Neuropsychological Assessment of Fatigue Utilizing Eye-Tracking Data
Department
Business and Information Technology
Major
Information Science and Technology
Research Advisor
Nah, Fiona Fui-Hoon, 1966-
Advisor's Department
Business and Information Technology
Funding Source
Laboratory for Information Technology Evaluation
Abstract
Fatigue is one of the leading causes of workplace incidents and car accidents and a rising safety issue for many industries. Many factors can be a source of fatigue, including sleep deprivation and prolonged mental and physical work. Negligence in effectively dealing with fatigue can have enormous consequences, ranging from economic loss due to a lack of productivity, to more extreme outcomes such as death. Therefore, it is essential to gain a better understanding on how to effectively detect fatigue.
The goal of this project is to isolate and determine how eye-tracking data can be used to assess fatigue in a person. Through this, we can better understand the neuropsychological signs of fatigue, and implement measures to improve safety and performance. The results of this research aim to minimize the risk of fatigue-related errors and accidents.
Biography
Luis Emmanuel Ocampo is a freshman in Information Science and Technology from Chesterfield, Missouri. He works as an assistant lab manager at the Laboratory for Information Technology Evaluation (LITE) and is webmaster for the Formula SAE design team. He is also a member of the Missouri S&T Chapter of the Association of Computing Machinery, the Thomas Jefferson Hall Association, and the Chancellor’s Leadership Academy.
Research Category
Social Sciences
Presentation Type
Poster Presentation
Document Type
Poster
Location
Upper Atrium
Presentation Date
17 Apr 2018, 9:00 am - 12:00 pm
Neuropsychological Assessment of Fatigue Utilizing Eye-Tracking Data
Upper Atrium
Fatigue is one of the leading causes of workplace incidents and car accidents and a rising safety issue for many industries. Many factors can be a source of fatigue, including sleep deprivation and prolonged mental and physical work. Negligence in effectively dealing with fatigue can have enormous consequences, ranging from economic loss due to a lack of productivity, to more extreme outcomes such as death. Therefore, it is essential to gain a better understanding on how to effectively detect fatigue.
The goal of this project is to isolate and determine how eye-tracking data can be used to assess fatigue in a person. Through this, we can better understand the neuropsychological signs of fatigue, and implement measures to improve safety and performance. The results of this research aim to minimize the risk of fatigue-related errors and accidents.
