Survey on Respiratory Signal Extraction from ECG Signals

This survey on respiratory signal extraction from ECG signals aims to provide detailed explanations of three distinct methodologies, ensuring readers gain comprehensive understanding of research in this domain. The three approaches - frequency extraction, filter-based filtering, and wavelet transformation - will be systematically examined. Frequency extraction techniques involve spectral analysis algorithms that can identify respiratory-related frequency components within ECG signals through Fourier transform implementations, enabling continuous respiratory monitoring and analysis. Filter-based methods utilize digital filter designs (such as bandpass or adaptive filters) with specific cutoff frequencies to eliminate interference signals while preserving accurate respiratory information. Wavelet transformation employs multi-resolution analysis principles, using functions like MATLAB's wavedec() to decompose ECG signals into different frequency bands, effectively isolating respiration-related components. Through detailed examination of these three methodologies, this survey aims to provide valuable references and inspiration for related research, including practical code implementation considerations for each technique.