Evidence map›Paper›PMID 33424634›Full record

ReviewFrontiers in physiology2020

Tactile Perception Technologies and Their Applications in Minimally Invasive Surgery: A Review.

Chao Huang, Qizhuo Wang, Mingfu Zhao, Chunyan Chen, Sinuo Pan, Minjie Yuan

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in physiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

13 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Recent advances in 3D printing applications for CNS tumours.European journal of medical research · 2025
    Review
  5. Endovascular Detection of Catheter-Thrombus Contact by Vacuum Excitation.IEEE transactions on bio-medical engineering · 2024
    Article
  6. A Review of Recent Advancements in Sensor-Integrated Medical Tools.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  7. Article
  8. Review
  9. 'Now you can see me, now you don't': seeking the invisible lung nodule.Interdisciplinary cardiovascular and thoracic surgery · 2023
    Article
  10. Safety considerations in laparoscopic surgery: A narrative review.World journal of gastrointestinal endoscopy · 2022
    Review
  11. Article
  12. Article
  13. Review
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 at 2 institutions in 1 country.

Chao HuangInstitute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Qizhuo WangInstitute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Mingfu ZhaoInstitute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Chunyan ChenNingbo Institute of Information Technology Application, Chinese Academy of Sciences, Ningbo, China.
Sinuo PanNingbo Institute of Information Technology Application, Chinese Academy of Sciences, Ningbo, China.
Minjie YuanNingbo Institute of Information Technology Application, Chinese Academy of Sciences, Ningbo, China.
Chinese Academy of Sciences · CNNingbo Institute of Industrial Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Minimally invasive surgery (MIS) has been the preferred surgery approach owing to its advantages over conventional open surgery. As a major limitation, the lack of tactile perception impairs the ability of surgeons in tissue distinction and maneuvers. Many studies have been reported on industrial robots to perceive various tactile information. However, only force data are widely used to restore part of the surgeon's sense of touch in MIS. In recent years, inspired by image classification technologies in computer vision, tactile data are represented as images, where a tactile element is treated as an image pixel. Processing raw data or features extracted from tactile images with artificial intelligence (AI) methods, including clustering, support vector machine (SVM), and deep learning, has been proven as effective methods in industrial robotic tactile perception tasks. This holds great promise for utilizing more tactile information in MIS. This review aims to provide potential tactile perception methods for MIS by reviewing literatures on tactile sensing in MIS and literatures on industrial robotic tactile perception technologies, especially AI methods on tactile images.

Indexed as

artificial intelligenceminimally invasive surgeryrobotic surgerytactile imagestactile perceptiontactile sensors

Identifiers

PMID33424634
PMCPMC7785975
OpenAlexW3118017580

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.