Multi-Classification Model for PPG Signal Arrhythmia Based on Time-Frequency Dual-Domain Attention Fusion.

ABSTRACT: Cardiac arrhythmia is a leading cause of sudden cardiac death. Its early detection and continuous monitoring hold significant clinical value. Photoplethysmography (PPG) signals, owing to their non-invasive nature, low cost, and convenience, have become a vital information source for monitoring cardiac activity and vascular health. However, the inherent non-stationarity of PPG signals and significant inter-individual variations pose a major challenge in developing highly accurate and efficient arrhythmia classification methods. To address this challenge, we propose a Fusion Deep Multi-domain Attention Network (Fusion-DMA-Net). Within this framework, we innovatively introduce a cross-scale residual attention structure to comprehensively capture discriminative features in both the time and fr

SUBMITTER: Sun Y 

PROVIDER: S-EPMC12526570 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature