Cross-Database and Cross-Channel Electrocardiogram Arrhythmia Heartbeat Classification Based on Unsupervised Domain Adaptation

January 1, 2024·
Md Niaz Imtiaz
Naimul Khan
Naimul Khan
· 0 min read
Abstract
We present an unsupervised domain adaptation approach for ECG arrhythmia classification that generalizes across different databases and lead configurations without requiring labeled target-domain data, addressing a critical challenge in clinical deployment of cardiac AI systems.
Type
Publication
Expert Systems with Applications, 244, 122960
publications
ECG Arrhythmia Classification Domain Adaptation Cardiology
Authors
Md Niaz Imtiaz
Post-Doctoral Fellow
Recently completed his PhD with Dr. Khan. Expert in physiological signal analysis and unsupervised domain adaptation, with a focus on cross-dataset generalization for ECG and EEG-based applications.
Naimul Khan
Authors
Naimul Khan
Associate Professor & Lab Director
Associate Professor and Director of the Multimedia Research Laboratory at Toronto Metropolitan University. Research spans multimedia signal processing, machine learning, and AR/VR with applications in healthcare and mental health.