Fisher Discriminant Analysis of EEG Data based on Drinking Events

نویسنده

  • Yuan Shi
چکیده

Objective: We have performed Fisher’s discriminant analysis to the EEG data of experimental subjects who were drunk on alcohol. The subjects of these experiments were recorded anonymously. The data has been used for feature extraction and classification decisions in order to determine the part of head electrode’s categories after alcohol intake and to explore the changes of EEG features. The calculation methods have been divided into four species In accordance with the strength of wave. The head electrodes have been used as a part of of 21 electrodes EEG data used for 6 subjects. We have performed Fisher’s discriminant analysis of the EEG data on the six subjects. After every 20 minutes 7.2 ml of alcohol was given to the subjects for drinking. The EEG data processing and statistical analysis adopted was independently designed regarding the EEG analysis toolbox and the program for correlation analysis. Results of the Fisher discriminant would be better applied to the feature extraction and classification decisions of the EEG data. Conclusions: EEG activity shows a significant response after alcohol intakes, electrode categories is noted to constantly change. After drinking 200 ml categories changes obviously, and drinking 600 ml category changes become calm. The changes found are not so obvious in men but are significantly obvious in women.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Study on Fisher Analysis of Electroencephalograph Data

Objective in this paper, we have done Fisher discriminant analysis to Electroencephalogram (EEG) data of experiment objects which are recorded impersonally, come up with a relatively accurate method used in feature extraction and classification decisions. The present study is the groundwork analysis for other analysis in EEG study. Methods In accordance with the strength of  wave, the head ele...

متن کامل

Optimized Seizure Detection Algorithm: A Fast Approach for Onset of Epileptic in EEG Signals Using GT Discriminant Analysis and K-NN Classifier

Background: Epilepsy is a severe disorder of the central nervous system that predisposes the person to recurrent seizures. Fifty million people worldwide suffer from epilepsy; after Alzheimer’s and stroke, it is the third widespread nervous disorder.Objective: In this paper, an algorithm to detect the onset of epileptic seizures based on the analysis of brain electrical signals (EEG) has b...

متن کامل

A review on EEG based brain computer interface systems feature extraction methods

The brain – computer interface (BCI) provides a communicational channel between human and machine. Most of these systems are based on brain activities. Brain Computer-Interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. The success of this methodology depends on the selection of methods to process the brain signals in each pha...

متن کامل

A review on EEG based brain computer interface systems feature extraction methods

The brain – computer interface (BCI) provides a communicational channel between human and machine. Most of these systems are based on brain activities. Brain Computer-Interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. The success of this methodology depends on the selection of methods to process the brain signals in each pha...

متن کامل

Classification of Motor Imagery EEG Signals Based on Time-Frequency Analysis

We describe a new technique for the classification of motor imagery electroencephalogram (EEG) recordings. The technique is based on a time-frequency analysis of EEG signals, regarding the relations between the EEG data obtained from the C3/C4 electrodes, the features were reduced according the Fisher distance. This reduced feature set is finally fed to a linear discriminant for classification....

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015