Wavelet Packet Transform for Pulse Wave Baseline Drift and Motion Artifact Removal: Superior Performance Compared to Wavelet Transform

Utilizing wavelet packet transform for removing baseline drift and motion artifacts from pulse wave signals significantly enhances signal processing outcomes. Wavelet packet transform outperforms traditional wavelet transform by providing superior frequency band decomposition and signal analysis capabilities. From an implementation perspective, wavelet packet transform employs a more flexible decomposition tree structure compared to standard wavelet transform, allowing for finer frequency resolution across multiple sub-bands. The algorithm typically involves: 1. Selecting an appropriate wavelet basis function (e.g., Daubechies, Symlets) matched to pulse wave characteristics 2. Implementing multi-level decomposition using wavelet packet trees 3. Applying thresholding techniques to specific sub-bands containing artifacts 4. Reconstructing the signal while preserving essential physiological information Key advantages include the ability to decompose signals into a greater number of sub-frequency bands, enabling more comprehensive capture of signal features and subtle details. This enhanced resolution allows for more precise identification and removal of baseline wander and motion-induced interference. Consequently, wavelet packet transform delivers improved accuracy and stability in pulse wave signal processing, making it particularly valuable for biomedical applications requiring high-fidelity signal analysis. The method's effectiveness can be quantified through signal-to-noise ratio improvements and preservation of diagnostic pulse wave features during reconstruction.