Computational Intelligence Techniques in Diagnosis of Brain Diseases
Gurumoorthy, Sasikumar
Computational Intelligence Techniques in Diagnosis of Brain Diseases by Sasikumar Gurumoorthy, Naresh Babu Muppalaneni, Xiao-Zhi Gao. - 1 recurso en línea (XI, 70 páginas 35 ilustraciones, 7 ilustraciones a color.) - SpringerBriefs in Forensic and Medical Bioinformatics 2196-8845 Engineering (Springer-11647) .
1.Introduction -- 2.Analysis of Electroencephalogram (EEG) using ANN -- 3.Classification and Analysis of EEG using SVM and MRE -- 4.Intelligent Technique to Identify Epilepsy Captures Using Fuzzy System -- 5.Analysis of EEG to find Alzheimer's disease using Intelligent Techniques.
This book highlights a new biomedical signal processing method of extracting a specific underlying signal from possibly noisy multi-channel recordings, and shows that the method is suitable for extracting independent components from the measured electroencephalogram (EEG) signal. The system efficiently extracts memory spindles and is also effective in Alzheimer seizures. Current developments in computer hardware and signal processing have made it possible for EEG signals or "brain waves" to communicate between humans and computers - an area that can be extended for use in this domain.
9789811065293
10.1007/978-981-10-6529-3 doi
Inteligencia artificial
Neurología
Ingeniería biomédica
Q342 / .G878 2018 EB
Computational Intelligence Techniques in Diagnosis of Brain Diseases by Sasikumar Gurumoorthy, Naresh Babu Muppalaneni, Xiao-Zhi Gao. - 1 recurso en línea (XI, 70 páginas 35 ilustraciones, 7 ilustraciones a color.) - SpringerBriefs in Forensic and Medical Bioinformatics 2196-8845 Engineering (Springer-11647) .
1.Introduction -- 2.Analysis of Electroencephalogram (EEG) using ANN -- 3.Classification and Analysis of EEG using SVM and MRE -- 4.Intelligent Technique to Identify Epilepsy Captures Using Fuzzy System -- 5.Analysis of EEG to find Alzheimer's disease using Intelligent Techniques.
This book highlights a new biomedical signal processing method of extracting a specific underlying signal from possibly noisy multi-channel recordings, and shows that the method is suitable for extracting independent components from the measured electroencephalogram (EEG) signal. The system efficiently extracts memory spindles and is also effective in Alzheimer seizures. Current developments in computer hardware and signal processing have made it possible for EEG signals or "brain waves" to communicate between humans and computers - an area that can be extended for use in this domain.
9789811065293
10.1007/978-981-10-6529-3 doi
Inteligencia artificial
Neurología
Ingeniería biomédica
Q342 / .G878 2018 EB