Author(s)

John LaRocco

Date Approved

9-21-2011

Document Type

Thesis

Degree Name

M.S. Engineering

Department

Electrical and Computer Engineering

College

Henry M. Rowan College of Engineering

First Advisor

Polikar, Robi

Subject(s)

Brain-computer interfaces;Meditation

Disciplines

Electrical and Computer Engineering

Abstract

The overall success of a brain computer interface (BCI) is largely dependent on the features used to make decisions. Noise in the electroencephalography (EEG) increases the difficulty of acquiring meaningful features. Previous literature suggests teaching subjects meditation and relaxation techniques may improve features relevant to BCI operation. The purpose of this study was to investigate performance on several cognitive protocols for both individuals who use meditation techniques and those who do not use these techniques. Both groups were given a motor imagery based BCI protocol, a P300 speller BCI, a verbal learning task, and an N-back test. No significant difference in performance was found between meditation and control groups. Our research does suggest however, significant differences for the P300 and motor imagery protocols may be found if a larger group (>20 subjects per class) is recruited.

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