Evidence map›Paper›PMID 39081833›Full record

ArticleCyborg and bionic systems (Washington, D.C.)2022

A Novel Biopsy Capsule Robot Based on High-Speed Cutting Tissue.

Zhibin Song, Wenjie Zhang, Wenhui Zhang, Dario Paolo

Abstract read
In one paragraph

Article in Cyborg and bionic systems (Washington, D.C.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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  12. The State-of-the-Art and Perspectives of Laser Ablation for Tumor Treatment.Cyborg and bionic systems (Washington, D.C.) · 2024
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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

4 authors.

Zhibin SongKey Laboratory of Mechanism Theory and Equipment Design of the Ministry of Education, Tianjin University, Tianjin 300072, China.
Wenjie ZhangKey Laboratory of Mechanism Theory and Equipment Design of the Ministry of Education, Tianjin University, Tianjin 300072, China.ORCID https://orcid.org/0000-0002-5016-6725
Wenhui ZhangBeijing Shijitan Hospital, Capital Medical University, Beijing 100084, China.
Dario PaoloKey Laboratory of Mechanism Theory and Equipment Design of the Ministry of Education, Tianjin University, Tianjin 300072, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The capsule robot (CR) is a promising endoscopic method in gastrointestinal diagnosis because of its low discomfort to users. Most CRs are used to acquire image information only and lack the ability to collect samples. Although some biopsy capsule robots (BCRs) have been developed, it remains challenging to acquire the intestinal tissue while avoiding tearing and adhesion due to the flexibility of colonic tissue. In this study, we develop a BCR with a novel sampling strategy in which soft tissue is scratched with sharp blades rotating at high speed to avoid tissue tearing. In the BCR design, a spiral spring with prestored energy is used to release high energy within a short period of time, which is difficult for a motor or magnet to perform within a small capacity installation space. The energy of the tightened spiral spring is transmitted to drive sharp blades to rotate quickly via a designed gear mechanism. To guarantee reliable sampling, a Bowden cable is used to transmit the user's manipulation to trigger the rotation of the blades, and the triggering force transmitted by the cable can be monitored in real time by a force sensor installed at the manipulating end. A prototype of the proposed BCR is designed and fabricated, and its performance is tested through in vitro experiments. The results show that the proposed BCR is effective and the size of its acquired samples satisfies clinical requirements.

Identifiers

PMID39081833
PMCPMC11288281

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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.