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EEG/ERP Analysis Methods and Applications

Langue : Anglais

Coordonnateurs : Nidal Kamel, Malik Aamir Saeed

Couverture de l’ouvrage EEG/ERP Analysis

Changes in the neurological functions of the human brain are often a precursor to numerous degenerative diseases. Advanced EEG systems and other monitoring systems used in preventive diagnostic procedures incorporate innovative features for brain monitoring functions such as real-time automated signal processing techniques and sophisticated amplifiers. Highlighting the US, Europe, Australia, New Zealand, Japan, Korea, China, and many other areas, EEG/ERP Analysis: Methods and Applications examines how researchers from various disciplines have started to work in the field of brain science, and explains the different techniques used for processing EEG/ERP data. Engineers can learn more about the clinical applications, while clinicians and biomedical scientists can familiarize themselves with the technical aspects and theoretical approaches.

This book explores the recent advances involved in EEG/ERP analysis for brain monitoring, details successful EEG and ERP applications, and presents the neurological aspects in a simplified way so that those with an engineering background can better design clinical instruments. It consists of 13 chapters and includes the advanced techniques used for signal enhancement, source localization, data fusion, classification, and quantitative EEG. In addition, some of the chapters are contributed by neurologists and neurosurgeons providing the clinical aspects of EEG/ERP analysis.

  • Covers a wide range of EEG/ERP applications with state-of-the-art techniques for denoising, analysis, and classification
  • Examines new applications related to 3D display devices
  • Includes MATLAB® codes


EEG/ERP Analysis: Methods and Applications

is a resource for biomedical and neuroscience scientists who are working on neural signal processing and interpretation, and biomedical engineers who are working on EEG/ERP signal analysis methods and developing clinical instrumentation. It can also assist neurosurgeons, psychiatrists, and postgraduate students doing research in neural engineering, as well as electronic engineers in neural signal processing and instrumentation.

Introduction to EEG and ERP Signals. Fundamentals of EEG Signal Processing. Event-Related Potentials. EEG Source Localization. Epilepsy Detection and Monitoring. Monitoring Neurological Injury by qEEG. qEEG Brain–based Computer Interface. Major Depressive Disorder. EEG and fMRI data Fusion. Memory Retention and Recall Processes. Neurofeedback. Future Aspects of EEG and ERP Signals.

Biomedical scientists, clinicians who are working on neural signal processing and interpretation, neuroscientists, psychiatrists, psychologists, as well as biomedical engineers, who are working on EEG and ERP analysis methods and developing novel clinical instrumentation. In addition, this book can be used as a reference book for graduate students in neural engineer

Dr. Nidal Kamel received his PhD (Hons) from the Technical University of Gdansk, Poland, in 1993. Since 1993 he has been involved in research projects related to brain signal processing, estimation theory, noise reduction, optimal filtering, and pattern recognition. His present research includes developing a technique for epileptic seizure detection, biomarkers for stress and major depressive disorder, and a high resolution technique for brain sources localization. Dr. Kamel is an associate professor at Universiti Teknologi PETRONAS and he is the leader of Neuro-Signal Processing Group at the Center of Image and Signal Intelligent Research (CISIR). In addition, he has published more than 150 research articles in various publications.


Dr. Aamir Saeed Malik

received his PhD in information and mechatronics from Gwangju Institute of Science & Technology in South Korea. Dr. Malik is an associate professor at the Department of Electrical and Electronic Engineering and director of mission oriented research biomedical technology at Universiti Teknologi PETRONAS. He has more than 200 publications in journals and conferences, three books, 16 patents, 34 awards and a cumulative impact factor greater than 150. His research interests include biomedical signal and image processing, and computer vision. He developed methods for acne grading, partial epileptic seizure prediction, tracking EEG signals and biomarkers for major depressive disorder.