Description
Brain Seizure Detection and Classification Using EEG Signals
Authors: Harpale Varsha K., Bairagi Vinayak
Language: EnglishSubjects for Brain Seizure Detection and Classification Using EEG Signals:
Keywords
discrete wavelet transform (DWT); electroencephalography (EEG); empirical mode decomposition (EMD); epilepsy; fuzzy classifier; machine learning approach; machine learning classifier; nonepileptic seizures (NES); pattern adapted wavelet transform (PAWT); preseizure detection; psychogenic nonepileptic seizures (PNES); seizure classification; seizure detection; seizure prediction; singular spectrum empirical mode decomposition (SSEMD); singular spectrum empirical wavelet transform (SSEWT); singular spectrum-based empirical mode decomposition (SSEMD); singular spectrum-based empirical wavelet transform (SSEWT)
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In Print (Delivery period: 14 days).
Add to cart the book of Harpale Varsha K., Bairagi Vinayak176 p. · 15x22.8 cm · Paperback
Description
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Brain Seizure Detection and Classification Using Electroencephalographic Signals presents EEG signal processing and analysis with high performance feature extraction. The book covers the feature selection method based on One-way ANOVA, along with high performance machine learning classifiers for the classification of EEG signals in normal and epileptic EEG signals. In addition, the authors also present new methods of feature extraction, including Singular Spectrum-Empirical Wavelet Transform (SSEWT) for improved classification of seizures in significant seizure-types, specifically epileptic and Non-Epileptic Seizures (NES). The performance of the system is compared with existing methods of feature extraction using Wavelet Transform (WT) and Empirical Wavelet Transform (EWT).
The book's objective is to analyze the EEG signals to observe abnormalities of brain activities called epileptic seizure. Seizure is a neurological disorder in which too many neurons are excited at the same time and are triggered by brain injury or by chemical imbalance.
1. Introduction2. EEG processing and artifact removal3. Seizure detection4. Seizure prediction5. Seizure classification6. Result and discussion
Dr. Vinayak K. Bairagi, is a recognized PhD guide in Savitribai Phule Pune University. He is working as Professor at Department of E electronics and Telecommunication Engg. and actively working as Chairman, IEEE Signal Processing Society Pune Chapter. He has teaching experience of 14 years and research experience of 10 years. He has filed 12 patents and 5 copyrights in technical field. He has published more than 70 papers. He has received IEI national level Young Engineer Award (2014) and ISTE national level Young Researcher Award (2015) for his excellence in the field of engineering. He also has 5 books and 6 book chapters on his credits. His area of interest is Biomedical Signal Processing and Brain Imaging.
- Presents EEG signal processing and analysis concepts with high performance feature extraction
- Discusses recent trends in seizure detection, prediction and classification methodologies
- Helps classify epileptic and non-epileptic seizures where misdiagnosis may lead to the unnecessary use of antiepileptic medication
- Provides new guidance and technical discussions on feature-extraction methods and feature selection methods based on One-way ANOVA, along with high performance machine learning classifiers for classification of EEG signals in normal and epileptic EEG signals, and new methods of feature extraction developed by the authors, including Singular Spectrum-Empirical Wavelet