Atrial Fibrillation Detection System via Acoustic Sensing for Mobile Phones
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866914993446846464 |
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| author | Liu, Xuanyu Li, Jiao Liu, Haoxian Yang, Zongqi Huang, Yi Zhang, Jin |
| author_facet | Liu, Xuanyu Li, Jiao Liu, Haoxian 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 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 97.9% accuracy, 96.8% precision, 97.2% recall, 98.3% specificity, and 97.0% F1 score. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2410_20852 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Atrial Fibrillation Detection System via Acoustic Sensing for Mobile Phones Liu, Xuanyu Li, Jiao Liu, Haoxian Yang, Zongqi Huang, Yi Zhang, Jin Sound Computational Engineering, Finance, and Science Audio and Speech Processing Quantitative Methods 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 97.9% accuracy, 96.8% precision, 97.2% recall, 98.3% specificity, and 97.0% F1 score. |
| title | Atrial Fibrillation Detection System via Acoustic Sensing for Mobile Phones |
| topic | Sound Computational Engineering, Finance, and Science Audio and Speech Processing Quantitative Methods |
| url | https://arxiv.org/abs/2410.20852 |