Research Visit of Ryan Thackston

Currently I'm working on programming the modules for the Brain-Computer Interface (BCI) framework in the Kiel Real-Time Applications Toolkit (KiRAT).

Magnetic sensors will be placed on the back of the head around the visual cortex and measure the magnetic fields of neurons firing. The subject will attentively look at an LED blinking 5 times a second. When the subject is attentively looking at the blinking LED, neurons in the visual cortex will also be firing off 5 times a second (or a multiple of 5 such as 10, 15, 20...etc). This is called a steady-state visually evoked potential (SSVEP). This firing in the visual cortex should be picked up by the magnetic sensors and through some processing, the SSVEP will be verified by the Brain-Computer Interface. When an it is verified that the visual cortex is also blinking 5 times a second (an SSVEP), a decision can be made. With several blinking LEDs in front of the subject ( 5 Hz, 7 Hz, 8.133 Hz, 9.4, 11 Hz), several actions can be made but the one LED that the subject is attentively focusing on will produce an SSVEP at the same rate the LED. If all LEDs are blinking but the subject isn't focusing on any of them, no action will be taken.

There will be 5 main modules for the BCI framework: - Preprocessing (to clean magnetic field signals and make easier for processing) - SSVEP Detector (detects if there is or isn't an SSVEP happening) - LED Control - controls the rate of blinking in each LED - Prompter - gives an audio message for the subject (Magnetic signals are not measured when on) - Main Control Unit (Saves data, performs actions based on the SSVEP detector, controls the LED Control & Prompter module, tells the SSVEP what LED frequency to look for)

The 5 modules have been programmed into KiRAT but are empty, right now I'm programming in the submodules. So for the preprocessing module, I'm programming in a highpass filter to remove drift noise from very low frequencies (100Hz). The SSVEP Detector and Main Control Unit modules will have other submodules with their own functionalities.

My task for this week has been to create a rough sketch of a prototype BCI Framework program using MATLAB. The first prototype will have Optically Pumped Magnetometers (OPM) placed on the back of the subject's skull measuring just above the visual cortex. A single blinking LED will be placed about 60 cm away from the subject who will be instructed to stare at the LED in order to produce an SSVEP in the visual cortex which can be measured by the OPM sensors. The MATLAB rough sketch will have 3 states - Standby, Processing, and Question. The Standby state will start the framework, clean variables and store data. The Processing state will process the data given, and the Question state will be for when a question is being asked to the subject.

Off campus, I was invited by some friends in my dorm to a session of Das Schwarze Auge (DSA). DSA is a table top game like Dungeons & Dragons and I had a great time meeting people and making new friends.

Monday I began going to the Medical Signal Processing Lab. Bus 60S is a direct route to the Faculty of Engenieerign ("Technische Fakultät" in German) of Kiel University (CAU). The bus ride takes about 50 - 60 Min so I practiced my German on Duolingo.

My thesis project will be to make a Brain-Computer Interface (BCI) framework that uses Optically Pumped Magnetometers (OPMs) to detect Steady-State Visually Evoked Potentials (SSVEP) in the visual cortex caused by the user looking at a blinking LED. This week I did a literature review on SSVEP BCIs made in the past.

 

Ryan Thackston 

University of Houston
Houston, Texas, USA

Visiting period: October 2019 - February 2020

Topic: Brain computer interfaces using magnetic sensors

Supervisors: Christine Selhuber-Unkel, Gerhard Schmidt

Contact

sfb1261@tf.uni-kiel.de

Chairman:

Prof. Dr. Eckhard Quandt

Kiel University
Institute for Materials Science

 

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CAU

Christian-Albrechts-Universität zu Kiel (CAU)

Christ.-Albrechts-Platz 4
D-24118 Kiel

UKSH

University Hospital Schleswig-Holstein, Campus Kiel (UKSH)

Arnold-Heller-Straße 3
D-24105 Kiel

ISIT

Fraunhofer Institute for Silicon Technology, Itzehoe (ISIT)

Fraunhoferstrasse 1
D-25524 Itzehoe  

IPN

IPN - Leibniz-Institut für die Pädagogik der Naturwissenschaften und Mathematik an der Universität Kiel

Olshausenstraße 62 
D-24118 Kiel

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