Date of Award

3-23-2017

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Systems Engineering and Management

First Advisor

Michael E. Miller, PhD.

Abstract

Brain-Computer Interfaces (BCIs) are systems that leverage user-brain activity to identify and perform specific functions. In applications requiring overt visual attention, focusing on visual stimuli with known temporal variation can elicit measurable changes in brain activity. However, elements of BCI applications can be intrusive. This research was designed to determine if Event-Related Potentials (ERPs), to include Steady-State Visually-Evoked Potentials (SSVEPs), could be elicited and interpreted from less obtrusive stimuli. Specifically, this research explores the use of variable frequency and long-wavelength (infrared) stimuli for SSVEP interpretation to explore the application of less obtrusive stimuli for application in BCIs. It was determined that increasing the primary wavelength of visual stimuli into the near infrared portion of the electromagnetic spectrum negatively impacts the observation of ERPs in human subjects. Additionally, the longer primary wavelengths of visual stimuli have a negative impact on the observation of target frequency band powers in SSVEP experiments. However, each of these signals were detected across the majority of participants for Light-Emitting Diodes (LEDs) with center frequencies as high as 770 nm and across some participants and conditions for LEDs with center frequencies as high as 830 nm.

AFIT Designator

AFIT-ENV-MS-17-M-195

DTIC Accession Number

AD1055210

Download

Share

COinS