MATLAB Wavelet Transform Algorithm for Removing Pulse Wave Baseline Drift

We can utilize wavelet transform in MATLAB to remove baseline drift from pulse wave signals. Wavelet transform is a highly effective signal processing technique that decomposes signals into sub-signals at different frequency bands. By applying wavelet transform to pulse wave signals, we obtain frequency-domain representations that facilitate better understanding and processing of the signal characteristics. The algorithm implementation involves key MATLAB functions including: 1. Wavelet decomposition using functions like wavedec() to break down the signal into approximation and detail coefficients 2. Thresholding operations on detail coefficients to eliminate low-frequency baseline drift components 3. Signal reconstruction using waverec() to generate the cleaned pulse wave This wavelet-based approach effectively separates the high-frequency pulse components from low-frequency baseline drift through multi-resolution analysis. The algorithm automatically identifies and removes drift components while preserving the morphological features of the original pulse wave. By implementing this wavelet transform algorithm, we achieve more accurate pulse wave analysis and research capabilities, enabling reliable feature extraction and physiological parameter calculation from clean pulse signals. The code provides customizable parameters for wavelet type selection, decomposition level adjustment, and threshold optimization to accommodate various signal qualities and application requirements.