MobileAF, a novel smartphone-based acoustic sensing system, detected atrial fibrillation with 98.4% accuracy, 99.2% specificity, and 95.8% recall in a study of 23 participants.
Does the MobileAF smartphone-based acoustic sensing system accurately detect atrial fibrillation in participants?
A novel smartphone-based acoustic sensing system demonstrated high accuracy and precision for detecting atrial fibrillation in a small initial cohort.
Atrial fibrillation (AF) is characterized by irregular electrical impulses originating in the atria, which can lead to severe complications and even death. Due to the intermittent nature of the AF, early and timely monitoring of AF is critical for patients to prevent further exacerbation of the condition. Although ambulatory ECG Holter monitors provide accurate monitoring, the high cost of these devices hinders their wider adoption. Current mobile-based AF detection systems offer a portable solution, however, these systems have various applicability issues such as being easily affected by environmental factors and requiring significant user effort. To overcome the above limitations, we present MobileAF , a novel smartphone-based AF detection system using speakers and microphones. In order to capture minute cardiac activities, we propose a multi-channel pulse wave probing method. In addition, we enhance the signal quality by introducing a three-stage pulse wave purification pipeline. What’s more, a ResNet-based network model is built to implement accurate and reliable AF detection. We collect data from 23 participants utilizing our data collection application on the smartphone. Extensive experimental results demonstrate the superior performance of our system, with 98.4% accuracy, 97.6% precision, 95.8% recall, 99.2% specificity, and 96.7% F1 score.
Liu et al. (Sat,) conducted a other in Atrial fibrillation (n=23). MobileAF (smartphone-based AF detection system) was evaluated on AF detection accuracy. MobileAF, a novel smartphone-based acoustic sensing system, detected atrial fibrillation with 98.4% accuracy, 99.2% specificity, and 95.8% recall in a study of 23 participants.