Evidence map›Paper›PMID 39764508›Full record

ArticleNational science review2025

A tactile perception method with flexible grating structural color.

Yuze Qiu, Chunfei Yan, Yan Zhang, Shengxuan Yang, Xiang Yao, Fawen Ai, Jinjin Zheng, Shiwu Zhang, Xinge Yu, Erbao Dong

Abstract read
In one paragraph

Article in National science review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. 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

10 authors.

Yuze QiuKey Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei 230026, China.
Chunfei YanInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
Yan ZhangKey Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei 230026, China.
Shengxuan YangInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
Xiang YaoKey Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei 230026, China.
Fawen AiInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
Jinjin ZhengInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
Shiwu ZhangInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
Xinge YuDepartment of Biomedical Engineering, City University of Hong Kong, Hong Kong 999077, China.ORCID https://orcid.org/0000-0003-0522-1171
Erbao DongKey Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei 230026, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Affordable high-resolution cameras and state-of-the-art computer vision techniques have led to the emergence of various vision-based tactile sensors. However, current vision-based tactile sensors mainly depend on geometric optics or marker tracking for tactile assessments, resulting in limited performance. To solve this dilemma, we introduce optical interference patterns as the visual representation of tactile information for flexible tactile sensors. We propose a novel tactile perception method and its corresponding sensor, combining structural colors from flexible blazed gratings with deep learning. The richer structural colors and finer data processing foster the tactile estimation performance. The proposed sensor has an overall normal force magnitude accuracy of 6 mN, a planar resolution of 79 μm and a contact-depth resolution of 25 μm. This work presents a promising tactile method that combines wave optics, soft materials and machine learning. It performs well in tactile measurement, and can be expanded into multiple sensing fields.

Indexed as

deep learningforce and tactile sensingstructural colorvision-based tactile sensorwave optics

Identifiers

PMID39764508
PMCPMC11702659

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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.