Bilateral Signal Warping for Left Ventricular Hypertrophy Diagnosis

TL;DR

This paper presents a novel bilateral signal warping method that enhances ECG-based diagnosis of Left Ventricular Hypertrophy by clustering heartbeat prototypes and comparing new records to these references.

Contribution

It introduces a bilateral signal warping approach that improves ECG classification accuracy for LVH by creating and utilizing heartbeat prototypes for better diagnosis.

Findings

Effective clustering of heartbeat prototypes

Improved ECG-based LVH detection accuracy

Potential for clinical application

Abstract

Left Ventricular Hypertrophy (LVH) is a major cardiovascular risk factor, linked to heart failure, arrhythmia, and sudden cardiac death, often resulting from chronic stress like hypertension. Electrocardiography (ECG), while varying in sensitivity, is widely accessible and cost-effective for detecting LVH-related morphological changes. This work introduces a bilateral signal warping (BSW) approach to improve ECG-based LVH diagnosis. Our method creates a library of heartbeat prototypes from patients with consistent ECG patterns. After preprocessing to eliminate baseline wander and detect R peaks, we apply BSW to cluster heartbeats, generating prototypes for both normal and LVH classes. We compare each new record to these references to support diagnosis. Experimental results show promising potential for practical application in clinical settings.