paper-with-me

홈 › Papers

AcousAF: Acoustic Sensing-Based Atrial Fibrillation Detection System for Mobile Phones

2024-08-09 · Xuanyu Liu, Haoxian Liu, Jiao Li, Zongqi Yang, Yi Huang, Jin Zhang

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.

📄 PDF Abstract BibTeX arXiv:2408.04912

Code (0)

등록된 구현이 없습니다.

Tasks

Atrial Fibrillation Detection

Similar Papers 제목 키워드 기반

Atrial Fibrillation Detection Using RR-Intervals for Application in Photoplethysmographs

2023-02-13 · Georgia Smith, Yishi Wang

Atrial Fibrillation is a common form of irregular heart rhythm that can be very dangerous. Our primary goal is to analyze Atrial Fibrillation data within ECGs to develop a model based only on RR-Intervals, or the length …

Atrial Fibrillation DetectionRhythm

ECGNET: Learning where to attend for detection of atrial fibrillation with deep visual attention

2019-02-15 · arXiv:1812.07422 2018 12

The complexity of the patterns associated with Atrial Fibrillation (AF) and the high level of noise affecting these patterns have significantly limited the current signal processing and shallow machine learning approache…

Atrial Fibrillation DetectionSpecificity

Self-supervised inter-intra period-aware ECG representation learning for detecting atrial fibrillation

2024-10-08 · Xiangqian Zhu, Mengnan Shi, Xuexin Yu, Chang Liu 외

Atrial fibrillation is a commonly encountered clinical arrhythmia associated with stroke and increased mortality. Since professional medical knowledge is required for annotation, exploiting a large corpus of ECGs to deve…

Atrial Fibrillation DetectionRepresentation LearningSelf-Supervised Learning

Deciphering Heartbeat Signatures: A Vision Transformer Approach to Explainable Atrial Fibrillation Detection from ECG Signals

2024-02-12 · Aruna Mohan, Danne Elbers, Or Zilbershot, Fatemeh Afghah 외

Remote patient monitoring based on wearable single-lead electrocardiogram (ECG) devices has significant potential for enabling the early detection of heart disease, especially in combination with artificial intelligence …

Atrial Fibrillation DetectionRhythm

A method for detection of atrial fibrillation using RR intervals

2000-09-24 · Computers in Cardiology 2000 9 · K. Tateno, L. Glass

This work describes a method for automatic detection of atrial fibrillation (AF) based on RR intervals. We define /spl Delta/RR to be the difference between successive RR intervals. The standard density histograms of RR …

Atrial Fibrillation DetectionSpecificity