Date of Award

12-22-2016

Document Type

Thesis

Degree Name

Master of Science in Computer Engineering

Department

Department of Electrical and Computer Engineering

First Advisor

Brett J. Borghetti, PhD.

Abstract

In this thesis, the artefactual effects of the small muscle movements were investigated. Upper frequency bands (30 Hz) of the EEG signal were extracted in order to investigate the artefactual effects of the small muscle movements. When the contamination level is high, the detection of the small muscle artifact can be made with the 92.2% accuracy. If these artifacts are really small such as a single finger movement, the detection accuracy decreases to 64%. But, the detection accuracy increases to 72% after removing the eye blink artifacts. The results of the classification support our hypothesis about the artefactual effects of the small muscle movements.

AFIT Designator

AFIT-ENG-MS-16-D-051

DTIC Accession Number

AD1032001

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