JMIR Publications

ABSTRACT

Background:

To date, the 12-lead electrocardiogram (ECG) is the gold standard for cardiological diagnosis in clinical settings. But due to the technological progress, a growing number of smartphone applications and gadgets for recording, visualizing and evaluating physical performance as well as health data is available. Although this new technology is innovative, time- and cost-efficient, only little is known about its accuracy in free-living conditions.

Objective:

This study aimed to examine the agreement between the single-lead ECG measurements of the Kardia Mobile App and the Apple Watch 4 compared to the 12-lead gold standard ECG in healthy adults in a non-clinical setting. Furthermore, it should be assessed whether the measurement error of the devices increases with an increasing heart rate.

Methods:

The study was designed as a prospective quasi-experimental one-sample measurement in which no randomization of the sampling was carried out. In total, ECGs at rest from N = 81 (average age 24.89  8.58 years, 71.6 % male) were recorded and statistically analyzed. We first created Bland-Altman-Plots for the graphical illustration of the measurement differences. To analyze the agreement between the mobile single-lead ECGS and the gold standard 12-lead ECG, we calculated Pearson’s correlations (r) and Lin’s concordance correlation coefficient (CCCLin).

Results:

Results showed a higher agreement for the Apple Watch (mean deviation QT: 6.85 %, QTcF: 7.43 %) than Kardia Mobile (mean deviation QT: 9.53 %, QTcF: 9.78 %) even if both tend to underestimate QT and QTcF intervals. For Kardia Mobile, the QT and QTcF intervals correlated significantly with the gold standard (rQT = .857, rQTcF = .727, p < .001). Lin’s concordance correlation coefficient corresponded to an almost complete heuristic agreement for the QT interval (CCCLin = .835), whereas the QTcF interval was in the range of strong agreement (CCCLin = .682). Also, for the Apple Watch, Pearson’s correlations were highly significant and in the range of a large effect (rQT = .793, rQTcF = .649, p < .001). Lin’s concordance correlation coefficient corresponded to a strong heuristic agreement for both the QT (CCCLin = .779) and QTcF (CCCLin = .615) intervals. A small negative correlation between the measurement error and increasing heart rate could be found of each the devices and the reference.

Conclusions:

The smart technology seems to be a promising and reliable approach for home-based health monitoring. Further research is needed to broaden the evidence regarding its validity and usability in different target groups. Clinical Trial: The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the University’s Ethics Committee (06/04/2018). All participants provided informed written consent. Participation was free and included no further risks. Participants were randomly assigned to numerical codes, for that data could be handled anonymously. The study was not preregistered.