NDLI: EEG Spike Detection Technique Using Output Correlation Method: A Kalman Filtering Approach

Content Provider	Springer Nature Link
Author	Garg, Harish Kumar Kohli, Amit Kumar
Copyright Year	2015
Abstract	This correspondence presents a technique for the electroencephalogram (EEG) spike enhancement and detection, which uses the Kalman filtering (KF) approach based on the output correlation method for the nonstationary signal enhancement. We describe the nonstationary EEG signal in terms of the general Markov model, in which the parameters are considered to be time-varying. In the proposed methodology, neither the process and measurement noise statistics nor the initial Kalman blending factor are stringently required. The EEG epileptic spikes (ESs) are pre-emphasized using the output correlation method, and subsequently, the detection is performed using the decision threshold based on the output of same adaptive filter. We have tested the proposed scheme on the synthetic EEG signal corrupted with randomly occurring triangular spikes. The presented simulation results manifest significant improvement in the signal-to-noise ratio (SNR) due to the modified estimation of time-varying parameters of the general Markov model, which in turn leads to the alleviated number of false-positives (FPs). It is apparent that the real-time EEG signal (rat data) can be analyzed using the proposed EEG epileptic spike enhancement and detection adaptive scheme, which outperforms the conventional KF technique under the different SNR conditions. At 10 dB SNR, the output correlation method provides approximately 40 % reduction in FPs for the triangular spikes in synthetic EEG signal and approximately 27.5 % reduction in FPs for ESs in the rat data as compared to the conventional KF scheme.
Starting Page	2643
Ending Page	2665
Page Count	23
File Format	PDF
ISSN	0278081X
Journal	Circuits, Systems, and Signal Processing
Volume Number	34
Issue Number	8
e-ISSN	15315878
Language	English
Publisher	Springer US
Publisher Date	2015-02-06
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Electroencephalogram (EEG) Epileptic spikes (ESs) Kalman filter (KF) Correlation Time-varying environments/channels Adaptive signal processing Markov model Circuits and Systems Electrical Engineering Signal, Image and Speech Processing Electronics and Microelectronics, Instrumentation
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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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