http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
EEG signal processing and machine learning
1 online resource (xxxiv, 714 pages) illustrations
"Electroencephalogram (EEG) signal processing is concerned with the development and application of advanced digital signal processing algorithms for analysis, quantification, separation, and classification of the impact of various brain abnormalities on the EEGs. Any medical or neurological condition that affects brain function will alter the EEG. Brain abnormalities introduce various rhythmic or arrhythmic effects on the signals. Moreover, most of the abnormalities in the human body directly or indirectly affect the brain and consequently change the EEG signals. Processing of biosignals using newly developed techniques have become a strong field of research and digital signal processing concepts have become part of the core training in biomedical engineering"--
Introduction to Electroencephalography -- EEG Waveforms -- EEG Signal Modelling -- Fundamentals of EEG Signal Processing -- EEG Signal Decomposition -- Chaos and Dynamical Analysis -- Machine Learning for EEG Analysis -- Brain Connectivity and Its Applications -- Event-Related Brain Responses -- Localization of Brain Sources -- Epileptic Seizure Prediction, Detection, and Localization -- Sleep Recognition, Scoring, and Abnormalities -- EEG-Based Mental Fatigue Monitoring -- EEG-Based Emotion Recognition and Classification -- EEG Analysis of Neurodegenerative Diseases -- EEG As A Biomarker for Psychiatric and Neurodevelopmental Disorders -- Brain-Computer Interfacing Using EEG -- Joint Analysis of EEG and Other Simultaneously Recorded Brain Functional Neuroimaging Modalities -- Index
Includes bibliographical references and index.