Smartphone-based ECG Arrhythmia Detection By Ryan D White, MS and Greg Flaker, MD
The detection of atrial fibrillation (AF) is important for stroke prevention in patients with AF. Multiple studies have shown the AliveCor smartphone ECG, called KardiaMobile, to be a reliable and accurate means of detecting atrial fibrillation. This device shows promise in arrhythmia assessment, managing patients with AF, and diagnosing AF early in high risk patients.
Atrial fibrillation (AF) is a common arrhythmia, affecting more than 2.7 million Americans [2]. This arrhythmia is associated with significant morbidity, carrying a 4- to 5-fold increased risk for ischemic stroke [3]. AF is often silent, with patients occasionally presenting with stroke as the first manifestation of the arrhythmia [4]. Other patients have troubling symptoms such as palpitations or dizziness. Smartphone monitoring of AF could also prove useful in patients with known AF. Symptomatic episodes could be documented which might alter the patient’s regimen of rhythm control or rate control medications. Furthermore, the costs for treating AF are extremely high, accounting for greater than 6.5 billion dollars annually [5].
The US FDA 510(k)-cleared KardiaMobile is smaller than a credit card and consists of two metal electrodes. A bipolar ECG lead I is created when the two metal electrodes are touched by the patient’s right and left hands. The ECG electrical signals are then converted into high frequency sound waves and transmitted to a smartphone on which the AliveCor Kardia App has been installed. The ECG can be reviewed on the smartphone, electronically stored or emailed, or electronically sent for professional review [Figure 2].
AliveCor has developed three FDA-cleared algorithms for use in the device [7]. An ECG is labeled as “Normal” when a patient’s heart rate is between 50-100 beats per minute, there are no or very few abnormal beats, and the rhythm is considered normal sinus. The ECG is labeled as “Unreadable” when the detector indicates there was too much interference for an adequate recording, whether from too much movement, or poor contact between the electrodes and the patient’s skin. The rhythm is labeled as “"Possible Atrial Fibrillation" when the device detects the presence of atrial fibrillation. AliveCor notes that this device provides possible findings and is not capable of making a diagnosis of atrial fibrillation. The recorded ECG can then be sent to a physician or medical professional for further review.
Smartphone accessory-based arrhythmia devices currently offer a validated means of monitoring atrial fibrillation. AliveCor device has received FDA clearance and has undergone over 60 studies demonstrating its accuracy. This device is available over the counter and is marketed directly to the general public in the United States. Multiple studies have shown the device to be a reliable and accurate means of detecting atrial fibrillation. However, it is important to note that the device is not intended for use in patients with implantable cardiac devices, such as pacemakers or ICDs or pediatric patients. The detection of AF by the AliveCor device is not diagnostic, and positive findings of new AF should warrant a confirmatory ECG.
References 1. Smith A. U.S. Smartphone Use in 2015. Pew Research Center. http://www.pewinternet.org/2015/04/01/us-smartphone-use-in-2015/ (Accessed January 2017). 2017;0:0?0. 2. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, De Ferranti S, Despr?s JP, Fullerton HJ, Howard VJ, Huffman MD, Judd SE, Kissela BM, Lackland DT, Lichtman JH. Heart disease and stroke statistics-2015 update. A report from the American Heart Association. 2015;0:0?0. [PubMed] 3. Wolf P A, Abbott R D, Kannel W B. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke. 1991 Aug;22 (8):983?8. [PubMed] 4. Healey JS, Connolly SJ, Gold MR, Israel CW, Van Gelder IC, Capucci A, Lau CP, Fain E, Yang S, Bailleul C, Morillo CA, Carlson M, Themeles E, Kaufman ES, Hohnloser SH. Subclinical atrial fibrillation and the risk of stroke. N Engl J Med. 2012;366:120?129. [PubMed] 5. Coyne Karin S, Paramore Clark, Grandy Susan, Mercader Marco, Reynolds Matthew, Zimetbaum Peter. Assessing the direct costs of treating nonvalvular atrial fibrillation in the United States. Value Health. 2006 Sep 12;9 (5):348?56. [PubMed] 6. Chan Pak-Hei, Wong Chun-Ka, Poh Yukkee C, Pun Louise, Leung Wangie Wan-Chiu, Wong Yu-Fai, Wong Michelle Man-Ying, Poh Ming-Zher, Chu Daniel Wai-Sing, Siu Chung-Wah. Diagnostic Performance of a Smartphone-Based Photoplethysmographic Application for Atrial Fibrillation Screening in a Primary Care Setting. J Am Heart Assoc. 2016 Jul 21;5 (7) [PMC free article] [PubMed] 7. AliveCore. AliveCor FAQ. https://www.alivecor.com/faq/ (Accessed January 2017). 2017;0:0?0. 8. Lau Jerrett K, Lowres Nicole, Neubeck Lis, Brieger David B, Sy Raymond W, Galloway Connor D, Albert David E, Freedman Saul B. iPhone ECG application for community screening to detect silent atrial fibrillation: a novel technology to prevent stroke. Int. J. Cardiol. 2013 Apr 30;165 (1):193?4. [PubMed] 9. Lowres Nicole, Neubeck Lis, Salkeld Glenn, Krass Ines, McLachlan Andrew J, Redfern Julie, Bennett Alexandra A, Briffa Tom, Bauman Adrian, Martinez Carlos, Wallenhorst Christopher, Lau Jerrett K, Brieger David B, Sy Raymond W, Freedman S Ben. Feasibility and cost-effectiveness of stroke prevention through community screening for atrial fibrillation using iPhone ECG in pharmacies. The SEARCH-AF study. Thromb. Haemost. 2014 Jun;111 (6):1167?76. [PubMed] 10. Williams J, Pearce K, Benett I, Williams J, Manchester M, Pearce K, Benett I. The effectiveness of a mobile ECG device in identifying AF: sensitivity, specificity and predictive value. British Journal of Cardiology. 2015;22:70?72. 11. Desteghe Lien, Raymaekers Zina, Lutin Mark, Vijgen Johan, Dilling-Boer Dagmara, Koopman Pieter, Schurmans Joris, Vanduynhoven Philippe, Dendale Paul, Heidbuchel Hein. Performance of handheld electrocardiogram devices to detect atrial fibrillation in a cardiology and geriatric ward setting. Europace. 2017 Jan;19 (1):29?39. [PubMed] 12. Hickey Kathleen T, Hauser Nicole R, Valente Laura E, Riga Teresa C, Frulla Ashton P, Masterson Creber Ruth, Whang William, Garan Hasan, Jia Haomiao, Sciacca Robert R, Wang Daniel Y. 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. 2016 Jul 16;16