The purpose of this 4-in-1 observational study is to test the performance of artificial intelligences (AIs) in distinguishing irregularly irregular heart rhythm called atrial fibrillation (AF) from normal heart rhythm using physiological signals collected by smartphones' built-in hardware and/or external accessories. Participants will: * Have their weight, height, resting heart rate and blood pressures measured * Have 12-lead electrocardiogram (ECG) of their heart electrical activities recorded * Have their heart sounds and 1-lead ECG recorded from their chest, and optical-based blood flow data (photoplethysmography or PPG) and 1-lead ECG recorded from their fingers using smartphones' built-in microphone, camera, and/or external accessories * Optionally have their optical-based blood flow data recorded from their face using smartphones' built-in camera (remote PPG or rPPG). The researchers will also create a database containing the physiological signals collected in this study along with the participants' medically relevant information to help train and test future AIs for medical applications.
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Differentiation of Atrial Fibrillation from Sinus Rhythm in Heart Sound Recordings
Timeframe: Day 0