Exploring the possibilities of the Emotiv Insight: discriminating between left- and right-handed responses

Stoelinga, E. (2016) Exploring the possibilities of the Emotiv Insight: discriminating between left- and right-handed responses. Bachelor's Thesis, Artificial Intelligence.

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Abstract

A new low-cost EEG device has recently entered the market. The Emotiv Insight is a wireless 5 channel EEG headset which promises to provide meaningful EEG data during everyday use. The goal of this study was to determine whether its measurements can reliably be used in EEG research and whether the device can be used as a Brain Computer Interface. The Emotiv Insight was used to measure brain activity during an experiment in which participants were consecutively asked to move or imagine movement of either their left or their right hand. Previous EEG research has found that this causes a larger activity in the contralateral brain hemisphere. The data were used to examine whether similar significant differences of brain activity could be found with the Emotiv Insight. The statistical machine-learning methods ridge regression and LASSO were used to analyze whether classification in left and right trials was possible. No evident differences between conditions were found, only few significant short-lasting differences of activity regarding location between conditions were encountered. Furthermore, the differences that were encountered between conditions contradict previous well-grounded findings. No model fitted with ridge regression or LASSO was able to gain an accuracy higher than chance. The conclusions of this study are that measurements taken with the Emotiv Insight do not prove to be reliable for a classification task as simple as right versus left motor activity and that the device is not recommended as a Brain Computer Interface.

Item Type:	Thesis (Bachelor's Thesis)
Degree programme:	Artificial Intelligence
Thesis type:	Bachelor's Thesis
Language:	English
Date Deposited:	15 Feb 2018 08:14
Last Modified:	15 Feb 2018 08:14
URI:	https://fse.studenttheses.ub.rug.nl/id/eprint/14278

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