BACKGROUND: The ubiquitous presence of internet-connected phones and tablets presents a new opportunity for cost-effective and efficient electrocardiogram (ECG) screening and on-demand diagnosis. Wireless, single-lead real-time ECG monitoring supported by iOS and android devices can be obtained quickly and on-demand. ECGs can be immediately downloaded and reviewed using any internet browser. OBJECTIVE: We compared the standard 12-lead ECG to the smartphone ECG in healthy young adults, elite athletes, and cardiology clinic patients. Accuracy for determining baseline ECG intervals and rate and rhythm was assessed. METHODS: In 381 participants, 30-second lead I ECG waveforms were obtained using an iPhone case or iPad. Standard 12-lead ECGs were acquired immediately after the smartphone tracing was obtained. De-identified ECGs were interpreted by automated algorithms and adjudicated by two board-certified electrophysiologists. RESULTS: Both smartphone and standard ECGs detected atrial rate and rhythm, AV block, and QRS delay with equal accuracy. Sensitivities ranged from 72% (QRS delay) to 94% (atrial fibrillation). Specificities were all above 94% for both modalities. CONCLUSION: Smartphone ECG accurately detects baseline intervals, atrial rate, and rhythm and enables screening in diverse populations. Efficient ECG analysis using automated discrimination and an enhanced smartphone application with notification capabilities are features that can be easily incorporated into the acquisition process.
BACKGROUND: The ubiquitous presence of internet-connected phones and tablets presents a new opportunity for cost-effective and efficient electrocardiogram (ECG) screening and on-demand diagnosis. Wireless, single-lead real-time ECG monitoring supported by iOS and android devices can be obtained quickly and on-demand. ECGs can be immediately downloaded and reviewed using any internet browser. OBJECTIVE: We compared the standard 12-lead ECG to the smartphone ECG in healthy young adults, elite athletes, and cardiology clinic patients. Accuracy for determining baseline ECG intervals and rate and rhythm was assessed. METHODS: In 381 participants, 30-second lead I ECG waveforms were obtained using an iPhone case or iPad. Standard 12-lead ECGs were acquired immediately after the smartphone tracing was obtained. De-identified ECGs were interpreted by automated algorithms and adjudicated by two board-certified electrophysiologists. RESULTS: Both smartphone and standard ECGs detected atrial rate and rhythm, AV block, and QRS delay with equal accuracy. Sensitivities ranged from 72% (QRS delay) to 94% (atrial fibrillation). Specificities were all above 94% for both modalities. CONCLUSION: Smartphone ECG accurately detects baseline intervals, atrial rate, and rhythm and enables screening in diverse populations. Efficient ECG analysis using automated discrimination and an enhanced smartphone application with notification capabilities are features that can be easily incorporated into the acquisition process.
Authors: David D McMANUS; Jo Woon Chong; Apurv Soni; Jane S Saczynski; Nada Esa; Craig Napolitano; Chad E Darling; Edward Boyer; Rochelle K Rosen; Kevin C Floyd; Ki H Chon Journal: J Cardiovasc Electrophysiol Date: 2015-11-13
Authors: Jonathan S Steinberg; Niraj Varma; Iwona Cygankiewicz; Peter Aziz; Paweł Balsam; Adrian Baranchuk; Daniel J Cantillon; Polychronis Dilaveris; Sergio J Dubner; Nabil El-Sherif; Jaroslaw Krol; Malgorzata Kurpesa; Maria Teresa La Rovere; Suave S Lobodzinski; Emanuela T Locati; Suneet Mittal; Brian Olshansky; Ewa Piotrowicz; Leslie Saxon; Peter H Stone; Larisa Tereshchenko; Mintu P Turakhia; Gioia Turitto; Neil J Wimmer; Richard L Verrier; Wojciech Zareba; Ryszard Piotrowicz Journal: Ann Noninvasive Electrocardiol Date: 2017-05 Impact factor: 1.468