Evidence map›Paper›PMID 36808497›Full record

ReviewChirurgie (Heidelberg, Germany)2023

[Development of a planned and monitoring robotic assistance and automation for application in orthopedics and trauma surgery].

Jan Reinhold, Jan Olschewski, Lennart Leon Heilemann, Andreas Seekamp, Sebastian Lippross, Thomas Meurer

Abstract readEnglish AbstractReview
PubMed Publisher
In one paragraph

Review in Chirurgie (Heidelberg, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Jan ReinholdLehrstuhl für Automatisierungs- und Regelungstechnik, Technische Fakultät, Christian-Albrechts-Universität zu Kiel, Kaiserstr. 2, 24143, Kiel, Deutschland.
Jan OlschewskiLehrstuhl für Automatisierungs- und Regelungstechnik, Technische Fakultät, Christian-Albrechts-Universität zu Kiel, Kaiserstr. 2, 24143, Kiel, Deutschland.
Lennart Leon HeilemannLehrstuhl für Automatisierungs- und Regelungstechnik, Technische Fakultät, Christian-Albrechts-Universität zu Kiel, Kaiserstr. 2, 24143, Kiel, Deutschland.
Andreas SeekampKlinik für Orthopädie und Unfallchirurgie, Universitätsklinikum Schleswig-Holstein, Campus Kiel, Arnold-Heller-Str. 3, 24105, Kiel, Deutschland.
Sebastian LipprossKlinik für Orthopädie und Unfallchirurgie, Universitätsklinikum Schleswig-Holstein, Campus Kiel, Arnold-Heller-Str. 3, 24105, Kiel, Deutschland. sebastian.lippross@uksh.de.
Thomas MeurerLehrstuhl für Automatisierungs- und Regelungstechnik, Technische Fakultät, Christian-Albrechts-Universität zu Kiel, Kaiserstr. 2, 24143, Kiel, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robot-assisted surgery offers many advantages with respect to precision and facilitation in medicine, whereby the physician controls the system externally by guiding the movement of the robot during the operation. Despite training and experience, operating errors by the user cannot be excluded. In addition, for the established systems the precise guidance of instruments along complexly shaped surfaces, e.g. for milling or cutting, depends on the skills of the operator. This article presents an expansion of the established robotic assistance for smooth movement along randomly shaped surfaces and introduces a movement automation which goes beyond the assistance systems used so far. Both approaches aim to improve the accuracy in surface-dependent medical procedures and avoid operator errors. Special applications with these requirements are, for example the execution of precise incisions or removal of adhering tissue in cases of spinal stenosis. A segmented computed tomography (CT) or magnetic resonance imaging (MRI) scan serves as the basis for a precise implementation. For robotic assistance externally guided by the operator the commands given to the robot are tested and monitored without delay so that adaptation of the movement exactly corresponding to the surface can be carried out. In contrast, the automation for the established systems differs in that the movement along the desired surface is roughly planned by the surgeon preoperatively by marking prominent points on the CT or MRI scan. From this a suitable track, including the appropriate instrument orientation, is calculated and, after checking the results, the robot finally carries this out autonomously. Based on this procedure, which is planned by humans and carried out by robots, errors are minimized, respective advantages are maximized and costly training on correct steering of robots becomes obsolete. The evaluation is carried out both in simulation and also experimentally on a complexly shaped 3D-printed lumbar vertebra from a CT scan with a Stäubli TX2-60 manipulator (Stäubli Tec-Systems GmbH Robotics, Bayreuth, Germany); however, the procedures are also transferable to and applicable on every other robotic system that covers the necessary working space, such as the da Vinci system.

Indexed as

Orthopedic ProceduresOrthopedicsRoboticsRobotic Surgical ProceduresGermanyHumansComplex surfacesInstrument orientationMovement automationOperating errorPrecision

Identifiers

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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.