ArticleFrontiers in robotics and AI2021
A Digital Twin Approach for Contextual Assistance for Surgeons During Surgical Robotics Training.
Article in Frontiers in robotics and AI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.
- Human-Centric Digital Twins in Industry: A Comprehensive Review of Enabling Technologies and Implementation Strategies.Sensors (Basel, Switzerland) · 2023Pooled it
- Digital twin-enabled robotic surgery: a bibliometric and knowledge-mapping analysis from patient-specific simulation to autonomy and clinical translation.Journal of robotic surgery · 2026Review
- A Granular Interaction Framework for Surgical Robotic Digital Twins: Enabling Realistic Segment-Level Manipulation in Extended Reality.International journal of computer assisted radiology and surgery · 2026Article
- Perception-first digital twin for augmented reality microsurgery.International journal of computer assisted radiology and surgery · 2026Article
- Digital Twin Technology In Radiology.Journal of imaging informatics in medicine · 2026Review
- Synthetic artificial intelligence in cardiology: from generative models to clinical applications.European heart journal open · 2026Review
- Designing a Digital Twin for the Management of Noncommunicable Diseases: Protocol for a Pilot Study and Methodology Validation.JMIR research protocols · 2026Article
- LAFOV PET as an enabling platform for pharmacokinetics-informed digital twins.Frontiers in medicine · 2026Article
- The IoRT-in-Hand: Tele-Robotic Echography and Digital Twins on Mobile Devices.Sensors (Basel, Switzerland) · 2025Article
- Virtual reality-augmented differentiable simulations for digital twin applications in surgical planning.Scientific reports · 2025Article
- Digital twin assisted surgery, concept, opportunities, and challenges.NPJ digital medicine · 2025Review
- Integration of Virtual Reality in the Control System of an Innovative Medical Robot for Single-Incision Laparoscopic Surgery.Sensors (Basel, Switzerland) · 2023Article
- Towards next generation digital twin in robotics: Trends, scopes, challenges, and future.Heliyon · 2023Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Minimally invasive robotic surgery copes with some disadvantages for the surgeon of minimally invasive surgery while preserving the advantages for the patient. Most commercially available robotic systems are telemanipulated with haptic input devices. The exploitation of the haptics channel, e.g., by means of Virtual Fixtures, would allow for an individualized enhancement of surgical performance with contextual assistance. However, it remains an open field of research as it is non-trivial to estimate the task context itself during a surgery. In contrast, surgical training allows to abstract away from a real operation and thus makes it possible to model the task accurately. The presented approach exploits this fact to parameterize Virtual Fixtures during surgical training, proposing a Shared Control Parametrization Engine that retrieves procedural context information from a Digital Twin. This approach accelerates a proficient use of the robotic system for novice surgeons by augmenting the surgeon's performance through haptic assistance. With this our aim is to reduce the required skill level and cognitive load of a surgeon performing minimally invasive robotic surgery. A pilot study is performed on the DLR MiroSurge system to evaluate the presented approach. The participants are tasked with two benchmark scenarios of surgical training. The execution of the benchmark scenarios requires basic skills as pick, place and path following. The evaluation of the pilot study shows the promising trend that novel users profit from the haptic augmentation during training of certain tasks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.