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Detection of atrial fibrillation using an earlobe photoplethysmographic sensor
Thomas Conroy1, Jairo Hernandez Guzman2, Burr Hall1
1Heart Research Follow-Up Program, Cardiology Department, University of Rochester Medical Center, University of Rochester, Rochester, NY, United States of America.
Abstract:
Atrial fibrillation (AF) is the most common cardiac arrhythmia in the world, associated with increased risk of thromboembolic events and an increased mortality rate. In addition, a significant portion of AF patients are asymptomatic. Current AF diagnostic methods, often including a body surface electrocardiogram or implantable loop recorder, are both expensive and invasive and offer limited access within the general community.
Objective:
We tested the feasibility of the detection of AF using a photoplethysmographic signal acquired from an inexpensive, non-invasive earlobe photoplethysmographic sensor. This technology can be implemented into wearable devices and would enable continuous cardiac monitoring capabilities, greatly improving the rate of asymptomatic AF detection.
Approach:
We conducted a clinical study of patients going through electrical cardioversion for AF treatment. Photoplethysmographic recordings were taken from these AF patients before and after their cardioversion procedure, along with recordings from a healthy control group. Using these recordings, cardiac beats were identified and the inter-systolic interval was calculated. The inter-systolic interval was used to calculate four parameters to quantify the heart rate variability indicative of AF. Receiver operating characteristic curves were used to calculate discriminant thresholds between the AF and non-AF cohorts.
Main Results:
The parameter with the greatest discriminant capability resulted in a sensitivity and specificity of 90.9%. These results are comparable to expensive ECG-based and invasive implantable loop recorder AF detection methods.
Significance:
These results demonstrate that using a non-invasive earlobe photoplethysmographic signal is a viable and inexpensive alternative to ECG-based AF detection methods, and an alternative that could be invaluable in detecting subclinical AF.
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