Med2ECG: Medical-Guided BCG-To-ECG Reconstruction for Diverse Populations

作者：Lin Chen, Yandao Huang, C W. LI, Jun Chen, Shuxin Zhong, Minghui Qiu, Chunzhen Guo, Yi Wang, Qian Zhang, Kaishun Wu · 年份：2026 · DOI：10.1145/3774906.3800463 · 研究领域：ECG Monitoring and Analysis、Non-Invasive Vital Sign Monitoring、Heart Rate Variability and Autonomic Control

Continuous ECG monitoring is vital for early detection of arrhythmias and other cardiac abnormalities—especially during sleep, when symptoms often go unnoticed—yet existing solutions remain expensive, obtrusive, and impractical for long-term daily use. Ballistocardiography (BCG)—a passive, contactless modality that captures cardiac-induced body motion—offers a compelling alternative. However, prior efforts treat ECG reconstruction as waveform regression, leading to overfitting to individual-specific or posture-dependent artifacts. Inspired by the fact that ECG and BCG reflect parallel structures in cardiac event sequences (e.g., P/QRS/T-waves vs. I/J-waves), we design Med2ECG: a structure-aligned system that reconstructs ECG from high-fidelity BCG by explicitly aligning their latent physiological events. Med2ECG incorporates three key designs: (i) Multi-Scale Feature Extractor captures hierarchical temporal dynamics, preserving clinically relevant fine-grained features; (ii) Shared-Personalized Experts employs a Mixture-of-Experts (MoE) to adaptively disentangle signal variations due to individual and environmental factors; (iii) Medical-Informed Strategies introduces a diagnostic-driven multi-objective loss, integrating structural alignment, morphological fidelity, and landmark-aware supervision to preserve clinically critical intervals. Experiments across public and self-collected in-hospital datasets (20 healthy individuals and 10 patients with diverse cardiovascular condi...