NDLI: Rhythm-based features for classification of focal and non-focal EEG signals

Content Provider	IET Digital Library
Author	Bajaj, Varun Rai, Khushnandan Kumar, Anil Sharma, Dheeraj Singh, Girish Kumar
Abstract	Electroencephalogram (EEG) contains five rhythms, which provide details about various activities of brain. These rhythms are separated using Hilbert–Huang transform for classification of focal and non-focal EEG signals. For this, the EEG signal is disintegrated into narrow bands intrinsic mode functions (IMFs) using empirical mode decomposition, and analytic representation of IMFs is computed by Hilbert transformation that helps to extract instantaneous frequencies of respective IMFs. Frequency bands of EEG signals known as rhythms are separated from analytic IMFs using instantaneous frequencies. Two efficient parameters Pearson product-moment correlation coefficient and Spearman rank correlation coefficient extracted from the rhythms are used with different kernel functions of least-squares support vector machine for the classification of focal and non-focal EEG signals. Thus, obtained results show improved performance of proposed method as compared to other existing methods.
Starting Page	743
Ending Page	748
Page Count	6
ISSN	17519675
Volume Number	11
e-ISSN	17519683
Issue Number	Issue 6, Aug (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/11/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2016.0435
Journal	IET Signal Processing
Publisher Date	2017-04-20
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Analytic Representation Bioelectric Signal Biology And Medical Computing Brain Activities Correlation Method Digital Signal Processing Electrical Activity in Neurophysiological Processes Electrodiagnostics And Other Electrical Measurement Technique Electroencephalogram Electroencephalography Empirical Mode Decomposition Feature Extraction Focal EEG Signal Classification Function Theory And Analysis Hilbert Transform Hilbert–Huang Transform IMF Integral Transforms Interpolation And Function Approximation Intrinsic Mode Function Knowledge Engineering Technique Least Squares Approximation Least-squares Support Vector Machine Medical Signal Processing Numerical Analysis Numerical Approximation And Analysis Pearson Product-moment Correlation Coefficient Rhythm-based Feature Signal Classification Signal Processing And Detection Signal Representation Spearman Rank Correlation Coefficient Support Vector Machine
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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