AcousAF: Acoustic Sensing-Based Atrial Fibrillation Detection System for Mobile Phones
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909282676506624 |
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| author | Liu, Xuanyu Liu, Haoxian Li, Jiao Yang, Zongqi Huang, Yi Zhang, Jin |
| author_facet | Liu, Xuanyu Liu, Haoxian Li, Jiao Yang, Zongqi Huang, Yi Zhang, Jin |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_04912 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | AcousAF: Acoustic Sensing-Based Atrial Fibrillation Detection System for Mobile Phones Liu, Xuanyu Liu, Haoxian Li, Jiao Yang, Zongqi Huang, Yi Zhang, Jin Sound Computational Engineering, Finance, and Science Emerging Technologies Machine Learning Audio and Speech Processing 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. |
| title | AcousAF: Acoustic Sensing-Based Atrial Fibrillation Detection System for Mobile Phones |
| topic | Sound Computational Engineering, Finance, and Science Emerging Technologies Machine Learning Audio and Speech Processing |
| url | https://arxiv.org/abs/2408.04912 |