Currently submitted to: JMIR Cardio
Date Submitted: Jun 3, 2019
Open Peer Review Period: Jun 5, 2019 - Jun 25, 2019
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The Use of Smart Watch for Early Detection of Paroxysmal Atrial Fibrillation: Validation Study
Wearable devices that carry a photoplethysmograph (PPG) can be useful for detecting paroxysmal atrial fibrillation (AF), which often goes uncaptured despite being a leading cause of stroke.
This study is the first part of a 2-phase study, which aimed at developing a method for immediate detection of paroxysmal AF using PPG-integrated wearable devices. In this study, the diagnostic performance of 2 major smart watches, Apple Watch Series 3 and Fitbit Charge HR, each equipped with a PPG sensor, were compared, and the pulse rate data outputted from those devices were analyzed for precision and accuracy in reference to the heart rate data from electrocardiography (ECG) during AF.
40 subjects from patients who underwent cardiac surgery at a single center between September 2017 and March 2018 were monitored for postoperative AF using telemetric ECG and PPG devices. AF was diagnosed using 12-lead ECG by qualified physicians. Each subject was given a pair of smart watches, Apple Watch and Fitbit, for simultaneous pulse rate monitoring. The heart rates of all subjects were also recorded on the telemetry system. Time-series pulse rate trends and heart rate trends were created and analyzed for trend pattern similarities. Those trend data were then used to determine the accuracy of PPG-based pulse rate measurements in reference to ECG-based heart rate measurements during AF.
Of the 20 AF events in group Fitbit, 6 (30%) showed a moderate or higher correlation (cross-correlation function > 0.40) between pulse rate trend patterns and heart rate trend patterns. Of the 16 AF events in group Apple Watch (workout mode), 12 (75%) showed a moderate or higher correlation between the 2 trend patterns. Linear regression analyses also showed a significant correlation between the pulse rates and the heart rates during AF in the subjects with Apple Watch. This correlation was not observed with Fitbit. Where X denotes the mean of all average pulse rates during AF and Y denotes the mean of all corresponding average heart rates during AF, the regression formulas for Apple Watch workout mode and Fitbit were X = 14.203 + 0.841Y and X = 58.225 + 0.228Y, respectively, and the coefficient of determination (R2) were 0.685 and 0.057, respectively. (P value, <0.001 and 0.285, respectively).
In this validation study, detection precision of AF and measurement accuracy during AF were both better with Apple Watch workout mode than with Fitbit.
This study was approved by the Clinical Research Ethics Committee of Chiba University Hospital (Protocol No. UMIN000028403; approved July 27, 2017)
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