Access Restriction

Author Sukanesh, R. ♦ Harikumar, R.
Sponsorship IEEE Region 10
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2008
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Decision trees ♦ Classification tree analysis ♦ Epilepsy ♦ Electroencephalography ♦ Humans ♦ Open wireless architecture ♦ Decision making ♦ Public healthcare ♦ Immune system ♦ Medical treatment ♦ Hierarchical Decision Trees ♦ EEG Signals ♦ Epilepsy Risk Levels ♦ Fuzzy Logic
Abstract The purpose of this paper is to identify the practicability of hierarchical soft (max-min) decision trees in optimization of fuzzy outputs in the classification of epilepsy risk levels from EEG (Electroencephalogram) signals. The fuzzy pre classifier is used to classify the risk levels of epilepsy based on extracted parameters like energy, variance, peaks, sharp and spike waves, duration, events and covariance from the EEG signals of the patient. Hierarchical soft decision tree (post classifier with max-min criteria) four types are applied on the classified data to identify the optimized risk level (singleton) which characterizes the patientpsilas risk level. The efficacy of the above methods is compared based on the bench mark parameters such as performance index (PI), and quality value (QV). A group of ten patients with known epilepsy findings are used for this study. High PI such as 95.88 % was obtained at QVpsilas of 22.43 in the hierarchical decision tree optimization when compared to the value of 40% and 6.25 through fuzzy classifier respectively. It is identified the hierarchical soft decision tree (Hier & h min-max) method is a good post classifier.
Description Author affiliation: Bannari Amman Inst. of Technol., Sathyamangalam (Harikumar, R.) || Dept. of ECE, Thiagarajar Coll. of Eng., Madurai (Sukanesh, R.)
ISBN 9781424424085
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-11-19
Publisher Place India
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 202.82 kB
Page Count 6
Starting Page 1
Ending Page 6

Source: IEEE Xplore Digital Library