Evidence map›Paper›PMID 42359258›Full record

ArticleCyborg and bionic systems (Washington, D.C.)2026

Enhancing Shape Sensing of Slender Medical Continuum Robot Using Carbon Nanotube Piezoresistive Fiber Bandage.

Pingyu Xiang, Xiangyu Mi, Hongye Zhang, Fei Wang, Xiong Yang, Yue Wang, Rong Xiong, Song Liu, Haojian Lu

Abstract read
In one paragraph

Article in Cyborg and bionic systems (Washington, D.C.), 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

9 authors.

Pingyu XiangDepartment of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Xiangyu MiDepartment of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Hongye ZhangDepartment of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Fei WangDepartment of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Xiong YangDepartment of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.
Yue WangDepartment of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Rong XiongDepartment of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Song LiuSchool of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China.
Haojian LuDepartment of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China.ORCID https://orcid.org/0000-0002-1393-3040

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Slender medical continuum robots with flexibility and highly redundant degrees of freedom are widely used in various minimally invasive surgery. However, when interacting with anatomical structures, the continuum robot adopts diverse shapes, posing challenges for operation and control. To achieve real-time intraoperative shape sensing and provide online guidance for manipulation, most existing methods rely on optical fibers embedded within the robot, which often require specialized robot designs and come with high costs. Here, we present a novel approach utilizing thin and flexible carbon nanotube piezoresistive fibers as a bandage, helically integrated on the surface of existing slender medical continuum robots for shape sensing. The spatial configuration of the robot is effectively inferred by downsampling the resistance changes along the robot's body and applying a learning-based method. The results demonstrate that the proposed helically arranged carbon nanotube piezoresistive fibers, combined with a data-driven approach, are capable of reconstructing the robot's spatial shape. In vitro and ex vivo experiments on animal tissues further highlight its promising potential for enhancing the shape-sensing ability of existing medical continuum robots.

Identifiers

PMID42359258
PMCPMC13291483

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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.