Why the study?
Facilitating AF monitoring using portable devices like smartphones could improve patient quality of life and support early diagnosis.
Can an algorithm using PPG signals from a smartphone camera detect paroxysmal atrial fibrillation?
Can an algorithm using PPG signals from a smartphone camera detect paroxysmal atrial fibrillation?
This work proposes a smartphone-based PPG algorithm for the detection of paroxysmal atrial fibrillation, aiming to facilitate accessible monitoring.
Answers are grounded in this paper and cite their sources.
Daily ECG monitoring may aid silent AF detection in older adults; leaves open need for outcome trials before practice change.
Atrial fibrillation (AF) is a common type of cardiac arrhythmia. AF is associated with increased rates of death and hospitalizations. It is also related to a degraded quality of life and reduced exercise capacity. Ageing increases the risk of developing AF, as well as hypertension and obesity. Continuous ECG monitoring is required in patients with previously diagnosed AF. Studies have also demonstrated that daily ECG monitoring increases the successful detection of silent AF among older adults. In this sense facilitating AF monitoring using portable devices such as Smartphones will increase patients life quality and could help to an early diagnosis. With this in mind in this work we present a proposal to detect AF using pulsatile photoplethysmogram (PPG) signal from a fingertip using the built-in camera lens in a smartphone. We developed an algorithm intended to sense paroxysmal AF considering resource utilization capabilities in order to be used in mobile devices with constrained.
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Estrella-Gallego et al. (2020) studied Atrial Fibrillation (n=9). Smartphone-based PPG algorithm vs. Kardia AliveCor ECG sensor and Samsung Health App was evaluated on Detection of atrial fibrillation and heart rate estimation.
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