R E S E A R C H   A R E A S

Emerging Technologies and Safety

Emerging technologies, such as collaborative robots, exoskeletons, virtual and augmented reality technologies, have the potential to improve productivity and reduce worker health and safety risk exposures. However, there are concerns for worker safety and health due to the potential for unforeseen hazards and adverse consequences involving the rapidly advancing technologies and increasing cognitive demands for workers. Our research aims to investigate the effects of emerging workplace technologies on attentional and cognitive performance, as well as the potentials and concerns associated with the technologies for worker safety.

Driving Safety

Driving is a complex task requiring various aspects of sensory, perceptual, cognitive, and motor abilities. Attentional and cognitive failures during driving due to internal and external distractions are one of the leading causes of crashes. Our research aims to investigate the precise relationships between different aspects of attentional and cognitive deficits and increased crash risks in various traffic situations and driver conditions. We are especially interested in older drivers and motor vehicle safety at work.  

Source: U.S. Census Bureau, 1960 to 2000, Decennial Censuses; 2010 American Community Survey; 2020 to 2060, 2017 National Population Projections.

Cognitive Aging and Safety

Age-related declines in attentional and cognitive functions may impact everyday and workplace task performance and increase health and safety risks at work. Our research aims to investigate how attentional and cognitive functions change with increasing age and understand the impacts of cognitive aging on public and workplace safety.

C U R R E N T   P R O J E C T   H I G H L I G H T S

Cognitive Fit of Exoskeletons

​Exoskeletons, or wearable technologies, may have adverse effects on the user’s cognitive performance during, and after, wearing them. This research project investigates the effects of wearing exoskeletons on cognitive loads and attentional distribution, using a multifaceted approach of self-reported, behavioral performance, and eye-tracking measures. The expected outcome includes the development of standards for test methods and measures for evaluating the cognitive fit of exoskeletons.  

This project is supported by ASTM International Exo Technology Center of Excellence (CoE). 

Oil & Gas Industry Driver Safety

Rapid growth of the oil and gas industry in the South Plains of Texas has led to increased crash risks among the truck drivers in the region. This research project aims to investigate the effects of driver characteristics on crash risks, with a focus on driving situations that are most relevant to the oil and gas industry and West Texas road environments. This research will contribute to the development of a fitness-to-drive measure and personalized training for at-risk drivers in the oil and gas industry.

This project is supported by The CH Foundation.

Human-Robot Communication

During human-robot interaction, robots need to detect and understand human commands, behaviors, and states, but they also must share relevant information, such as current status, cued actions, and intent and goal, with the human users. This project aims to develop and evaluate different robot-to-human communication modalities and message types for safety communication using virtual simulation. This study will examine the communication effectiveness and its impacts on user perceptions of robots.  

This project is supported by the
National Institute for Occupational Safety and Health (NIOSH).

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 R E S E A R C H   T O O L S developed by our lab

AFDQ Attentional Failures during Driving Questionnaire is a self-reported fitness-to-drive assessment tool.
                  PDF | EXCEL

AVF-VR/AVF-AR Virtual and augmented reality-based Attentional Visual Field (AVF) tasks will be available via Github soon.

A V A I L A B L E    E Q U I P M E N T   &   R E S O U R C E S

Hardware

• Collaborative Robot and Accessories: Universal Robots UR5, Robotiq Hand-E Gripper
• Exoskeletons: Levitate AIRFRAME®, SuitX LegX and BackX, EduExo Kit
• VR/AR Headsets: HTC Vive Pro, HTC Vive Pro Eye, Microsoft Hololens2, Steam Valve Index
• Eye-Trackers: Pupil Labs Core, Pupil Labs VR add-on
  
• Driving Simulator: STISIM M2000
  
• Depth Camera: Intel® RealSense™ D435
  

Software

• Statistics: SPSS, MPlus
• Experiment Design: E-Prime
• Body Tracking: Cubemos Skeleton Tracking SDK, Nuitrack