A novel app using the camera sensor of an iPhone 4S with integrated LED, the researchers tested pulse wave signals acquired from the fingertips of 80 patients with atrial fibrillation (AF) (n=40) and in sinus rhythm (SR) (n=40). They aimed to test the app’s accuracy in detecting AF compared to cardiologists AF decision based on ECG. Conclusion: app reliably discriminated between SR and AF, best parameter set achieved an overall accuracy of 95% (sensitivity 95%, specificity 95%).
Preventicus algorithm discriminated between AF patients and controls (sinus rhythm, including ectopic beats) with an overall accuracy of 95% (Sens. / Spec. 95%).
L. Krivoshei, S. Weber et al. Smart detection of atrial fibrillation. Europace. 2017 May 1;19(5):753-757.