Evidence map›Paper›PMID 41826339›Full record

ArticleNature communications2026

Ultraflexible photoelectrical impedance tomography-based imager for 3-axis robotic tactile sensing.

Kun Qiao, Xuyang Feng, Linyu Dong, Limei Liu, Qing Ma, Dechun Zhao, Shang Lu, Haoyang Wang, Cunjiang Yu, Lijia Pan and 1 more

Abstract read
In one paragraph

Article in Nature communications, 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

11 authors.

Kun Qiao *School of Electronic Science & Engineering, Southeast University, Nanjing, China.ORCID http://orcid.org/0000-0002-9111-0381
Xuyang Feng *School of Electronic Science & Engineering, Southeast University, Nanjing, China.
Linyu Dong *School of Electronic Science & Engineering, Southeast University, Nanjing, China.
Limei LiuSchool of Electronic Science & Engineering, Southeast University, Nanjing, China. limeiliu@yzu.edu.cn.
Qing MaSchool of Electronic Science & Engineering, Southeast University, Nanjing, China.
Dechun ZhaoSchool of Electronic Science & Engineering, Southeast University, Nanjing, China.
Shang LuSchool of Electronic Science & Engineering, Southeast University, Nanjing, China.
Haoyang WangSchool of Electronic Science & Engineering, Southeast University, Nanjing, China. wanghaoyang@seu.edu.cn.ORCID http://orcid.org/0009-0002-1700-5919
Cunjiang YuDepartment of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA.ORCID http://orcid.org/0000-0002-0155-0368
Lijia PanSchool of Electronic Science and Engineering, Nanjing University, Nanjing, China.ORCID http://orcid.org/0000-0002-8917-7843
Binghao WangSchool of Electronic Science & Engineering, Southeast University, Nanjing, China. binghaowang@seu.edu.cn.ORCID http://orcid.org/0000-0002-9631-6901

Funding

Basic Research Program of Jiangsu Province BK20240896Basic Research Program of Jiangsu Province BK20241291National Natural Science Foundation of China (National Science Foundation of China) 22305036
6 · The paper itself

Abstract

Vision-based robotic triaxial tactile sensing provides superior spatial resolution and rich multimodal data. However, employing rigid CMOS imagers suffers from limitations in mechanical flexibility and large-area scalability. Here we present a large-area ultraflexible photoelectrical impedance tomography (PIT)-based imager that achieves high-fidelity triaxial tactile sensing. The 5-μm-thick PIT imager incorporates a quantum dots/metal-oxide heterojunction layer with 16 peripheral electrodes, significantly reducing interconnects complexity (pixel-to-interconnect ratio >80). The device exhibits a photo-to-dark-current ratio exceeding 10⁴ under ultraviolet illumination, resolves spatiotemporal features as fine as 1.5 mm, and can simultaneously image up to five occluded regions. By integrating a thin light-scattering porous rubber and flexible LEDs, triaxial force decoding is achieved through Gaussian photocurrent analysis. The system achieves over a dynamic range of 80 kPa with a normal force sensitivity of 0.04 kPa⁻¹, a shear displacement resolution of 0.17 μm kPa⁻¹, and a topological recognition accuracy of 96.5%. We anticipate that this technology will enable advanced applications in industrial and humanoid robotics, medical and rehabilitation robotics, and wearable health monitoring and human-machine interaction systems.

Identifiers

PMID41826339
PMCPMC13128857

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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.