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 AcousAF, a novel AF detection system based on acoustic sensors of smartphones. Particularly, we explore the potential of pulse wave acquisition from the wrist using smartphone speakers and microphones. In addition, we propose a well-designed framework comprised of pulse wave probing, pulse wave extraction, and AF detection to ensure accurate and reliable AF detection. We collect data from 20 participants utilizing our custom data collection application on the smartphone. Extensive experimental results demonstrate the high performance of our system, with 92.8% accuracy, 86.9% precision, 87.4% recall, and 87.1% F1 Score.

翻译：心房颤动（AF）的特征是源于心房的异常电脉冲，可能导致严重并发症甚至死亡。由于AF具有间歇性，早期及时监测对于患者防止病情进一步恶化至关重要。虽然动态心电图监测仪能提供精确监测，但其高昂成本阻碍了更广泛的应用。当前基于移动设备的AF检测系统提供了便携解决方案，但这些系统存在多种适用性问题，例如易受环境因素影响且需要用户大量操作。为克服上述局限，我们提出AcousAF——一种基于智能手机声学传感器的新型AF检测系统。特别地，我们探索了利用智能手机扬声器和麦克风从腕部采集脉搏波的潜力。此外，我们提出了由脉搏波探测、脉搏波提取和AF检测组成的精心设计框架，以确保准确可靠的AF检测。我们通过智能手机定制数据采集应用收集了20名参与者的数据。大量实验结果表明，本系统具有92.8%的准确率、86.9%的精确率、87.4%的召回率和87.1%的F1分数，展现出优异性能。