EEG Signal Processing

Developing and understanding advanced signal processingtechniques for the analysis of EEG signals is crucial in the areaof biomedical research. This book focuses on these techniques,providing expansive coverage of algorithms and tools from the fieldof digital signal processing. It discusses their applications tomedical data, using graphs and topographic images to showsimulation results that assess the efficacy of the methods.

Additionally, expect to find:

• explanations of the significance of EEG signal analysis andprocessing (with examples) and a useful theoretical andmathematical background for the analysis and processing of EEGsignals;
• an exploration of normal and abnormal EEGs, neurologicalsymptoms and diagnostic information, and representations of theEEGs;
• reviews of theoretical approaches in EEG modelling, such asrestoration, enhancement, segmentation, and the removal ofdifferent internal and external artefacts from the EEG and ERP(event-related potential) signals;
• coverage of major abnormalities such as seizure, and mentalillnesses such as dementia, schizophrenia, and Alzheimer’sdisease, together with their mathematical interpretations from theEEG and ERP signals and sleep phenomenon;
• descriptions of nonlinear and adaptive digital signalprocessing techniques for abnormality detection, sourcelocalization and brain-computer interfacing using multi-channel EEGdata with emphasis on non-invasive techniques, together with futuretopics for research in the area of EEG signal processing.