Real-world evidence for passive video-based cardiac monitoring from smartphones used by patients with a history of AF.

Passive cardiac monitoring has become synonymous with wearable technologies, necessitating patients to incorporate new devices into their daily routines. While this requirement may not be a burden for many, it is a constraint for individuals with chronic diseases who already have their daily routine. In this study, we introduce an innovative technology that harnesses the front-facing camera of smartphones to capture pulsatile signals discreetly when users engage in other activities on their device.

Measurements of pulse rate using facial video cameras from smart devices in patients diagnosed with atrial fibrillation.

Clinical applications of passive long-term heart rate (HR) monitoring in patients with cardiac arrhythmias include adequate drug titration of atrioventricular (AV) nodal drugs and assessment of medical compliance with treatment. A majority of patients treated with beta-blockers, especially patients with atrial fibrillation (AF), require some degree of drug titration during the first 6 months of treatment to ensure that adequate HR control and medicine compliance has been achieved. Failing to achieve adequate rate control in patients with AF can lead to worsening symptoms, heart failure exacerbations, and potentially tachycardia-induced cardiomyopathy.

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.

Monitoring Pulse Rate in the Background Using Front Facing Cameras of Mobile Devices.

We propose a novel framework to passively monitor pulse rate during the time spent by users on their personal mobile devices. Our framework is based on passively capturing the user's pulse signal using the front-facing camera. Signal capture is performed in the background, while the user is interacting with the device as he/she normally would, e.

Dynamic Off-Body Rician Channel Modeling for Indoor Wireless Body Area Networks.

Wireless off-body channel is commonly treated as a traditional communication system assuming large and small scale fading to be independent. In this work, we challenge this approach and experimentally show that in a typical WBAN environment of a single room, this assumption is not accurate. We propose an off-body channel model where path loss and multipath fading are entirely determined by Rician distribution and linked through a stochastic Rician factor K.