I1.03 - NeuroErgonomics

EEG Data Collection Assessing Cognitive Fatigue.

Sponsor: Ingram School of Engineering
Student Team: Garrett Grose, Javier Espinosa, Jasmine Gillis, Cole Williamson 
Faculty Advisor: Dr. Michelle Londa

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I1.03 Logo

This project seeks to investigate how EEG data can be utilized to detect, and predict, cognitive fatigue in manual material handling workers. As the workforce progress throughout their workday, the employees become physically and mentally fatigued which can affect their work performance. Using an electroencephalography (EEG) device, brain data can be recorded as s subject simulates a work task. Understanding when an employee becomes mentally fatigued and how this can affect their physical performance is crucial in improving productivity in repetitive tasks on a factory floor.

I1.03 Poster Pitch

To view a PDF file of our poster, click the link below!

I1.03 Poster.pdf

Team Contact Information

I1.03 Team Photo
From left to right (Garrett Grose, Javier Espinosa, Jasmine Gillis, Cole Williamson)

Team Project Manager: Cole Williamson, caw281@txstate.edu

Faculty Advisor: Dr. Michelle Londa, ml40@txstate.edu


Let us know what you think! You can evaluate our project here: I1.03 Evaluation Form