This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal processing in a comprehensive, simple, and easy-to-understand manner. EEG records the electrical activity generated by the firing of neurons within human brain at the scalp. They are widely used in clinical neuroscience, psychology, and neural engineering, and a series of EEG signal-processing techniques have been developed. Intended for cognitive neuroscientists, psychologists and other interested readers, the book discusses a range of current mainstream EEG signal-processing and feature-extraction techniques in depth, and includes chapters on the principles and implementation strategies.
This book focuses on these techniques, providing expansive coverage of algorithms and tools from the field of digital signal processing.
This edited book presents state of the art aspects of EEG signal processing methods, with an emphasis on advanced strategies, case studies, clinical practices and applications such as EEG for meditation, auditory selective attention, sleep ...
This book is intended to provide an introduction to and summary of essentially all major aspects of BCI research and development.
The book covers the feature selection method based on One-way ANOVA, along with high performance machine learning classifiers for the classification of EEG signals in normal and epileptic EEG signals.
This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis.
From the table, we can observe that, many researchers also focused on EEG relative power, coherence-based features, phase synchrony features in frequency domain. ... Quantitative EEG Event-Related Potentials and Neurotherapy.
Many more biomedical signal processing implementations are in place using machine learning methods. This is the inspiration in adopting machine learning approach for analysing EEG signal data for epileptic seizure detection.
This two-volume book provides an insight into the 10th International Conference on Soft Computing for Problem Solving (SocProS 2020).
This two-volume book constitutes the refereed proceedings of the 3rd International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021, held in April 2021. Due to the COVID-19 pandemic the conference was held virtually.
2009), composite CSP (method 2, n = 3) (Kang et al. 2009), R-CSP (Lu et al. 2009) and SSFO (Yong et al. 2008). As shown in Fig. 8.6, compared to the four existing methods, the proposed algorithm yields the best accuracy for Subjects 1, ...