InTech, 2013, 270 pages, ISBN: 9535111344 9789535111344 The objective of this book is to discuss recent progress and future prospects of Brain-Computer Interface (BCI) systems. The topics discussed in this book are: important issues concerning end-users; approaches to interconnect a BCI system with one or more applications; several advanced signal processing methods; review of hybrid and wireless techniques used in BCI systems; and applications of BCI systems in epilepsy treatment and emotion detections. BCI systems allow communication based on a direct electronic interface which conveys messages and commands directly from the human brain to a computer. In the recent years, attention to this new area of research and the number of publications discussing different paradigms, methods, signal processing algorithms, and applications have been increased dramatically. Contents: Preface A User Centred Approach for Bringing BCI Controlled Applications to End-Users BCI Integration: Application Interfaces Adaptive Network Fuzzy Inference Systems for Classification in a Brain Computer Interface Bayesian Sequential Learning for EEG-Based BCI Classification Problems Optimal Fractal Feature and Neural Network: EEG Based BCI Applications Using Autoregressive Models of Wavelet Bases in the Design of Mental Task-Based BCIs Client-Centred Music Imagery Classification Based on Hidden Markov Models of Baseline Prefrontal Hemodynamic Responses Equivalent-Current-Dipole-Source-Localization-Based BCIs with Motor Imagery Sources of Electrical Brain Activity Most Relevant to Performance of Brain-Computer Interface Based on Motor Imagery A Review of P300, SSVEP, and Hybrid P300/SSVEP Brain-Computer Interface Systems Review of Wireless Brain-Computer Interface Systems Brain Computer Interface for Epilepsy Treatment Emotion Recognition Based on Brain-Computer Interface Systems Brain-Computer Interface (BCI) systems allow communication based on a direct electronic interface which conveys messages and commands directly from the human brain to a computer. In the recent years, attention to this new area of research and the number of publications discussing different paradigms, methods, signal processing algorithms, and applications have been increased dramatically. The objective of this book is to discuss recent progress and future prospects of BCI systems. The topics discussed in this book are: important issues concerning end-users; approaches to interconnect a BCI system with one or more applications; several advanced signal processing methods (i.e., adaptive network fuzzy inference systems, Bayesian sequential learning, fractal features and neural networks, autoregressive models of wavelet bases, hidden Markov models, equivalent current dipole source localization, and independent component analysis); review of hybrid and wireless techniques used in BCI systems; and applications of BCI systems in epilepsy treatment and emotion detections
