Evidence map›Paper›PMID 39249173›Full record

ArticleInternational journal of computer assisted radiology and surgery2025

6G in medical robotics: development of network allocation strategies for a telerobotic examination system.

Sven Kolb, Andrew Madden, Nicolai Kröger, Fidan Mehmeti, Franziska Jurosch, Lukas Bernhard, Wolfgang Kellerer, Dirk Wilhelm

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sven Kolb *TUM School of Medicine and Health, Klinikum rechts der Isar, Research Group MITI, Technical University of Munich, Munich, Germany. sven.kolb@tum.de.ORCID http://orcid.org/0009-0002-3176-3206
Andrew Madden *TUM School of Medicine and Health, Klinikum rechts der Isar, Research Group MITI, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0009-0004-4283-2355
Nicolai KrögerTUM School of Computation, Information and Technology, Chair of Communication Networks, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0003-4282-4166
Fidan MehmetiTUM School of Computation, Information and Technology, Chair of Communication Networks, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0002-0997-6929
Franziska JuroschTUM School of Medicine and Health, Klinikum rechts der Isar, Research Group MITI, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0002-9974-6886
Lukas BernhardTUM School of Medicine and Health, Klinikum rechts der Isar, Research Group MITI, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0002-9729-8928
Wolfgang KellererTUM School of Computation, Information and Technology, Chair of Communication Networks, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0003-4358-8038
Dirk WilhelmTUM School of Medicine and Health, Klinikum rechts der Isar, Research Group MITI, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0002-2972-9802

Funding

Bundesministerium für Bildung und Forschung 16KISK002
6 · The paper itself

Abstract

purposeHealthcare systems around the world are increasingly facing severe challenges due to problems such as staff shortage, changing demographics and the reliance on an often strongly human-dependent environment. One approach aiming to address these issues is the development of new telemedicine applications. The currently researched network standard 6G promises to deliver many new features which could be beneficial to leverage the full potential of emerging telemedical solutions and overcome the limitations of current network standards.

methodsWe developed a telerobotic examination system with a distributed robot control infrastructure to investigate the benefits and challenges of distributed computing scenarios, such as fog computing, in medical applications. We investigate different software configurations for which we characterize the network traffic and computational loads and subsequently establish network allocation strategies for different types of modular application functions (MAFs).

resultsThe results indicate a high variability in the usage profiles of these MAFs, both in terms of computational load and networking behavior, which in turn allows the development of allocation strategies for different types of MAFs according to their requirements. Furthermore, the results provide a strong basis for further exploration of distributed computing scenarios in medical robotics.

conclusionThis work lays the foundation for the development of medical robotic applications using 6G network architectures and distributed computing scenarios, such as fog computing. In the future, we plan to investigate the capability to dynamically shift MAFs within the network based on current situational demand, which could help to further optimize the performance of network-based medical applications and play a role in addressing the increasingly critical challenges in healthcare.

Indexed as

Computer Communication NetworksRoboticsTelemedicineHumansSoftware6GFog computingMedical roboticsTelemedicine

Identifiers

PMID39249173
PMCPMC11759283

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.