Computational Science Hub (CSH)

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/16924

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CortexVR: Immersive analysis and training of cognitive executive functions of soccer players using virtual reality and machine learning
(2022) Krupitzer, Christian; Naber, Jens; Stauffert, Jan-Philipp; Mayer, Jan; Spielmann, Jan; Ehmann, Paul; Boci, Noel; Bürkle, Maurice; Ho, André; Komorek, Clemens; Heinickel, Felix; Kounev, Samuel; Becker, Christian; Latoschik, Marc Erich
Goal: This paper presents an immersive Virtual Reality (VR) system to analyze and train Executive Functions (EFs) of soccer players. EFs are important cognitive functions for athletes. They are a relevant quality that distinguishes amateurs from professionals. Method: The system is based on immersive technology, hence, the user interacts naturally and experiences a training session in a virtual world. The proposed system has a modular design supporting the extension of various so-called game modes. Game modes combine selected game mechanics with specific simulation content to target particular training aspects. The system architecture decouples selection/parameterization and analysis of training sessions via a coaching app from an Unity3D-based VR simulation core. Monitoring of user performance and progress is recorded by a database that sends the necessary feedback to the coaching app for analysis. Results: The system is tested for VR-critical performance criteria to reveal the usefulness of a new interaction paradigm in the cognitive training and analysis of EFs. Subjective ratings for overall usability show that the design as VR application enhances the user experience compared to a traditional desktop app; whereas the new, unfamiliar interaction paradigm does not negatively impact the effort for using the application. Conclusion: The system can provide immersive training of EF in a fully virtual environment, eliminating potential distraction. It further provides an easy-to-use analyzes tool to compare user but also an automatic, adaptive training mode.
Modelling and simulation for preclinical cardiac safety assessment of drugs with human iPSC-derived cardiomyocytes
(2020) Kügler, Philipp
As a potentially life threatening side effect, pharmaceutical compounds may trigger cardiac arrhythmias by impeding the heart’s electrical and mechanical function. For this reason, any new compound needs to be tested since 2005 for its proarrhythmic risk both during the preclinical and the clinical phase of the drug development process. While intensive monitoring of cardiac activity during clinical tests with human volunteers constitutes a major cost factor, preclinical in vitro tests with non cardiac cells and in vivo tests with animals are currently under serious debate because of their poor extrapolation to drug cardiotoxicity in humans. For about five years now, regulatory agencies, industry and academia are working on an overhaul of the cardiac drug safety paradigm that is built a) on human heart muscle cells, that can be abundantly bioengineered from donor stem cells without ethical concerns (human induced pluripotent stem cell derived cardiomyocytes, hiPSC-CMs), and b) on computational models of human cardiac electrophysiology both at the cellular and the organ level. The combined use of such human in vitro and human in silico models during the preclinical phase is expected to improve proarrhythmia test specificity (i.e. to lower the false-positive rate), to better inform about the need of thorough heart monitoring in the clinic, and to reduce or even replace animal experiments. This review article starts by concisely informing about the electrical activity of the human heart, about its possible impairment due to drug side effects, and about hiPSC-CM assays for cardiac drug safety testing. It then summarizes the mathematical description of human cardiac electrophysiology in terms of mechanistic ODE and PDE models, and illustrates how their numerical analysis may provide insight into the genesis of drug induced arrhythmias. Finally, this paper surveys proarrhythmic risk estimation methods, that involve the simulation of human heart muscle cells, and addresses opportunities and challenges for future interdisciplinary research.
Visual tracking of a moving target in 360-degree virtual reality: analysis of the effects on attention and mood
(2025) Sellner, T.; Ehmann, P.; Spielmann, J.; Gogolla, F.; Rösgen, A.; Mayer, J.; Schoenfeld, M. A.; Flor, H.
The training of attentional capacities is an important part of many rehabilitative efforts, for example, in the treatment of stroke. The Helix-Arena is an innovative virtual reality (VR) training device, which enables multimodal training in a 360-degree virtual environment. A pursuit training was developed for the Helix-Arena. In this study, we evaluate the effectiveness of the pursuit training in the Helix-Arena compared to a control group [CG, training on a personal computer (PC)] in 34 healthy participants. The experimental group (EG, N = 19) participated in four training sessions in the Helix-Arena over a period of 2 weeks. The control group (N = 15) completed similar training sessions in a non-VR environment on a PC. During each training session, changes in attention (Test of Attentional Performance battery, TAP) and general mood (Positive and Negative Affect Schedule, PANAS) were assessed pre- and post-training. A significantly higher pre-to-post improvement was observed in the EG for the TAP subtest attention shift in the subcategory invalid instructor ( p = 0.04) than that in the CG. In addition, we found a higher positive affect after the training in the EG but not in the CG (p < 0.01). These results suggest advantages of the VR environment for attentional and affective processes. The VR training can thus improve not only cognitive abilities but also training motivation. In a next step, the training can be used with patients in a rehabilitation context, but it is also suitable for educational and gaming contexts.

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