NDLI: The preliminary study of EEG and ECG for epileptic seizure prediction based on Hilbert Huang Transform

Content Provider	IEEE Xplore Digital Library
Author	Phomsiricharoenphant, Worawich Ongwattanakul, Songpol Wongsawat, Yodchanan
Copyright Year	2014
Description	Author affiliation: Department of Biomedical Engineering, Mahidol University, Nakompathom, Thailand (Phomsiricharoenphant, Worawich; Ongwattanakul, Songpol; Wongsawat, Yodchanan)
Abstract	Epilepsy is a chronic brain disorder. The patient are suffer from the unpredictable seizure. The conventional method for studies the characteristic of epileptic seizure is measuring the Electroencephalogram (EEG). On the other side, there are some studies reported about the relation between heart rate from Electrocardiogram (ECG) and epileptic seizure. This paper is a preliminary study about EEG and ECG based epileptic seizure prediction. The feature extraction method is based on the Hilbert Huang Transform (HHT) and we try to indicate some phenomena of EEG and ECG before the seizure onset. We extract the mean instantaneous frequency from EEG and R-R interval from ECG. The result shows the mean instantaneous frequency in mode one of intrinsic mode function was significantly dropped down simultaneously with R-R interval variation before seizure onset, the prior time is around 130 second. So, we can conclude that there is a possibility to use these two feature as a indicator for early prediction.
Starting Page	1
Ending Page	4
File Size	343376
Page Count	4
File Format	PDF
ISBN	9781479968015
DOI	10.1109/BMEiCON.2014.7017433
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-11-26
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hilbert Huang Transform Epilepsy EEG Electrocardiography ECG Feature extraction Electroencephalography
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

Real-Time Seizure Detection Based on EEG and ECG Fused Features Using Gabor Functions

A proposed frame work for real time epileptic seizure prediction using scalp EEG

Automatic Prediction of Epileptic Seizure Using Kernel Fisher Discriminant Classifiers

Epileptic seizureprediction based on Hilbert Huang Transform and Artificial Neural Networks

Performance analysis of lifting based DWT and MLPNN for epilepsy seizure from EEG

Focal epileptic seizure forecasting in EEG signals using wavelet transform and artificial neural networks

Efficient EEG analysis for seizure monitoring in epileptic patients

Epileptic seizure prediction using the spatiotemporal correlation structure of intracranial EEG

EEG signal classification using frequency band analysis towards epileptic seizure prediction

The preliminary study of EEG and ECG for epileptic seizure prediction based on Hilbert Huang Transform

Similar Documents

Real-Time Seizure Detection Based on EEG and ECG Fused Features Using Gabor Functions

A proposed frame work for real time epileptic seizure prediction using scalp EEG

Automatic Prediction of Epileptic Seizure Using Kernel Fisher Discriminant Classifiers

Epileptic seizureprediction based on Hilbert Huang Transform and Artificial Neural Networks

Performance analysis of lifting based DWT and MLPNN for epilepsy seizure from EEG

Focal epileptic seizure forecasting in EEG signals using wavelet transform and artificial neural networks

Efficient EEG analysis for seizure monitoring in epileptic patients

Epileptic seizure prediction using the spatiotemporal correlation structure of intracranial EEG

EEG signal classification using frequency band analysis towards epileptic seizure prediction

The preliminary study of EEG and ECG for epileptic seizure prediction based on Hilbert Huang Transform