Respiratory Rate Estimation and ECG-Derived Respiration Techniques -A Review

Abstract

Respiratory rate estimation is a critical physiological parameter with applications across healthcare, particularly in diagnosing respiratory, cardiovascular, and neurological conditions. This paper reviews multiple studies focused on respiratory rate estimation using electrocardiograms (ECG) and various signal processing techniques. The studies range from open-source software development to advanced signal fusion models and deep learning approaches. This review highlights the key methodologies, clinical validations, and the evolution of techniques for improving accuracy, reliability, and application in real-world clinical environments.