Computational Intelligence Techniques in Diagnosis of Brain Diseases

1. Auflage 2018
ISBN: 978-981-10-6528-6
Verlag: Springer Nature B.V.

Buch, Englisch, 70 Seiten, Format (B × H): 154 mm x 238 mm, Gewicht: 1416 g

Reihe: SpringerBriefs in Applied Sciences and Technology

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.

Zielgruppe

Research

Autoren/Hrsg.

Gurumoorthy, Sasikumar

Muppalaneni, Naresh Babu

Gao, Xiao-Zhi

Fachgebiete

• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Neurologie, Klinische Neurowissenschaft

Inhaltsverzeichnis

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.

Über Autor(innen)

Dr. Sasikumar Gurumurthy is a professor at the Department of Computer Science and Systems engineering at Sree Vidyanikethan Engineering College in Tirupati. His current interests include soft computing and artificial intelligence in biomedical engineering, human and machine interaction and applications of intelligent system techniques, new user interfaces, brain-based interactions, human-centric computing, fuzzy sets and systems, image processing, cloud computing, content-based learning and social network analysis.

Dr Naresh Babu Muppalaneni is an associate professor at the Department of Computer Science and Systems Engineering at Sree Vidhyanikethan Engineering College in Tirupati. He has 10 years of teaching and research experience. He received a research grant from DST under the Young Scientist scheme to work on “Identifying single drug multiple targets for diabetes”. His research interests are cryptology, computer networks and computational systems biology.

Xiao-Zhi Gao received his B.Sc. and M.Sc. degrees from the Harbin Institute of Technology, China in 1993 and 1996, respectively. He earned a D.Sc. (Tech.) degree from the Helsinki University of Technology, Finland in 1999. He is currently a visiting researcher at the Machine Vision and Pattern Recognition Laboratory, Lappeenranta University of Technology, Finland. He is also a guest professor at Beijing Normal University, Harbin Institute of Technology, and Beijing City University, China. Dr. Gao has published more than 150 technical papers in refereed journals and for international conferences. He is an Associate Editor of the Journal of Intelligent Automation and Soft Computing and an editorial board member of the Journal of Applied Soft Computing, International Journal of Bio-Inspired Computation, and Journal of Hybrid Computing Research. Dr. Gao was the General Chair of the 2005 IEEE Mid-Summer Workshop on Soft Computing in Industrial Applications. His current research interests includeneural networks, fuzzy logic, evolutionary computing, swarm intelligence, and artificial immune systems, together with their applications in industrial electronics.