Approaching Low-Cost Cardiac Intelligence with Semi-Supervised Knowledge Distillation

TL;DR

This paper introduces LiteHeart, a semi-supervised knowledge distillation framework that significantly improves low-cost cardiac intelligence systems using wearable ECG data, reducing the performance gap with high-cost systems and enabling scalable daily cardiac monitoring.

Contribution

LiteHeart is the first semi-supervised knowledge distillation method that incorporates region-aware and cross-layer modules to enhance low-cost cardiac AI performance.

Findings

Outperforms existing methods by 4.27% to 7.10% in macro F1 score.

Reduces the performance gap between low-cost and high-cost cardiac AI.

Demonstrates robustness under limited supervision across five datasets.

Abstract

Deploying advanced cardiac artificial intelligence for daily cardiac monitoring is hindered by its reliance on extensive medical data and high computational resources. Low-cost cardiac intelligence (LCCI) offers a promising alternative by using wearable device data, such as 1-lead electrocardiogram (ECG), but it suffers from a significant diagnostic performance gap compared to high-cost cardiac intelligence (HCCI). To bridge this gap, we propose LiteHeart, a semi-supervised knowledge distillation framework. LiteHeart introduces a region-aware distillation module to mimic how cardiologists focus on diagnostically relevant ECG regions and a cross-layer mutual information module to align the decision processes of LCCI and HCCI systems. Using a semi-supervised training strategy, LiteHeart further improves model robustness under limited supervision. Evaluated on five datasets covering over 38 cardiovascular diseases, LiteHeart substantially reduces the performance gap between LCCI and HCCI, outperforming existing methods by 4.27% to 7.10% in macro F1 score. These results demonstrate that LiteHeart significantly enhances the diagnostic capabilities of low-cost cardiac intelligence systems, paving the way for scalable, affordable, and accurate daily cardiac healthcare using wearable technologies.