A Neural Networks Approach to EEG Signals Modeling

Hasan A. Al-Nashash; A. M S Zalzala; Nitish V. Thakor

A Neural Networks Approach to EEG Signals Modeling

Hasan A. Al-Nashash, A. M S Zalzala, Nitish V. Thakor

School of Engineering & Physical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

In this paper, a comparison of the application of neural networks and a first order Markov process amplitude model are reported for the modelling of electoencephalography (EEG) signals recorded from a controlled experimental setup of rodent brain injury with hypoxic-ischemic cardiac arrest. The NN model was found to be superior in modeling the nonlinearities of EEG signal variations.

Original language	English
Title of host publication	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Pages	2451-2454
Number of pages	4
Volume	3
Publication status	Published - 2003
Event	A New Beginning for Human Health: the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Cancun, Mexico Duration: 17 Sept 2003 → 21 Sept 2003

Conference

Conference	A New Beginning for Human Health: the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Country/Territory	Mexico
City	Cancun
Period	17/09/03 → 21/09/03

Keywords

Brain Injury
Cardiac Arrest
EEG
Markov
Modeling
Neural Networks

Cite this

@inproceedings{fa72d0880d1a4d62bb830717ff2a5155,

title = "A Neural Networks Approach to EEG Signals Modeling",

abstract = "In this paper, a comparison of the application of neural networks and a first order Markov process amplitude model are reported for the modelling of electoencephalography (EEG) signals recorded from a controlled experimental setup of rodent brain injury with hypoxic-ischemic cardiac arrest. The NN model was found to be superior in modeling the nonlinearities of EEG signal variations.",

keywords = "Brain Injury, Cardiac Arrest, EEG, Markov, Modeling, Neural Networks",

author = "Al-Nashash, \{Hasan A.\} and Zalzala, \{A. M S\} and Thakor, \{Nitish V.\}",

year = "2003",

language = "English",

volume = "3",

pages = "2451--2454",

booktitle = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

note = "A New Beginning for Human Health: the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society ; Conference date: 17-09-2003 Through 21-09-2003",

}

Al-Nashash, HA, Zalzala, AMS & Thakor, NV 2003, A Neural Networks Approach to EEG Signals Modeling. in Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. vol. 3, pp. 2451-2454, A New Beginning for Human Health: the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Cancun, Mexico, 17/09/03.

TY - GEN

T1 - A Neural Networks Approach to EEG Signals Modeling

AU - Al-Nashash, Hasan A.

AU - Zalzala, A. M S

AU - Thakor, Nitish V.

PY - 2003

Y1 - 2003

N2 - In this paper, a comparison of the application of neural networks and a first order Markov process amplitude model are reported for the modelling of electoencephalography (EEG) signals recorded from a controlled experimental setup of rodent brain injury with hypoxic-ischemic cardiac arrest. The NN model was found to be superior in modeling the nonlinearities of EEG signal variations.

AB - In this paper, a comparison of the application of neural networks and a first order Markov process amplitude model are reported for the modelling of electoencephalography (EEG) signals recorded from a controlled experimental setup of rodent brain injury with hypoxic-ischemic cardiac arrest. The NN model was found to be superior in modeling the nonlinearities of EEG signal variations.

KW - Brain Injury

KW - Cardiac Arrest

KW - EEG

KW - Markov

KW - Modeling

KW - Neural Networks

UR - https://www.scopus.com/pages/publications/1542330938

M3 - Conference contribution

VL - 3

SP - 2451

EP - 2454

BT - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

T2 - A New Beginning for Human Health: the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 17 September 2003 through 21 September 2003

ER -

A Neural Networks Approach to EEG Signals Modeling

Abstract

Conference

Keywords

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