https://doi.org/10.1016/ j.acvd.2021.11.003.

[19] Guarnieri, G.; Mapelli, M.; Moltrasio, M.; Agostoni, P.; Tondo, C. Connected health: Ventricular tachycardia detection with Apple Watch–A case report. Heliyon 2024, 10 [23], e40595. https://doi.org/10.1016/j.heliyon.2024.e40595.

[20] Perino, A. C.; Gummidipundi, S. E.; Lee, J.; Hedlin, H.; Garcia, A.; Ferris, T.; Balasubramanian, V.; Gardner, R. M.; Cheung, L.; Hung, G.; Granger, C. B.; Kowey, P.; Rumsfeld, J. S.; Russo, A. M.; True Hills, M.; Talati, N.; Nag, D.; Tsay, D.; Desai, S.; Desai, M.; et al. Arrhythmias other than atrial fibrillation in those with an irregular pulse detected with a smartwatch: Findings from the Apple Heart Study. Circ. Arrhythm. Electrophysiol. 2021, 14 [10], e010063. https://doi. org/10.1161/CIRCEP.121.010063.

[21] Madona, P.; Basti, R. I.; Zain, M. M. PQRST wave detection on ECG signals. Gac. Sanit. 2021, 35 (S2), S364– S369. https://doi.org/10.1016/j.gaceta.2021.10.052.

[22] Hindricks, G.; Potpara, T.; Dagres, N.; Arbelo, E.; Bax, J. J.; Blomström-Lundqvist, C.; Boriani, G.; Castella, M.; Dan, G.- A.; Dilaveris, P. E.; Fauchier, L.; Filippatos, G.; Kalman, J. M.; La Meir, M.; Lane, D. A.; Lebeau, J.-P.; Lettino, M.; Lip, G. Y. H.; Pinto, F. J.; Thomas, G. N.; et al. 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). Eur. Heart J. 2021, 42 [5], 373–498. https:// doi.org/10.1093/eurheartj/ehaa612.

[23] Abedin, Z. Differential diagnosis of wide QRS tachycardia: A review. J. Arrhythm. 2021, 37 [5], 1162–1172. https://doi. org/10.1002/joa3.12599.

[24] American Medical Resource Institute. SVT vs VT: Understanding the Difference in Heart Rhythm Disorders. ACLS Online Blog. https://www.aclsonline.us/blog/difference-betweensvt-and-vt/ (accessed August 20, 2025).

[25] Li, K.; Elgalad, A.; Cardoso, C.; Perin, E. C. Using the Dean&Francis April Liao Apple Watch to record multiple-lead electrocardiograms in detecting myocardial infarction: Where are we now? Tex Heart Inst J. 2022, 49 [4], e227845. https://doi.org/10.14503/THIJ-22- 7845.

[26] Mallick, A.; Rahul, L. R.; Shaiju, A.; Neelapala, S. D.; Giri, L.; Sarkar, R.; Jana, S. AI-based 3-lead to 12-lead ECG reconstruction: Towards smartphone-based public healthcare. In Proceedings of the 2024 IEEE International Conference on E-health Networking, Application & Services (HealthCom); IEEE: Nara, Japan, 2024; pp 1–6. https://doi.org/10.1109/ HealthCom60970.2024.10880752.

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Published

2025-10-23