Songs induced mood recognition system using EEG signals.

BACKGROUND: Brain computer interfacing is a system that acquires and analyzes neural signals to create a communication channel directly between the brain and the computer. The EEG records the electrical fields generated by the nerve cells. With the help of Fourier Transformation the EEG signals are classified into four different frequency bands. PURPOSE: The main purpose of the present paper is to report results related to classification of EEG signals of different people subjected to different conditions. METHODS: The experiment has been done on 10 subjects having activities related to hearing music chosen from categories of patriotic, happy, romantic and sad songs along with relaxation activity. 19 electrodes have been used under (10-20) International Standard. The δ, θ α and ß components of EEG signals to these activities have been determined. Different statistical methods including linear discriminate analysis have been tested for classification. RESULTS: Result of the Linear Discriminant Analysis (LDA) made four groups of all modes (Relaxation, Happy, Sad, Patriotic and Romantic Song) labeled group1, Group2, Group3 and Group4 of all ten electrodes for Delta, Theta, alpha and Beta frequencies. CONCLUSION: The study may be used for the development of activities induced mood recognition (AIMR) system from the EEG signal.

Structural behavior of alcohol-1,4-dioxane mixtures through dielectric properties using TDR.

The values of complex permittivity for alcohol-1,4-dioxane (DX) mixtures with various concentrations have been determined in the frequency range 10 MHz to 20 GHz using the time domain reflectometry (TDR) method. Numbers of hydrogen bonds between alcohol-alcohol and alcohol-dioxane pairs are estimated from the values of the static dielectric constant by using the Luzar model. The model provides a satisfactory explanation of the experimental results related to the static dielectric constant. The binding energies for alcohol-alcohol (pair 11) and alcohol-DX (pair 12) are estimated to be -13.98 and -16.25 kJ/mol, respectively. The results have also been compared with previous results of the ethyleneglycol-DX system.

Dielectric properties of ethyleneglycol-1,4-dioxane mixtures using TDR method.

Complex permittivity has been determined for mixtures of ethyleneglycol-1,4-dioxane (EG-DX) with various concentrations in the frequency range from 100 MHz to 30 GHz at 25 degrees C by time domain reflectometry (TDR). A primary process with an asymmetric shape and a Debye-type small-amplitude high-frequency process are observed for each mixture. The deviation of the relaxation time for the primary process from that of the ideal mixture shows a maximum value at a mole fraction of 1,4-dioxane, xDX approximately =0.8. The static permittivity for the mixtures can be explained using the Luzar model by assuming the formation of two types of hydrogen-bonded dimers, one between EG-EG (pair 1) and the other between EG-DX (pair 2). The number of these pairs is also estimated as a function of concentration. These results of the relaxation time and static permittivity are interpreted on the basis of a model of two kinds of cooperative domains coexisting in the mixtures.