DocumentCode :
2418445
Title :
Analysis of EEG signals using Advanced Generalized Fractal Dimensions
Author :
Easwaramoorthy, D. ; Uthayakumar, R.
Author_Institution :
Dept. of Math., Deemed Univ., Dindigul, India
fYear :
2010
fDate :
29-31 July 2010
Firstpage :
1
Lastpage :
6
Abstract :
The Human Brain is a highly complex and a nonlinear system. The disorder in the Human Brain creates a lot of physiopathological diseases, especially the Epileptic Seizure. Electroencephalogram (EEG) was used by the physicians to diagnosis the patients who is suffering from Seizure. The Generalized Fractal Dimensions (GFD) is the measure of complexity and the chaotic behaviour (irregularity) of the Fractal Time Series (EEG Signals). We design the Advanced form of Generalized Fractal Dimensions to discriminate the Normal and Ictal EEGs and the comparison was done at last between the two methods namely Advanced GFD & GFD through graphical methods. Finally we conclude that there is significant differences between the Normal and Ictal EEGs in the Advanced GFD Method than the GFD Method by using the statistical tool called ANOVA Test. This multifractal technique is a very efficient tool in the Non-linear Analysis to analyze the EEG Signals and to detect or predict the state of illness of the Epileptic Patients.
Keywords :
diseases; electroencephalography; fractals; medical signal processing; statistical testing; time series; ANOVA test; EEG signal analysis; GFD method; advanced generalized fractal dimensions; chaotic behaviour; electroencephalogram; epileptic seizure patients; fractal time series; human brain; multifractal technique; nonlinear analysis; nonlinear system; physiopathological diseases; statistical tool; Analysis of variance; Electroencephalography; Entropy; Fractals; Mathematical model; Probability distribution; Time series analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing Communication and Networking Technologies (ICCCNT), 2010 International Conference on
Conference_Location :
Karur
Print_ISBN :
978-1-4244-6591-0
Type :
conf
DOI :
10.1109/ICCCNT.2010.5591775
Filename :
5591775
Link To Document :
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