Emotion detection via EEG analysis

Jeferson Gomez Lara and Andrés Ordóñez Bolaños, Universidad de Narño, San Juan de Pasto - Colombia, 2018

Electroencephalography (EEG) is a scanning technique based on the recording of electrical activity in the brain. Nowadays, on one hand, its practice has become more common in the field of engineering and its use has brought great advances in the field of neuro-rehabilitation of different limbs of the human body. On the other hand, several wrks have been developed for EEG signal analysis, aimed at recognizing brain activity for the development of brain-computer interfaces (BCI).

As well, studies have shown that human emotions can be determined by means of signals measured on the scalp, which have been used in the design of different types of brain-computer interface (BCI), computer-aided diagnosis systems, recognition of emotions, and automatic interpretation of actions/movements, among others. Nonetheless, despite several studies have been proposed, finding or selecting a method being optimal for the identification of emotions from EEG signals -taking into account aspects such as accuracy, computational cost and applications in real time- remains an open issue.

One of the main problems faced when classifying this type of signals is the nature of the emotions-driven signals, since they may be greatly similar to each other, and therefore the task of differentiating emotions is not trivial but challenging.

This study aims to establish important aspects for the comparison and selection of EEG signal analysis techniques. As well, it is intended to find a method reaching a good percentage of performance at the task of recognizing emotions through EEG signals.



Papers

Interpretación semántica computarizada de señales cerebrales para identificar emociones : Un estado del arte 

II Jornadas Internacionales de Investigación Científica y 1er Foro de Investigación "Desafíos Actuales de la Sociedad del Conocimiento"


Recognition of emotions using ICEEMD-based characterization of multimodal physiological signals 

LASCAS 2019

see full paper

Feature Extraction Analysis for Emotion Recognition from ICEEMD of Multimodal Physiological Signals

ACIIDS 2019Intelligent Information and Database Systems


Thesis


About us

Andrés Ordóñez
Bolaños
 
Jeferson Gomez 
Lara

Electronic Engineer Electronic Engineer
 oordonez@udenar.edu.co   jefersongomez008@gmail.com

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