R E S E A R C H   A R E A S

Benefits and Risks of Augmentation Technology for Humans

Emerging technologies, such as extended reality (XR), exoskeletons, and wearable robots, extend and enhance human capabilities to assist with task performance and improve health, well-being, and safety. However, there could be unforeseen hazards and adverse consequences these novel technologies bring to individuals, communities, and society. Our research aims to investigate the impact of augmentation technology on cognitive functions, behavioral and neural changes, and safety outcomes, with a goal of expanding its benefits while mitigating potential risks.

Impact of Assistive Technology on Worker Safety, Health, and Well-being

Assistive technology provides a broad range of support for persons with sensory, cognitive, and physical impairments and helps them perform cognitively and physically demanding tasks more successfully and safely in workplaces. Our research aims to identify factors impacting users’ interaction with assistive technology, assess user perceptions and attitudes toward assistive technology, and investigate its impact on psychosocial outcomes, such as retirement intentions, occupational self-efficacy, and workplace ageism.

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

Technology to Improve Cognitive Health and Safety of Older Adults

Age-related declines in attentional and cognitive functions may impair everyday and workplace task performance and increase health and safety risks among older adults. Our research aims to understand how attentional and cognitive functions change with increasing age and its impacts on public and workplace safety and to develop cognitive and skill training tools using rapidly advancing technologies, such as virtual reality (VR).

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

Driving is a complex task requiring various perceptual, cognitive, and motor abilities. 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

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

AVF-XR is an extended reality-based Attentional Visual Field (AVF) task: a beta version is currently available via Github.

Wearable Robot Perception (WeaR-P)  questionnaire is to assess a current or future user’s multi-dimensional perception of wearable robots PDF.

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

• fNIRS (Functional Near-Infrared Spectroscopy): NIRx Technologies 8 x 8 wireless NIRSport2
• Collaborative Robot: Universal Robots UR5, Robotiq Hand-E Gripper
• Exoskeletons
  • Powered (active): Dephy ExoBoots, EduExo
  • Unpowered (passive): Levitate AIRFRAME®, SuitX LegX and BackX
• Extended Reality (XR) Head-Mounted Display (HMD)
  • Virtual Reality (VR): HTC Vive Pro, HTC Vive Pro Eye, Steam Valve Index
  • Augemented Reality (AR): Microsoft Hololens2, Meta Quest 3
• Alienware Aurora Computers: R8, R12
  
• Eye-Trackers: Pupil Labs Core, Pupil Labs VR add-on
• Driving Simulator: STISIM M2000
• Depth Camera: Intel® RealSense™ D435 | D455
• UHCOTech HeadSpot

Software

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