Advanced Methods in Biomedical Signal Processing and Analysis

Presenting state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, and empirical mode decomposition.

The book also provides an understanding of feature extraction, feature ranking, and feature selection methods, while demonstrating how to apply artificial intelligence and machine learning to biosignal techniques.

Gives advanced methods in signal processing

Includes machine and deep learning methods

Presents experimental case studies