Compressed Sensing for ECG and PPG: A Review of Recent Developments

Antónia Kováčová; Ján Šaliga; Ondrej Kováč

doi:10.2478/aei-2026-0008

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Compressed Sensing for ECG and PPG: A Review of Recent Developments

Acta Electrotechnica et Informatica

Volume 26 (2026): Issue 2 (June 2026)

By: Antónia Kováčová, Ján Šaliga and Ondrej Kováč

Open Access

|Jun 2026

Abstract

The increasing integration of information and communication technologies in healthcare has enabled advanced patient monitoring and personalized treatment. Efficient data management is crucial in such systems, as the high volume of biomedical signals requires optimized compression techniques. Compressed sensing has emerged as an approach within lossy compression methods, leveraging signal sparsity to achieve high compression ratios (CR) without significant loss of critical information. This paper provides a concise review of the most recent developments in CS for electrocardiogram (ECG) and photoplethysmogram (PPG) signals, summarizing key advances in standard CS methods, dictionary-based approaches, and emerging frameworks incorporating artificial intelligence. The review aims to highlight current trends and outline directions for future research in biomedical signal compression.

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