Evidence map›Paper›PMID 31265381›Full record

ArticleIEEE transactions on bio-medical engineering2020

Toward Safe Retinal Microsurgery: Development and Evaluation of an RNN-Based Active Interventional Control Framework.

Changyan He, Niravkumar Patel, Mahya Shahbazi, Yang Yang, Peter Gehlbach, Marin Kobilarov, Iulian Iordachita

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.6field-weighted citation impact, top 7% of its field
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

17 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Robotic Assistance for Intraocular Microsurgery: Challenges and Perspectives.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2022
    Article
  7. Article
  8. Artificial intelligence and ophthalmic surgery.Current opinion in ophthalmology · 2021
    Review
  9. Stochastic Force-based Insertion Depth and Tip Position Estimations of Flexible FBG-Equipped Instruments in Robotic Retinal Surgery.IEEE/ASME transactions on mechatronics : a joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division · 2021
    Article
  10. Automatic Light Pipe Actuating System for Bimanual Robot-Assisted Retinal Surgery.IEEE/ASME transactions on mechatronics : a joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division · 2020
    Article
  11. FBG-based Kalman Filtering and Control of Tool Insertion Depth For Safe Robot-assisted Vitrectomy.... International Symposium on Medical Robotics. International Symposium on Medical Robotics · 2020
    Article
  12. Force-based Safe Vein Cannulation in Robot-assisted Retinal Surgery: A Preliminary Study.... International Symposium on Medical Robotics. International Symposium on Medical Robotics · 2020
    Article
  13. Auditory Feedback Effectiveness for Enabling Safe Sclera Force in Robot-Assisted Vitreoretinal Surgery: a Multi-User Study.Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems · 2020
    Article
  14. An Optimized Tilt Mechanism for a New Steady-Hand Eye Robot.Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems · 2020
    Article
  15. Review
  16. Artificial intelligence, robotics and eye surgery: are we overfitted?International journal of retina and vitreous · 2019
    Article
  17. Towards Bimanual Vein Cannulation: Preliminary Study of a Bimanual Robotic System With a Dual Force Constraint Controller.IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation
    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

7 authors at 3 institutions in 2 countries.

Changyan He
Niravkumar Patel
Mahya Shahbazi
Yang Yang
Peter Gehlbach
Marin Kobilarov
Iulian Iordachita
Johns Hopkins University · USBeihang University · CNJohns Hopkins Hospital · US

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
NIBIB NIH HHS R01 EB023943
6 · The paper itself

Abstract

objectiveRobotics-assisted retinal microsurgery provides several benefits including improvement of manipulation precision. The assistance provided to the surgeons by current robotic frameworks is, however, a "passive" support, e.g., by damping hand tremor. Intelligent assistance and active guidance are, however, lacking in the existing robotic frameworks. In this paper, an active interventional control framework (AICF) has been presented to increase operation safety by actively intervening the operation to avoid exertion of excessive forces to the sclera.

methodsAICF consists of the following four components: first, the steady-hand eye robot as the robotic module; second, a sensorized tool to measure tool-to-sclera forces; third, a recurrent neural network to predict occurrence of undesired events based on a short history of time series of sensor measurements; and finally, a variable admittance controller to command the robot away from the undesired instances.

resultsA set of user studies were conducted involving 14 participants (with four surgeons). The users were asked to perform a vessel-following task on an eyeball phantom with the assistance of AICF as well as other two benchmark approaches, i.e., auditory feedback (AF) and real-time force feedback (RF). Statistical analysis shows that AICF results in a significant reduction of proportion of undesired instances to about 2.5%, compared with 38.4% and 26.2% using AF and RF, respectively.

conclusionAICF can effectively predict excessive-force instances and augment performance of the user to avoid undesired events during robot-assisted microsurgical tasks. SIGNIFICANCE: The proposed system may be extended to other fields of microsurgery and may potentially reduce tissue injury.

Indexed as

RoboticsRobotic Surgical ProceduresHumansMicrosurgeryRetinaSclera

Identifiers

PMID31265381
PMCPMC7197394
OpenAlexW2961129621

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.