000			02247 a2200241 4500
008			250109b |||||||| |||| 00| 0 eng d
020			_a9783319476520
082			_a530.82 SIU
100			_aSiuly, Siuly
245			_aEEG signal analysis and classification: techniques and applications
260			_aCham, Switzerland: _bSpringer, _c2018.
300			_axiii, 256p.: _bill.; hbk.: _c24 cm.
440			_aHealth Information Science (HIS)
520			_aThis book presents advanced methodologies in two areas related to electroencephalogram (EEG) signals: detection of epileptic seizures and identification of mental states in brain computer interface (BCI) systems. The proposed methods enable the extraction of this vital information from EEG signals in order to accurately detect abnormalities revealed by the EEG. New methods will relieve the time-consuming and error-prone practices that are currently in use. Common signal processing methodologies include wavelet transformation and Fourier transformation, but these methods are not capable of managing the size of EEG data. Addressing the issue, this book examines new EEG signal analysis approaches with a combination of statistical techniques (e.g. random sampling, optimum allocation) and machine learning methods. The developed methods provide better results than the existing methods. The book also offers applications of the developedmethodologies that have been tested on several real-time benchmark databases. This book concludes with thoughts on the future of the field and anticipated research challenges. It gives new direction to the field of analysis and classification of EEG signals through these more efficient methodologies. Researchers and experts will benefit from its suggested improvements to the current computer-aided based diagnostic systems for the precise analysis and management of EEG signals. https://link.springer.com/book/10.1007/978-3-319-47653-7
650			_aImage and Speech Processing
650			_aSignal
650			_aHealth Informatics
650			_aArtificial Intelligence
650			_aBiomedical Engineering and Bioengineering
700			_a Li, Yan _eCo-author
700			_aZhang, Yanchun _eCo-author
942			_cTD _2ddc
999			_c61524 _d61524