Evidence map›Paper›PMID 39763108›Full record

ArticleThe international journal of medical robotics + computer assisted surgery : MRCAS2025

Controlling of Applied Force and Cornea Displacement Estimation in Robotic Corneal Surgery With a Gripper Surgical Instrument.

Ali Soltani Sharif Abadi, Andrew Ordys, Barbara Pierscionek

Abstract read
In one paragraph

Article in The international journal of medical robotics + computer assisted surgery : MRCAS, 2025. 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

3 authors.

Ali Soltani Sharif AbadiInstitute of Electronic Systems, Faculty of Electronics and Information Technology, Warsaw University of Technology, Warsaw, Poland.ORCID https://orcid.org/0000-0001-8901-836X
Andrew OrdysThe Institute of Automatic Control and Robotics, Faculty of Mechatronics, Warsaw University of Technology, Warsaw, Poland.
Barbara PierscionekFaculty of Health, Education, Medicine and Social Care, Medical Technology Research Centre, The Institute of Excellence in Robotic Surgery, Anglia Ruskin University, Chelmsford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe human eye consists of highly sensitive, hydrated, and relatively thin tissues, making precise control and accurate force estimation crucial in robotic eye surgery. This paper introduces a novel control method and state observer designed for a gripper surgical instrument used on the external ocular surface during robotic eye surgery.

methodsA novel state observer, operating in tandem with the controller, estimates the applied force. The proposed control approach, termed the Fixed-time Observer-based Sliding Mode Control (FOSMC), estimates the applied force by determining the gripper states and uses an eye model to calculate its displacement.

resultsThe performance of the proposed control method was compared with two other finite-time and asymptotic techniques across two scenarios. The results demonstrated excellent performance using the proposed method.

conclusionsThe FOSMC control technique effectively estimates the applied force during robotic eye surgery, making it a reliable solution for controlling the gripper surgical instrument.

Indexed as

CorneaRobotic Surgical ProceduresAlgorithmsEquipment DesignHumansOphthalmologic Surgical ProceduresReproducibility of ResultsSurgery, Computer-AssistedSurgical Instrumentsfixed‐time controlforce estimationgripperhuman eye displacementrobotic eye surgery

Identifiers

PMID39763108
PMCPMC11713865

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Registered trials

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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.