Ewha Med J.  2003 Jun;26(2):121-132. 10.12771/emj.2003.26.2.121.

Development of Computerized Tools for Nonlinear Analysis of EEG

Affiliations
  • 1Department of Neurology, College of Medicine, Ewha Womans University, Korea.
  • 2Department of Pathology, College of Medicine, Ewha Womans University, Korea.

Abstract


OBJECTIVES
EEG is a record of electronic signals of brain. If there are effective methods for analysis of EEG signal it can be used as a diagnostic tool for diseases related to brain function. We developed a new diagnostic system for analysis of EEG by using nonlinear dynamic theory.
METHODS
We made a basic computer program which was designed to analysis of pattern of EEG. For analysis of pattern, EEG signal was processed by variable experimental analytical methods and grouped by common pattern.
RESULTS
Program was composed of multiple systems. Signal generating system was composed of Lorenz signal generation and Rossler signal generation parts. EEG processing system was composed of Normalization, Band pass filtering, First Second difference, Add random noise and Sur-rogate making parts. EEG analyses system was composed of Spectral analyses, Phase space analyses, Correlation analyses and Mode analyses parts. Pattern recognition and grouping system was com-posed of data format, Power spectrum, Neural network process and Classification parts.
CONCLUSION
We developed a basic computer program for systemic analysis of EEG by Nonlinear analysis methods.

Keyword

EEG; Non linear analysis; Correlation dimension

MeSH Terms

Brain
Classification
Electroencephalography*
Noise
Nonlinear Dynamics
Full Text Links
  • EMJ
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr