Evidence map›Paper›PMID 36298180›Full record

ArticleSensors (Basel, Switzerland)2022

A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery.

Armin Ehrampoosh, Bijan Shirinzadeh, Joshua Pinskier, Julian Smith, Randall Moshinsky, Yongmin Zhong

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. Controlling of Applied Force and Cornea Displacement Estimation in Robotic Corneal Surgery With a Gripper Surgical Instrument.The international journal of medical robotics + computer assisted surgery : MRCAS · 2025
    Article
  4. Article
  5. Review
  6. Article
  7. Article
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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.

Armin EhrampooshRobotics and Mechatronics Research Laboratory (RMRL), Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, VIC 3800, Australia.ORCID 0000-0002-5482-3454
Bijan ShirinzadehRobotics and Mechatronics Research Laboratory (RMRL), Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, VIC 3800, Australia.
Joshua PinskierData61, CSIRO, Brisbane, QLD 4069, Australia.ORCID 0000-0002-8878-9012
Julian SmithDepartment of Surgery, Monash University, Melbourne, VIC 3800, Australia.ORCID 0000-0003-1244-4277
Randall MoshinskyDepartment of Surgery, Monash University, Melbourne, VIC 3800, Australia.
Yongmin ZhongDepartment of Mechanical and Automotive Engineering, RMIT University, Melbourne, VIC 3083, Australia.ORCID 0000-0002-0105-9296

Funding

Australian Research Council Discovery Projects DP180103852Monash Institute of Medical Engineering (MIME) Seed Funding none
6 · The paper itself

Abstract

With robotic-assisted minimally invasive surgery (RAMIS), patients and surgeons benefit from a reduced incision size and dexterous instruments. However, current robotic surgery platforms lack haptic feedback, which is an essential element of safe operation. Moreover, teleportation control challenges make complex surgical tasks like suturing more time-consuming than those that use manual tools. This paper presents a new force-sensing instrument that semi-automates the suturing task and facilitates teleoperated robotic manipulation. In order to generate the ideal needle insertion trajectory and pass the needle through its curvature, the end-effector mechanism has a rotating degree of freedom. Impedance control was used to provide sensory information about needle-tissue interaction forces to the operator using an indirect force estimation approach based on data-based models. The operator's motion commands were then regulated using a hyperplanar virtual fixture (VF) designed to maintain the desired distance between the end-effector and tissue surface while avoiding unwanted contact. To construct the geometry of the VF, an optoelectronic sensor-based approach was developed. Based on the experimental investigation of the hyperplane VF methodology, improved needle-tissue interaction force, manipulation accuracy, and task completion times were demonstrated. Finally, experimental validation of the trained force estimation models and the perceived interaction forces by the user was conducted using online data, demonstrating the potential of the developed approach in improving task performance.

Indexed as

RoboticsRobotic Surgical ProceduresFeedbackHumansMinimally Invasive Surgical ProceduresSuturesforce sensinghaptic feedbackoptoelectronic sensorrobotic assisted minimally invasive surgeryrobotic needle drivervirtual fixture

Identifiers

PMID36298180
PMCPMC9609411

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.