GenAI+AR Siemens

Automatic Scene Creation for Augmented Reality Work Instructions Using Generative AI. Siemens. PI. Ming Tang. co-PI: Tianyu Jiang. $25,000. UC. 4/1/2024-12/31/2024

Sponsor: Siemens through UC MME Industry 4.0/5.0 Institute

 

Paper in AHFE conference

Nancy Daraiseh, Ming Tang, Mikhail Nikolaenko . Using Virtual Reality to Enhance Behavioral Staff Training for Interacting with Aggressive Psychiatric Patients. The 15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024). Nice, France, July 24-27, 2024.

Objective: To conduct a pilot study to enhance staff training and confidence when interacting with aggressive psychiatric patients using a virtual reality (VR) training module depicting an escalating patient scenario.

Significance: Dysregulated emotional outbursts, reactive aggression, and self-injurious behaviors are common in psychiatrically hospitalized patients. These behaviors result in aggressive patient interactions (APIs) which are associated with increased risk of harm to the patient and staff. Minimal research has examined interventions for successful training to effectively reduce or prevent API events and subsequent harm. Despite intensive, standardized trainings in crisis de-escalation protocols, staff continue to experience high rates of API injuries. More realistic training and competency in a safe environment to practice implementation and utilization of de-escalation strategies to avoid APIs and patient harm are needed.

Methods Using a pre – post, quasi-experimental design, 40 Behavioral Health Specialists and Registered Nurses at a pediatric psychiatric facility will participate in VR training depicting a commonly experienced scenario when interacting with an aggressive patient. Participants are stratified by job experience, sex, and VR experience. Study aims are to: i) assess the feasibility and usability of VR training among this population and ii) obtain measures of learner satisfaction and performance. Surveys measure usability, learner satisfaction, and coping with patient aggression. Pre- and post-performance in training will be compared and assessed by percent correct answers on the first attempt; time to correct answer; and the number of successful and unsuccessful attempts.

Preliminary Results (full analyses in progress): Preliminary survey results (N=14) show that 64% perceived the VR experience to be consistent with their real-world experiences: 87% agree that the VR training would help with interactions with aggressive patients: 71% reported the training was effective in identifying de-escalation strategies: 79% stated the training was effective in recognizing stages of patient crisis; training included important skills used in their job; and would recommend the training. Finally, 100% would participate in future VR trainings.

Anticipated Conclusions: We plan to show that using VR to supplement in-place training programs for high-risk situations can improve users’ understanding of essential de-escalation and crisis techniques. We anticipate results will show an enhanced ability and confidence when interacting with aggressive patients. Future studies will expand on results and examine implications on staff and patient harm. 

Check more information on the  VR-based Employee Safety Training. Therapeutic Crisis Intervention Simulation 

UC UPRISE

XR-Lab’s project was selected to join the Undergraduates Pursuing Research in Science and Engineering (UPRISE) Program
UNDERGRADUATE SUMMER RESEARCH PROGRAM IN SCIENCE AND ENGINEERING
May 6 – July 26, 2024

 

Project title: Reinforcement Learning (RL) system in Game Engine

This project proposes the development of a sophisticated reinforcement learning (RL) system utilizing the robust and versatile environment of Unreal Engine 5 (UE5). The primary objective is to create a flexible and highly realistic simulation platform that can model a multitude of real-life scenarios, ranging from object recognition, urban navigation to emergency response strategies. This platform aims to significantly advance the capabilities of RL algorithms by exposing them to complex, diverse, and dynamically changing environments. Leveraging the advanced graphical and physical simulation capabilities of UE5, the project will focus on creating detailed and varied scenarios in which RL algorithms can be trained and tested. These scenarios will include, but not be limited to, urban traffic systems, natural disaster simulations, and public safety response models. The realism and intricacy of UE5’s environment will provide a challenging and rich training ground for RL models, allowing them to learn and adapt to unpredictable variables akin to those in the real world.

AE studio 2024

AE Studio 3004, Restaurant Design

 

Spring 2024. Instructors: Ming Tang, Samira Sarabandikachyani

This studio serves as a comprehensive introduction to designing a building. 

Honors Seminar student projects

“Human-Computer Interaction in the Age of Extended Reality & Metaverse” student projects

Spring. 2024.  UC

Under the guidance of Ming Tang, Director of the XR-Lab at Digital Futures and DAAP, UC, this honors seminar course has propelled students through an immersive journey into the realm of XR. The course encompasses Extended Reality, Metaverse, and Digital Twin technologies, providing a comprehensive platform for theoretical exploration and practical application in XR development.

The coursework showcases an array of student-led research projects that investigate the role of XR in various domains, including medical training, flight simulation, entertainment, tourism, cultural awareness, fitness, and music. Through these projects, students have had the opportunity to not only grasp the intricate theories underpinning future HCI developments but also to apply their skills in creating immersive experiences that hint at the future of human-technology interaction.

 

 “Human-Computer Interaction in the Age of Extended Reality & Metaverse” is a UC Honors course that delves into the burgeoning field of extended reality (XR) and its confluence with human-computer interaction (HCI), embodying a fusion of scholarly inquiry and innovative practice.

Ming Tang, Professor, Director of XR-Lab, DAAP, University of Cincinnati

Students: Nishanth Chidambaram, Bao Huynh, Caroline McCarthy, Cameron Moreland, Frank Mularcik, Cooper Pflaum, Triet Pham, Brooke Stephenson, Pranav Venkataraman

Thanks for the support from the UC Honors Program and UC Digital Futures.