NDLI: Identification of Visual Evoked Potentials in EEG detection by emprical mode decomposition

Content Provider	IEEE Xplore Digital Library
Author	Vergallo, P. Lay-Ekuakille, A. Giannoccaro, N.I. Trabacca, A. Labate, D. Morabito, F.C. Urooj, S. Bhateja, V.
Copyright Year	2014
Description	Author affiliation: Dept. of Electr. Eng., Gautam Buddha Univ., Noida, India (Urooj, S.; Bhateja, V.) \|\| IRCCS E. Medea, Sci. Inst. for Res., Brindisi, Italy (Trabacca, A.) \|\| Dept. DIMET, Mediterranea Univ., Reggio Calabria, Italy (Labate, D.; Morabito, F.C.) \|\| Dip. d'Ing. dell'Innovazione, Univ. of Salento, Lecce, Italy (Vergallo, P.; Lay-Ekuakille, A.; Giannoccaro, N.I.)
Abstract	Visual Evoked Potentials (VEPs) are referred to electrical potentials due to brief visual stimuli which can be recorded from scalp overlying visual cortex. A way to measure VEPs is through encephalogram (EEG). VEPs are very important because they can quantify functional integrity of the optic pathway. Their study allows to detect abnormalities that affect the visual pathways or visual cortex in the brain, and so methods that permit to identify VEPs components in EEG signals must be defined. However, the background activity measured from EEG hides VEPs components because they have a low voltage. So it is necessary to define a robust method to extract features, which best describe these potentials of interest. In this work Empirical Mode Decomposition (EMD) method is used to separate the EEG components and to detect VEPs. EMD decomposes a signal into components named Intrinsic Mode Functions (IFM). The results, obtained from the study of EEG records of a normal person, suggest that IMFs may be used to determine VEPs in EEG and to obtain important information related to brain activity by a time and frequency analysis of IMF components. It is well comparable with the known Wavelet Transform method, but it is characterized from a greater simplicity of implementation because the basis used in the analysis is generated by the same analyzed signal.
Sponsorship	IEEE Spain Sect. IE/PEL Joint Chapt.
Starting Page	1
Ending Page	5
File Size	1749963
Page Count	5
File Format	PDF
ISBN	9781479938667
DOI	10.1109/SSD.2014.6808848
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-02-11
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Integrated circuits Visualization Empirical Mode Decomposition Databases EEG Evoked Potentials Electrocardiography Monitoring
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

ECG classification with emprical mode decomposition denoised by wavelet transform

Analysis of EEG signals by emprical mode decomposition and mutual information

Detection of ECG beat using ensemble empirical mode decomposition

ECG-based personal identification using empirical mode decomposition and Hilbert transform

Detection of QRS complex in electrocardiogram signal by the empirical mode decomposition

Identification the limit of conscious perception of surface EEG signals with visual evoked potentials

Estimation of visual evoked potentials using a signal subspace approach

A new QRS detector based on empirical mode decomposition

Detection of steady-state visual evoked potentials in the eeg.

Identification of Visual Evoked Potentials in EEG detection by emprical mode decomposition

Similar Documents

ECG classification with emprical mode decomposition denoised by wavelet transform

Analysis of EEG signals by emprical mode decomposition and mutual information

Detection of ECG beat using ensemble empirical mode decomposition

ECG-based personal identification using empirical mode decomposition and Hilbert transform

Detection of QRS complex in electrocardiogram signal by the empirical mode decomposition

Identification the limit of conscious perception of surface EEG signals with visual evoked potentials

Estimation of visual evoked potentials using a signal subspace approach

A new QRS detector based on empirical mode decomposition

Detection of steady-state visual evoked potentials in the eeg.

Identification of Visual Evoked Potentials in EEG detection by emprical mode decomposition