Evidence map›Paper›PMID 41497444›Full record

ArticleIEEE transactions on human-machine systems2025

Bimanual Manipulation of Steady-Hand Eye Robots with Adaptive Sclera Force Control: Cooperative vs. Teleoperation Strategies.

Mojtaba Esfandiari, Peter Gehlbach, Russell H Taylor, Iulian I Iordachita

Abstract read
In one paragraph

Article in IEEE transactions on human-machine systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Deep Learning-Enhanced Robotic Subretinal Injection with Real-Time Retinal Motion Compensation.IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering · 2025
    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

4 authors.

Mojtaba EsfandiariMojtaba Esfandiari and Iulian Iordachita are with the Department of Mechanical Engineering and also the Laboratory for Computational Sensing and Robotics at the Johns Hopkins University, Baltimore, MD, 21218, USA.
Peter GehlbachPeter Gehlbach is with the Wilmer Eye Institute, Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
Russell H TaylorRussell H. Taylor is with the Department of Computer Science and also the Laboratory for Computational Sensing and Robotics at the Johns Hopkins University, Baltimore, MD, 21218, USA.
Iulian I IordachitaMojtaba Esfandiari and Iulian Iordachita are with the Department of Mechanical Engineering and also the Laboratory for Computational Sensing and Robotics at the Johns Hopkins University, Baltimore, MD, 21218, USA.

Funding

Enabling Technology for Safe Robot-assisted Surgical MicromanipulationR01EB023943 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI GEHLBACH, PETER LOUIS, IORDACHITA, IULIAN IOAN · 2017 to 2024
$2.3M
Enabling technology for image-guided robot-assisted sub-retinal injectionsR01EB025883 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI IORDACHITA, IULIAN IOAN · 2019 to 2021
$1.5M
Enabling Dexterous Intraocular Surgery with Robotic AssistanceR01EB034397 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI IULIAN IOAN IORDACHITA · 2024 to 2026
$1.2M
NIBIB NIH HHS R01 EB023943NIBIB NIH HHS R01 EB025883NIBIB NIH HHS R01 EB034397
6 · The paper itself

Abstract

Performing retinal vein cannulation (RVC) as a potential treatment for retinal vein occlusion (RVO) without the assistance of a surgical robotic system is very challenging to do safely. The main limitation is the physiological hand tremor of surgeons. Robot-assisted eye surgery technology may resolve the problems of hand tremors and fatigue and improve the safety and precision of RVC. The Steady-Hand Eye Robot (SHER) is an admittance-based robotic system that can filter out hand tremors and enables ophthalmologists to manipulate a surgical instrument inside the eye cooperatively. However, the admittance-based cooperative control mode does not safely minimize the contact force between the surgical instrument and the sclera to prevent tissue damage. In addition, features such as haptic feedback or hand motion scaling, which can improve the safety and precision of surgery, require a teleoperation control framework. This work presents, for the first time in the field of robot-assisted retinal microsurgery research, a registration-free bimanual adaptive teleoperation (BMAT) control framework using SHER 2.0 and SHER 2.1 robotic systems. Both SHERs are integrated with an adaptive force control (AFC) algorithm that dynamically and automatically minimizes the tool-sclera interaction forces, enforcing them within a safe limit. The scleral forces are measured using two fiber Bragg grating (FBG)-based force-sensing tools. The performance of the proposed BMAT control framework is evaluated by comparison with a bimanual adaptive cooperative (BMAC) framework in a vessel-following experiment conducted under a surgical microscope. Experimental results demonstrate the effectiveness of the BMAT control framework in performing a safe bimanual telemanipulation of the eye without over-stretching it, even in the absence of registration between the two robots.

Indexed as

Adaptive force controlbimanual adaptive teleoperationfiber Bragg grating sensorforce-sensing surgical instrumentsteady-hand eye robot

Identifiers

PMID41497444
PMCPMC12768329

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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.