Assessment of facial video-based detection of atrial fibrillation across human complexion

Background: Early self-detection of atrial fibrillation (AF) can help delay and/or prevent significant associated complications, including embolic stroke and heart failure. We developed a facial video technology, videoplethysmography (VPG), to detect AF based on the analysis of facial pulsatile signals. Objective: The purpose of this study was to evaluate the accuracy of a video-based technology to detect AF on a smartphone and to test the performance of the technology in AF patients across the whole spectrum of skin complexion and under various recording conditions. Methods: The performance of video-based monitoring depends on a set of factors such as the angle and the distance between the camera and the patient’s face, the strength of illumination, and the patient’s skin tone. We conducted a clinical study involving 60 subjects with a confirmed diagnosis of AF. A continuous electrocardiogram was used as the gold standard for cardiac rhythm annotation. The VPG technology was fine-tuned on a smartphone for the first 15 subjects. Validation recordings were then done using 7053 measurements collected from the remaining 45 subjects. Results: The VPG technology detected the presence of AF using the video camera from a common smartphone with sensitivity and specificity ≥90%. The ambient level of illumination needs to be ≥100 lux for the technology to deliver consistent performance across all skin tones. Conclusion: We demonstrated that facial video-based detection of AF provides accurate outpatient cardiac monitoring including high pulse rate accuracy and medical-grade performance for AF detection