Treffer: Virtual reality interactions via a user-generic ultrasound human-machine interface for wrist and hand tracking.

Title:
Virtual reality interactions via a user-generic ultrasound human-machine interface for wrist and hand tracking.
Authors:
Grandi Sgambato B; Department of Bioengineering, Imperial College London, London, UK., Hodossy BK; Department of Bioengineering, Imperial College London, London, UK., Barsakcioglu DY; Department of Bioengineering, Imperial College London, London, UK., Yang X; Department of Bioengineering, Imperial College London, London, UK.; School of Automation, Southeast University, Nanjing, China., Jakob A; Ultrasound Department, Fraunhofer Institut für Biomedizinische Technik, Sulzbach, Germany., Fournelle M; Ultrasound Department, Fraunhofer Institut für Biomedizinische Technik, Sulzbach, Germany., Tang MX; Department of Bioengineering, Imperial College London, London, UK., Farina D; Department of Bioengineering, Imperial College London, London, UK. d.farina@imperial.ac.uk.
Source:
Nature communications [Nat Commun] 2025 Dec 11; Vol. 16 (1), pp. 11062. Date of Electronic Publication: 2025 Dec 11.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE
Imprint Name(s):
Original Publication: [London] : Nature Pub. Group
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Grant Information:
899822 EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
Entry Date(s):
Date Created: 20251211 Date Completed: 20251211 Latest Revision: 20251214
Update Code:
20251214
PubMed Central ID:
PMC12699032
DOI:
10.1038/s41467-025-66001-6
PMID:
41381418
Database:
MEDLINE

Weitere Informationen

As computers move from desktop screens into our glasses, traditional controllers such as keyboards and mice have proven impractical. A control interface for immersive experiences needs to seamlessly transport intention from the real to the virtual world while remaining portable, accurate, and robust. Here, we present an easy-to-wear, dry-contact and portable ultrasound armband that can decode morphological information and act as a virtual reality controller by predicting hand and wrist kinematics. Using our armband, we collected a large dataset of paired ultrasound and hand kinematics and used it to train supervised deep-learning models capable of predicting hand kinematics from ultrasound. We explored how diverse intra-session, cross-session, and cross-participant data shifts affect model performance. Further, we proposed methods for data conditioning, augmentation, and a referencing strategy to mitigate the influence of confounding factors and to achieve accurate prediction of hand kinematics on unseen users without fine-tuning. Finally, we demonstrated the feasibility of our interface in a real-time virtual reality control framework. Using the developed ultrasound interface, participants completed challenging interaction tasks with simulated contact physics. This work demonstrates the potential of ultrasound-based technologies as a virtual reality interface, showcasing strong performance, robustness, and generalization potential.
(© 2025. The Author(s).)

Competing interests: The authors declare no competing interests.