Monitoring Atrial Fibrillation using PPG Signals and a Smartphone

Abstract

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.

Quantitative Analysis Using Consecutive Time Window for Unobtrusive Atrial Fibrillation Detection Based on Ballistocardiogram Signal

“…These monitoring devices are convenient, but they are based on cardiac electrophysiology and lack the analysis of cardio-dynamic changes. For PPG-based AF detection, wearable devices include smartwatches/bands [ 49 , 50 , 51 ], smartphones [ 52 , 53 ], and cameras [ 54 ]. These monitoring devices can provide cardio-dynamic information, but the accuracy is currently affected by motion artefacts, measurement location, skin conditions, ectopic beats, peripheral vascular disease, poor skin contact, and limited battery life [ 44 , 55 ].…”

Recent Research for Unobtrusive Atrial Fibrillation Detection Methods Based on Cardiac Dynamics Signals: A Survey

“…Moreover, Poh et al Chan et al and Krivoshei et al used a smartphone with a sampling rate of 30 Hz, where the device was placed on the tip of the index finger to extract the PPG signal for distinguishing AF and SR [ 51 , 52 , 53 ]. Gallego et al collected the PPG signals with the sensor embedded in the Samsung smartphone to detect AF [ 54 ].…”

“…In terms of PPG signal, Bashar et al filtered the PPG signal using a 6th order Butterworth band-pass filter with passband frequencies ranging from 0.5 to 20 Hz [ 44 ]. Estrella-Gallego et al utilized an exponentially weighted moving average (EWMA) filter to denoise PPG signals [ 54 ]. Shashikumar et al applied a 41st order FIR band-pass filter with passband frequencies from 0.2 to 10 Hz to filter PPG signals [ 45 ].…”

“…The frame length of SCG signal was generally set as 5 s [ 22 , 23 ], 10 s [ 4 , 33 , 34 , 35 , 36 ] or 12.5 s [ 30 , 31 ], 30 s [ 41 , 45 ]. Moreover, the frame length of PPG signal was commonly set as 1.66 s [ 46 ], 5 s [ 32 ], 10 s [ 57 ], 15 s [ 50 ], 17 s [ 51 ], 17.1 s [ 52 ], 30 s [ 40 , 43 , 44 , 45 , 47 , 54 ], or 60 s [ 42 ].…”

“…Lahdenoja et al calculated HR from the median of eight BBI from each SCG segment to identify AF [ 33 ]. A. Estrella-Gallego et al extracted HR using the location of each PPG trough to detect AF [ 54 ].…”