Lightweight ECG signal classification via linear law-based feature extraction

Lightweight ECG signal classification via linear law-based feature extraction

This paper introduces LLT-ECG, a novel semi-supervised method for electrocardiogram (ECG) signal classification that leverages principles from theoretical physics to generate features without relying on backpropagation or hyperparameter tuning. The method identifies linear laws that capture shared p...

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Bibliographic Details
Main Authors: Péter Pósfay, Marcell T Kurbucz, Péter Kovács, Antal Jakovác
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Machine Learning: Science and Technology
Subjects:
ECG classification
linear law
representation learning
anomaly detection
machine learning
Online Access:https://doi.org/10.1088/2632-2153/ade6c3
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