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Brain Seizure Detection and Classification Using EEG Signals

Brain Seizure Detection and Classification Using Electroencephalographic Signals presents EEG signal processing and analysis with high;

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EEG Brain Signal Classification for Epileptic Seizure Disorder Detection

EEG Brain Signal Classification for Epileptic Seizure Disorder Detection provides the knowledge necessary to classify EEG brain signals;

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Epileptic Seizures and the EEG

address the problem from an interdisciplinary perspective. Epileptic Seizures and the EEG: Measurement, Models, Detection and Prediction brings;

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EEG Signal Analysis and Classification

This book presents advanced methodologies in two areas related to electroencephalogram (EEG) signals: detection of epileptic seizures and;

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EEG-Based Brain-Computer Interfaces

EEG-Based Brain-Computer Interface: Cognitive Analysis and Control Applications provides a technical approach to using brain signals for;

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Biomedical Signal Processing for Healthcare Applications

-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases;

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Introduction to EEG- and Speech-Based Emotion Recognition

Introduction to EEG- and Speech-Based Emotion Recognition Methods examines the background, methods, and utility of using;

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EEG Signal Processing

attention, sleep apnoea; person authentication; handedness detection, Parkinson's disease, motor imagery, smart air travel support and brain signal;

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Brain Signals

by MEG and EEG. The book first provides a brief introduction to brain states and the early history of EEG and MEG, describes the generation;

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EEG-Based Diagnosis of Alzheimer Disease

extraction and classification of Alzheimer's Disease using EEG signals. This book brings together the use of different EEG features, such as linear;

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Analysis and Classification of EEG Signals for Brain-Computer Interfaces

of human brain work, to the use of Moore-Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG;

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Analysis and Classification of EEG Signals for Brain Computer Interfaces

of human brain work, to the use of Moore-Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG;

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Adaptive Processing of Brain Signals

understanding and analysis of brain signals. No attempt is made to comment on physiological aspects of brain activity; instead, signal processing;

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MEG-EEG Primer

difference between the methods is that skull and scalp dampen and smear EEG signals, but do not affect MEG. Hence, to fully understand brain;

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KNN Classifier and K-Means Clustering for Robust Classification of Epilepsy from EEG Signals. A Detailed Analysis

Knn Classifier and K-Means Clustering Fo;

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Neural Engineering Techniques for Autism Spectrum Disorder

Spectrum Disorder (ASD), including brain signal analysis, EEG analytics, feature selection, and analysis of blood oxygen level-dependent (BOLD;

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Comprehensive Analysis of Extreme Learning Machine and Continuous Genetic Algorithm for Robust Classification of Epilepsy from EEG Signals

Comprehensive Analysis of Extreme Learni is een boek van Harikumar Rajaguru;...

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Real Time BCI System Design to Control Arduino Based Speed Controllable Robot Us

processing module of brain-computer interfaces, and describes the various EEG-acquisition devices available and compares their features and;

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Comprehensive Analysis of Swarm Based Classifiers and Bayesian Based Models for Epilepsy Risk Level Classification from EEG Signals

Comprehensive Analysis of Swarm Based Cl is een boek van Harikumar Rajaguru;...

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Introduction to Non-Invasive EEG-Based Brain-Computer Interfaces for Assistive Technologies

of experience working on these interfaces. The author provides a review of the human brain and EEG signals, describing the human brain, anatomically and;

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Reading EEGs

Focusing on stepwise development of concepts, pattern recognition and integration with clinical practice, Reading EEGs: A Practical;

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Epilepsy Board Review

diagnosis, classification and treatment are thoroughly covered, along with seizure classification, epidemiology, normal and abnormal EEG, and;

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Radar for Indoor Monitoring

key attributes of radar for in-door human monitoring, namely: motion classification including fall, detection of vital signs, and;

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Radar for Indoor Monitoring

key attributes of radar for in-door human monitoring, namely: motion classification including fall, detection of vital signs, and;

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Understanding Epilepsy

Neurology certification. Five sections comprise the main text: mechanisms, classification, EEG technical concepts, diagnostic tools, and management;

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EEG/ERP Analysis

Changes in the neurological functions of the human brain are often a precursor to numerous degenerative diseases. Advanced EEG systems and;

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EEG/ERP Analysis

Changes in the neurological functions of the human brain are often a precursor to numerous degenerative diseases. Advanced EEG systems and;

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