EPOC Emotiv EEG Basics

TL;DR

This paper provides a beginner's guide to using the EPOC Emotiv EEG device for BCI research, including setup, basic analysis, and experiments detecting alpha waves and cognitive disturbances.

Contribution

It offers practical tutorials, code examples, and analysis methods for new users to perform EEG experiments with the EPOC Emotiv device.

Findings

Detection of visual occipital alpha waves (Berger Rhythm)

Reduction of alpha power during cognitive disturbances

Comparison of feature extraction and classification methods

Abstract

This document provides some basic guidance to start working with the EPOC Emotiv neuroheadset device and describes how to use it to perform basic Brain-Computer Interface (BCI) research. A brief tutorial on how to set up the device, from its electrophysiological point of view, as well as a description and practical code to perform some basic analysis, is explained. A basic experiment is introduced to detect one of the oldest and, indeed, quite still valuable electrophysiological correlate, visual occipital alpha waves, or Berger Rhythm. An additional experiment is expounded where the power spectrum of alpha waves is reduced when a subject is affected by background cognitive disturbances. This document also briefs about the extraction of information by using the EPOC Emotiv library and also with python Emokit package. This report presents a basic guide on how to use EEGLAB and MATLAB, as well as python stack to perform the neurophysiological analysis. Finally, a basic analysis on different feature extraction and classification methods is provided.