Evidence map›Paper›PMID 39421850›Full record

Article... International Symposium on Medical Robotics. International Symposium on Medical Robotics2024

A Data-Driven Model with Hysteresis Compensation for I

Mojtaba Esfandiari, Yanlin Zhou, Shervin Dehghani, Muhammad Hadi, Adnan Munawar, Henry Phalen, David E Usevitch, Peter Gehlbach, Iulian Iordachita

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ... International Symposium on Medical Robotics. International Symposium on Medical Robotics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Model Predictive Path Integral Control of IProceedings of the ... American Control Conference. American Control Conference · 2025
    Article
  5. 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

9 authors.

Mojtaba EsfandiariDepartment of Mechanical Engineering and Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, 21218, USA.
Yanlin ZhouDepartment of Mechanical Engineering and Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, 21218, USA.
Shervin DehghaniDepartment of Computer Science, Technische Universität München, München 85748 Germany.
Muhammad HadiDepartment of Mechanical Engineering and Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, 21218, USA.
Adnan MunawarDepartment of Mechanical Engineering and Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, 21218, USA.
Henry PhalenDepartment of Mechanical Engineering and Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, 21218, USA.
David E UsevitchDepartment of Mechanical Engineering and Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, 21218, USA.
Peter GehlbachWilmer Eye Institute, Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
Iulian IordachitaDepartment of Mechanical Engineering and Laboratory for Computational Sensing and Robotics, 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 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 EB034397
6 · The paper itself

Abstract

Retinal microsurgery is a high-precision surgery performed on a delicate tissue requiring the skill of highly trained surgeons. Given the restricted range of instrument motion in the confined intraocular space, snake-like robots may prove to be a promising technology to provide surgeons with greater flexibility, dexterity, and positioning accuracy during retinal procedures such as retinal vein cannulation and epiretinal membrane peeling. Kinematics modeling of these robots is an essential step toward accurate position control. Unlike conventional manipulators, modeling these robots does not follow a straightforward method due to their complex mechanical structure and actuation mechanisms. The hysteresis problem can especially impact the positioning accuracy significantly in wire-driven snake-like robots. In this paper, we propose a data-driven kinematics model using a probabilistic Gaussian mixture model (GMM) and Gaussian mixture regression (GMR) approach with a hysteresis compensation algorithm. Experimental results on the two-degree-of-freedom (DOF) integrated robotic intraocular snake (I

Identifiers

PMID39421850
PMCPMC11486515

What OpenQuestion holds

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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.