AR technology and sensor-based motion & location tracking systems will be combined to provide fine-grained computer-generated 3D images and actual physical objects in real-time. The team technologically innovates an AR system by integrating a real-time motion-tracking sensor and an optical see-through head-mounted display (OST-HMD). 

In this study, we developed an interactive learning solution for engineering education by combining augmented reality (AR) and Near-Field Electromagnetic Ranging (NFER) technologies. We built an instructional system that integrates AR devices and real-time positioning sensors to improve the interactive experience of learners in an immersive learning environment. 

This study investigates the reliability of the Near-Field Electromagnetic Ranging (NFER) system in capturing the real-time location data of nurses’ workflow and sees whether the NFER system could be a new method to conduct a time-motion study in an intensive care unit (ICU). 

In this study, we have developed the gauge monitoring simulation and applied the eye and head tracking technology to assess the effectiveness of flow, level, pressure, and temperature gauge shapes developed by the Abnormal Situation Management Consortium. The primary objective of this research is to investigate the relationship between human perception stress (pupil diameter) and performance (sensitivity d’) in a process control monitoring task using the eye and head-integrated human-in-the-loop (HITL) simulation 

The primary objective of this research is to investigate the relationship between eye inter-fixation time and situation awareness in a dynamic control task. In this study, participants were trained to use the Anti-Air Warfare Coordinator (AAWC) simulation. According to the results, participants with relatively high levels of situation awareness show lower inter-fixation time than those with relatively low levels of situation awareness.

This study aimed to assess the collision avoidance capabilities of aftermarket products over road evaluation. The team conducted a real-driving usability study for evaluating aftermarket Collusion Avoidance Technology (CAT) devices by using eye-tracking technology. 

The primary objective of this research is to develop a Natural Goals Operators Methods and Selection rules Language (NGOMSL) model for Electronic Health Record (EHR) use in an Emergency Department (ED). In this study, the research team visits the ED Clinical Engineering lab at the Mayo Clinic in Minnesota and collaborates with scientists in systems engineering to observe emergency physicians’ and nurses’ behaviors related to the EHR process. Behavior monitoring equipment in the lab was used as a tool to collect physicians and nurses’ behaviors. The team developed hierarchical task analysis (HTA) charts by using the collected data. Following this, the team will develop the NGOMSL model based on the HTA charts.