Preface

Advanced Electroencephalography Analytical Methods: Fundamentals, Acquisition, and Applications presents the theoretical basis and applications of electroencephalography (EEG) signals in neuroscience, involving signal analysis, processing, signal acquisition, representation, and applications of EEG signal analysis using nonlinear approaches and machine learning. It explains principles of neurophysiology, linear signal processing, computational intelligence, and the nature of signals including machine learning. Applications involve computer-aided diagnosis, brain-computer interfaces, rehabilitation engineering, and applied neuroscience. This book: • Includes a comprehensive review on biomedical signals nature and acquisition aspects • Focuses on selected applications of neuroscience/cardiovascular/muscle-related biomedical areas • Provides a machine learning update to a classical biomedical signal processing approach • Explains deep learning and application to biomedical signal processing and analysis • Explores relevant biomedical engineering and neuroscience state-of-the-art applications This book is intended for researchers and graduate students in biomedical signal processing, electrical engineering, neuroscience, and computer science.