Heartbeat of Security: Unveiling the Pulse of ECG Biometric Authentication

Telehealth and remote monitoring improve healthcare accessibility but also expose sensitive data to security and privacy risks, where traditional authentication methods often prove inadequate. The electrocardiogram (ECG) has emerged as a promising biometric modality due to its inherent liveness detection, universality, and individual uniqueness. This paper reviews the ECG authentication pipeline, including signal acquisition through wearables, pre-processing techniques for noise reduction, feature extraction methods (fiducial, non-fiducial, and deep learning), and classification models. Publicly available datasets are examined, alongside key performance benchmarks. Persistent challenges-such as intra-subject variability, computational constraints in wearables, and ethical concerns are discussed, with future directions highlighting multimodal systems, privacy-preserving techniques, and standardized validation. ECG authentication demonstrates strong potential to become a secure and practical component of Telehealth systems.