Clear_Pixel VR (Pt.2)
Enhancing VR Training with Realistic Animation and Visual Effects
Clear_Pixel VR (CPVR) is an innovative virtual reality training company focused on creating immersive, simulation-based learning modules for the medical and scientific sectors. Based in the UK, their flagship offerings include VR training for laboratory safety and procedures, with recent expansions into animal handling simulations used in biomedical and pharmaceutical research.
Following a successful collaboration with CEMET to design a modular UI and test system for training modules, Clear_Pixel VR returned with a new challenge: increasing realism in their VR courses through high-fidelity animations and intuitive visual feedback systems. Specifically, they needed two key components:
A believable graphing system to represent dynamic data displays (like those used in lab equipment), simulating real-time input such as heart rate monitors or measurement outputs.
A set of anatomically accurate and behaviourally realistic mouse animations, for use in VR modules that simulate various forms of handling and injection techniques—such as intraperitoneal, subcutaneous, and intravenous administration.
The goal was to elevate both visual authenticity and learning effectiveness, especially in scenarios where accurate behaviour modelling is critical. Clear_Pixel VR’s overarching ambition was to reduce the use of live animals in training settings, by creating realistic enough VR simulations that can serve as a meaningful precursor to real-world practice.
What Did We Do?
CEMET’s development team engaged in close consultation with CPVR’s animators, subject matter experts, and instructional designers to ensure the new content would integrate seamlessly with the existing VR experience, powered by Unreal Engine 5.2.
Clear_Pixel VR needed a solution that would accurately portray live monitoring equipment, such as oscilloscopes or medical diagnostics, in a way that was both visually convincing and easy to maintain. The original idea was to build a dynamic graphing system that could draw lines in real-time based on data input. However, in practice this posed a number of technical challenges, including performance overhead, complexity of implementation, and potential limitations in adapting to varied graph types.
Instead, CEMET devised a solution that combined creative design with performance efficiency. By using a sequence of pre-generated, high-resolution graph images animated on a canvas, we were able to simulate the drawing of a line across time—just as a real graph would appear when updating live. These animations were modular and reusable, allowing Clear_Pixel VR to load new visual graphs simply by swapping out image sets. This dramatically reduced development time and enabled flexible application across multiple training scenarios.
Far from being a shortcut, this approach enhanced the realism of Clear_Pixel’s VR experience without compromising performance. The system could be integrated into any part of their training where monitoring or data output was required—such as simulations of heart rate monitors, lab sensor outputs, or diagnostic equipment. It added a critical layer of authenticity to the training modules, particularly for audiences familiar with real-world lab environments who expect high visual fidelity from medical simulations.
The second part of the project focused on delivering lifelike animations for mouse handling. Working from Clear_Pixel’s precise behavioural briefs, CEMET developed a set of loopable, realistic animations to simulate various stages of laboratory animal handling. These included:
Mouse tail pickup: A looped animation of the mouse squirming when suspended by the tail—accurately reflecting common behavioural responses.
Scruff (neck) pickup: A stationary, submissive animation where the mouse is held at the base of the neck, as is standard in lab procedure.
Cage grip behaviour: A gripping action in which the mouse clings to the bars of a cage lid—often used to stabilise the animal before injection.
Tube restraint: Simulated behaviour of the mouse inside a plastic restraint tube used for precise handling.
Each animation was carefully created using the existing rigged 3D model and exported as in-place looping FBX files for seamless integration into Unreal. Although CEMET typically works in Unity, the assets and workflows were developed with Unreal’s requirements in mind, ensuring easy hand-off to CPVR’s own dev team.
Impact
The resulting animations marked a significant leap in realism for Clear_Pixel VR’s training modules. The smooth blending and behavioural accuracy of the mouse actions introduced a new level of immersion—giving trainees a better sense of how lab animals behave during procedures, something previously missing from earlier versions of the training.
Likewise, the animated graph system now enables Clear_Pixel VR to present data displays in an intuitive and performance-friendly way across any number of scenarios, without requiring costly real-time development or additional computation. This has opened the door for future modules involving simulated instruments, diagnostics, and experimental procedures.
Most importantly, the combination of realistic animal behaviour and interactive feedback strengthens CPVR’s mission: reducing stress and harm to animals by equipping trainees with more lifelike, experiential training tools. These improvements have made the modules more engaging, more informative, and more aligned with the ethical goals of modern laboratory practice.
Conclusion
This collaboration exemplifies how applied creative technology, underpinned by close collaboration, can produce transformative educational outcomes. With CEMET’s support, Clear_Pixel VR is now better positioned than ever to grow its training platform—expanding its content library while continuing to set the standard for immersive, ethical lab-based instruction.
CEMET is proud to continue to support Clear_Pixel VR through the development of this project. To find out more about their latest work visit their website or follow them via Instagram, X or Facebook.
This project is jointly funded by the UK Government’s Shared Prosperity Fund and Cardiff Capital Region (CCR) the Academic-Industry Partnerships programme, part of the Cluster Development and Growth Programme, supported by Cardiff Council.
