Evidence map›Paper›PMID 42536818›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

EndoTac: An Endoscopic Camera-Based Tactile Sensor with High Sensitivity for Minimally Invasive Surgery.

Yupeng Wang, Nicolas Raison, Xuyang Zhang, Aijia Yang, Lukas Lindenroth, Shan Luo

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yupeng WangDepartment of Engineering, King's College London, London, UK.ORCID https://orcid.org/0009-0004-7843-2484
Nicolas RaisonSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
Xuyang ZhangDepartment of Engineering, King's College London, London, UK.ORCID https://orcid.org/0009-0002-7096-6858
Aijia YangFaculty of Engineering, Imperial College London, London, UK.ORCID https://orcid.org/0009-0004-3402-1691
Lukas LindenrothSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.ORCID https://orcid.org/0000-0002-9108-4574
Shan LuoDepartment of Engineering, King's College London, London, UK.ORCID https://orcid.org/0000-0003-4760-0372

Funding

EPSRC EP/T033517/2EPSRC UKRI3438
6 · The paper itself

Abstract

Minimally invasive surgery (MIS) removes direct tactile feedback from surgical procedures, making it challenging for surgeons to manipulate delicate anatomy, such as vasculature and other soft tissue. Existing tactile tools developed for MIS in prior research are either too bulky or have limited sensing coverage, restricting their utility in practical surgical workflows. To address these challenges, we introduce EndoTac, a novel miniaturized vision-based tactile sensor designed to traverse a standard trocar while offering a large sensing area with high sensitivity. EndoTac integrates an endoscopic camera to achieve a compact and MIS-compatible form factor, and employs a convex mirror to capture the contact information across a wide sensing area, thereby maximizing effective sensing coverage. A soft membrane further enables the sensor to achieve high sensitivity by deforming under gentle interactions with soft and fragile tissue like vascular structures. Experimental results demonstrate that EndoTac achieves a low detection threshold of 20.5 mN, a high pixel-level sensitivity slope in the low-force regime, improved force resolution, and reliable estimation of vessel deformation in vascular palpation tests. Together, these results show that EndoTac provides a significant step toward restoring tactile perception in MIS, offering a practical pathway to safer and more precise surgical manipulation.

Indexed as

deformation sensingforce sensingminimally invasive surgerytactile sensingvascular sensing

Identifiers

PMID42536818
PMCPMC13427239

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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.