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 

paper SpaceXR in HCI 2024

SpaceXR: Virtual Reality and Data Mining for Astronomical Visualization ” is published in the 26th HCI International Conference. Proceeding Book.  Washington DC, USA. 29 June – 4 July 2024
Authors: Mikhail Nikolaenko, Ming Tang



This paper presents a ” SpaceXR ” project that integrates data science, astronomy, and Virtual Reality (VR) technology to deliver an immersive and interactive educational tool. It is designed to cater to a diverse audience, including students, academics, space enthusiasts, and professionals, offering an easily accessible platform through VR headsets. This VR application offers a data-driven representation of celestial bodies, including planets and the sun within our solar system, guided by data from the NASA and Gaia databases. The VR application empowers users with interactive capabilities encompassing scaling, time manipulation, and object highlighting. The potential applications span from elementary educational contexts, such as teaching the star system in astronomy courses, to advanced astronomical research scenarios, like analyzing spectral data of celestial objects identified by Gaia and NASA. By adhering to emerging software development practices and employing a variety of conceptual frameworks, this project yields a fully immersive, precise, and user-friendly 3D VR application that relies on a real, publicly available database to map celestial objects. 

Check more project details on Solar Systems in VR. 

paper on JEC

Paper accepted in the Journal of Experimental Criminology.

Cory P. Haberman, Ming Tang, JC Barnes, Clay Driscoll, Bradley J. O’Guinn, Calvin Proffit, The Effect of Checklists on Evidence Collection During Initial Investigations A Randomized Controlled Trial in Virtual Reality. Journal of Experimental Criminology

Objective To examine the impact of an investigative checklist on evidence collection by police officers responding to a routine burglary investigation.

Methods A randomized control trial was conducted in virtual reality to test the effectiveness of an investigative checklist. Officers in the randomly assigned treatment group (n = 25) were provided with a checklist during the simulated investigation. Officers in the control group (n = 26) did not have access to the checklist at any time. The checklist included five evidence items commonly associated with burglary investigations.

Results Officers who were randomly provided with an investigative checklist were significantly more likely to collect two evidence items located outside of the virtual victim’s home. Both treatment and control officers were about equally as likely to collect three evidence items located inside the residence.

Conclusions Investigative checklists represent a promising new tool officers can use to improve evidence collection during routine investigations. More research is needed, however, to determine whether checklists improve evidence collection or case clearances in real-life settings. Virtual reality simulations provide a promising tool for collecting data in otherwise difficult or complex situations to simulate

Keywords: Investigations, Burglary, Checklists, Policing, Experiment, Randomized controlled trial

more information on this VR police training project available here. 

paper at ASEBP

Cory P. Haberman, Ming Tang, JC Barnes, Clay Driscoll, Bradley J. O’Guinn, Calvin Proffit,. Using Virtual Reality Simulations to Study Initial Burglary Investigations. American Society of Evidence-Based Policing’s 2023 Conference. 2023. Las Vegas. Nevada. (accepted)

Thanks for the support from the Cincinnati Police Department and the University of Cincinnati Research Grant. 

Using Virtual Reality Simulations to Study Initial Burglary Investigations

Cory P. Haberman, Ming Tang, JC Barnes, Clay Driscoll, Bradley J. O’Guinn, Calvin Proffit, University of Cincinnati

In this presentation, we discuss using virtual reality to study police investigations. First, we present the results of an experiment assessing the impact of providing investigative checklists to patrol officers responding to a burglary call for service in a large midwestern police agency. Second, we discuss the lessons learned from developing virtual reality simulations with limited budgets and student-based development teams. Third, we discuss the lessons learned from using virtual reality as a data collection technique for policing research.

More information is available at  VR for Police Training


paper at ACSE-ICTD conference

Raman, M., Tang, M3D Visualization Development of Urban Environments for Simulated Driving Training and VR Development in Transportation Systems. ASCE ICTD 2023 Conference. Austin. TX. 06. 2023


This work is based on a project to develop a physics-based, 3D digital visual environment that is a replication of actual field conditions for over seventy miles of Ohio highways and city roads for use in a driving simulator for the Ohio Department of Transportation. While transportation engineering design traditionally involves 3D design in a 2D workspace to create the built environment in the context of a natural environment, this project required replication of existing natural + built environments in a 3D digital space, thereby presenting a unique challenge to develop a new, repeatable process to create a specific digital end product.

Using industry-specific software comprised of InfraWorks (urban infrastructure design), Civil 3D (terrain modeling), Rhino (3D product modeling), 3ds Max (rendering/animation), Maya (3D animation/simulation), and Python (scripting) that are traditionally dedicated to their fields, the team developed a process to integrate them outside of their intended purposes so that they could connect industry-specific functionalities to deliver a novel product that can now be utilized by multiple markets.

This process utilizes the functionalities of each software to resolve a portion of the puzzle and delivers it as a solution for the next step of development using another software. Using an iterative development cycle approach, the process bridges the gaps between the industries of Transportation Engineering, Visualization, Architecture, and Gaming to deliver the end product.

The resulting 3D digital model of the existing urban environment can now be readily used as a baseline product for any industry that would benefit from such a digital model. In transportation engineering, it can be used in Transportation Systems Planning, Surface Operations, and/or Workforce Development. In outside/connected markets, it can be used in UI-based development, interactive game-based multiplayer virtual meetings, and photo-realistic immersive models for use in VR/multiplayer exploratory environments. This process has been standardized for the digital development of existing site conditions and context for the architectural conceptualization of buildings and public spaces in the Architecture program at the University of Cincinnati. The same process has been carried into the next development phase for the Ohio Department of Transportation.


Project link:

Training Simulation for snowplow