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Multimodal Interactions and Embodiment in Hybrid Environments

Published: November 2025

Multimodal interactions and embodiment in hybrid environments describe the fusion of virtual and real worlds through advanced technologies such as full-body representations and digital twins. The goal is to enhance immersion and user experience by having these systems adapt in real time to human actions and optimize interaction in social and collaborative contexts. This leads to improved human-machine collaboration and adaptability. The development of hybrid environments and multimodal interaction systems has made great progress in recent years.

Guiding questions

  • How can immersion in hybrid environments be further improved to enable even more realistic experiences?
  • What role do AI and machine learning play in adapting hybrid environments to individual users?
  • How can social and collaborative aspects be optimally considered in multimodal interaction systems?
  • What ethical guidelines should apply to the use of digital twins and virtual representations of real people?
  • How can the transferability of skills learned in hybrid environments to real-world situations be ensured?

Challenges

The development of realistic simulations that accurately replicate tissue and surgical procedures, as well as the integration of haptic feedback in VR training environments, pose technical challenges. A seamless connection of real and virtual data in real time requires powerful systems and algorithms. Intuitive user interfaces are crucial for the acceptance of hybrid environments. Furthermore, the use of digital twins and virtual patient avatars raises questions about data protection and liability that urgently need to be clarified.

Concrete examples

  • Meetings in virtual conference rooms using avatars with realistic body language
  • Training and simulation for the education of specialists, e.g., virtual surgical procedures, flight simulation, machine maintenance
  • Creative collaboration, e.g., design and architecture tools

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Reference

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Reference

Michel Reichardt

Michel Reichardt Project Manager Strategic Foresight

Christoph Grollman

Christoph Grollman Project Manager Strategic Foresight

Dr. Sophia Gänßle

Dr. Sophia Gänßle Project Manager Data Science Strategic Foresight

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