Table 3 Open in new tab Diagnostic...

Study

Device and AI algorithm

Signal analysed

AF detection

Algorithm using smartphone (Kardia Mobile Cardiac Monitor) and handheld cardiac rhythm recorder vs. physician-interpreted ECG

ECG

96.6% sensitivity and 94.1% specificity for AF detection

Wristband/wristwatch-based irregular pulse notification algorithm

PPG

Positive predictive value of PPG signals being 91.6% (95% CI 91.5–91.8%)

Smartwatch-based irregular pulse notification algorithm vs. subsequent monitoring with ECG patch

Initial PPG followed by simultaneous PPG and ECG

Smartwatch-based algorithm had a positive predictive value of 0.84 (95% CI 0.76–0.92) for observing AF during the simultaneous monitoring period

Chen et al.²⁰

Smart wristband device enabled by AF-identifying AI algorithm vs. wristband ECG reviewed by physicians

PPG and ECG

Sensitivity, specificity, and accuracy were 88.00%, 96.41%, and 93.27%, respectively, for PPG and 87.33%, 99.20%, and 94.76% for ECG

Wasserlauf et al.²¹

Apple Watch with KardiaBand (enabled by convoluted neural network algorithm) vs. insertable cardiac monitor

ECG

97.5% and 97.7% for episode sensitivity and duration sensitivity, respectively

Smartwatch-based algorithm vs. cardiologists’ diagnosis by electrocardiography

PPG

Sensitivity of 93.7% (95% CI 89.8–96.4%), specificity of 98.2% (95% CI 95.8–99.4%), and 96.1% accuracy (95% CI 94.0–97.5%)

Table 3

Diagnostic accuracy of artificial intelligence-aided devices in identifying atrial fibrillation

Study	Device and AI algorithm	Signal analysed	AF detection
The iREAD Study William et al.¹⁷	Algorithm using smartphone (Kardia Mobile Cardiac Monitor) and handheld cardiac rhythm recorder vs. physician-interpreted ECG	ECG	96.6% sensitivity and 94.1% specificity for AF detection
HUAWEI Heart Study Guo et al.¹⁸	Wristband/wristwatch-based irregular pulse notification algorithm	PPG	Positive predictive value of PPG signals being 91.6% (95% CI 91.5–91.8%)
Apple Heart Study Perez et al.¹⁹	Smartwatch-based irregular pulse notification algorithm vs. subsequent monitoring with ECG patch	Initial PPG followed by simultaneous PPG and ECG	Smartwatch-based algorithm had a positive predictive value of 0.84 (95% CI 0.76–0.92) for observing AF during the simultaneous monitoring period
Chen et al.²⁰	Smart wristband device enabled by AF-identifying AI algorithm vs. wristband ECG reviewed by physicians	PPG and ECG	Sensitivity, specificity, and accuracy were 88.00%, 96.41%, and 93.27%, respectively, for PPG and 87.33%, 99.20%, and 94.76% for ECG
Wasserlauf et al.²¹	Apple Watch with KardiaBand (enabled by convoluted neural network algorithm) vs. insertable cardiac monitor	ECG	97.5% and 97.7% for episode sensitivity and duration sensitivity, respectively
WATCH AF trial Dörr et al.²²	Smartwatch-based algorithm vs. cardiologists’ diagnosis by electrocardiography	PPG	Sensitivity of 93.7% (95% CI 89.8–96.4%), specificity of 98.2% (95% CI 95.8–99.4%), and 96.1% accuracy (95% CI 94.0–97.5%)

Study	Device and AI algorithm	Signal analysed	AF detection
The iREAD Study William et al.¹⁷	Algorithm using smartphone (Kardia Mobile Cardiac Monitor) and handheld cardiac rhythm recorder vs. physician-interpreted ECG	ECG	96.6% sensitivity and 94.1% specificity for AF detection
HUAWEI Heart Study Guo et al.¹⁸	Wristband/wristwatch-based irregular pulse notification algorithm	PPG	Positive predictive value of PPG signals being 91.6% (95% CI 91.5–91.8%)
Apple Heart Study Perez et al.¹⁹	Smartwatch-based irregular pulse notification algorithm vs. subsequent monitoring with ECG patch	Initial PPG followed by simultaneous PPG and ECG	Smartwatch-based algorithm had a positive predictive value of 0.84 (95% CI 0.76–0.92) for observing AF during the simultaneous monitoring period
Chen et al.²⁰	Smart wristband device enabled by AF-identifying AI algorithm vs. wristband ECG reviewed by physicians	PPG and ECG	Sensitivity, specificity, and accuracy were 88.00%, 96.41%, and 93.27%, respectively, for PPG and 87.33%, 99.20%, and 94.76% for ECG
Wasserlauf et al.²¹	Apple Watch with KardiaBand (enabled by convoluted neural network algorithm) vs. insertable cardiac monitor	ECG	97.5% and 97.7% for episode sensitivity and duration sensitivity, respectively
WATCH AF trial Dörr et al.²²	Smartwatch-based algorithm vs. cardiologists’ diagnosis by electrocardiography	PPG	Sensitivity of 93.7% (95% CI 89.8–96.4%), specificity of 98.2% (95% CI 95.8–99.4%), and 96.1% accuracy (95% CI 94.0–97.5%)

AF, atrial fibrillation; AI, artificial intelligence; CI, confidence interval; ECG, electrocardiogram; PPG, photo plethysmography.