Atrial Fibrillation Detection System via Acoustic Sensing for Mobile Phones
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.
Authors
- Xuanyu Liu (ORCID: https://orcid.org/0009-0001-2825-311X)
- Haoxian Liu (ORCID: https://orcid.org/0009-0004-7550-1325)
- Zongqi Yang (ORCID: https://orcid.org/0009-0006-4191-8290)
- Jin Zhang (ORCID: https://orcid.org/0000-0002-2674-0918)
- Jiao Li (ORCID: https://orcid.org/0000-0002-3918-4922)
- Yi Huang (ORCID: https://orcid.org/0009-0008-0039-4026)
Institutions
- Southern University of Science and Technology (CN)
Publication Details
- Journal
- ACM Transactions on Sensor Networks
- Published
- 2025-11-08
- DOI
- https://doi.org/10.1145/3771548
- Citations
- 1
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.39