Classification model of arousal and valence mental states by EEG signals analysis and Brodmann correlations

Abstract

This paper proposes a methodology to perform emotional states classification by the analysis of EEG signals, wavelet decomposition and an electrode discrimination process, that associates electrodes of a 10/20 model to Brodmann regions and reduce computational burden. The classification process were performed by a Support Vector Machines Classification process, achieving a 81.46 percent of classification rate for a multi-class problem and the emotions modeling are based in an adjusted space from the Russell Arousal Valence Space and the Geneva model.

Authors and Affiliations

Adrian Aguinaga, Miguel Ramirez, Maria Flores

Keywords

Related Articles

Quadrant Based WSN Routing Technique By Shifting Of Origin

A sensor is a miniaturized, low powered (basically battery powered), limited storage device which can sense the natural phenomenon or things and convert it into electrical energy or vice versa using transduction process....

Analysis of Guess and Determined Attack on Non Linear Modified SNOW 2.0 Using One LFSR 

stream ciphers encrypt the data bit by bit. In this research a new model of stream cipher SNOW 2.0 has been proposed i.e. Non linear modified SNOW 2.0 using one Linear Feedback Shift Register (LFSR) with the embedding of...

Improving Seek Time for Column Store Using MMH Algorithm 

 Hash based search has, proven excellence on large data warehouses stored in column store. Data distribution has significant impact on hash based search. To reduce impact of data distribution, we have proposed Memor...

An Efficient Deep Learning Model for Olive Diseases Detection

Worldwide, plant diseases adversely influence both the quality and quantity of crop production. Thus, the early detection of such diseases proves efficient in enhancing the crop quality and reducing the production loss....

Comparative Analysis between a Photovoltaic System with Two-Axis Solar Tracker and One with a Fixed Base

In this article, the comparative analysis of the stored energies between a photovoltaic system with a two-axis solar tracker, controlled by Arduino with respect to the energy stored by a fixed-base photovoltaic system is...

Download PDF file
  • EP ID EP137750
  • DOI 10.14569/IJACSA.2015.060633
  • Views 96
  • Downloads 0

How To Cite

Adrian Aguinaga, Miguel Ramirez, Maria Flores (2015). Classification model of arousal and valence mental states by EEG signals analysis and Brodmann correlations. International Journal of Advanced Computer Science & Applications, 6(6), 230-238. https://europub.co.uk./articles/-A-137750