Evidence map›Paper›PMID 41561357›Full record

ArticleFrontiers in bioengineering and biotechnology2025

Toward virtual bladder: real-time bladder volume monitoring with flexible AuCNT strain sensors.

Youngjun Cho, Yujin Jo, Minseok Kang, Heejae Shin, Jeongmok Cho, HyungHwa Jeong, HyunSuk Peter Suh, ChangSik John Pak, Jeonhyeong Park, Soonchul Kwon and 4 more

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

14 authors.

Youngjun ChoDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea.
Yujin JoDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea.
Minseok KangDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea.
Heejae ShinDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea.
Jeongmok ChoDepartment of Plastic and Reconstruction Surgery, Ewha Womans University Medical Center, Seoul, Republic of Korea.
HyungHwa JeongDepartment of Plastic and Reconstructive Surgery, Soon Chun Hyang University Bucheon Hospital, Bucheon-Si, Republic of Korea.
HyunSuk Peter SuhDepartment of Plastic and Reconstructive Surgery, Asan Medical Center, Seoul, Republic of Korea.
ChangSik John PakDepartment of Plastic and Reconstructive Surgery, Asan Medical Center, Seoul, Republic of Korea.
Jeonhyeong ParkDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea.
Soonchul KwonDepartment of Smart Convergence, Kwangwoon University, Seoul, Republic of Korea.
Hongsoo ChoiDepartment of Biomedical Engineering, University of Massachusetts Amherst, Amherst, MA, United States.
Jaesok YuDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea.
Hoe Joon KimDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea.
Sanghoon LeeDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital twin technology holds considerable potential for personalized diagnostics and treatment of bladder dysfunction, particularly neurogenic conditions such as underactive bladder (UAB). In this study, to address the need for precise monitoring, we introduce a flexible, stretchable strain sensor composed of gold-coated carbon nanotubes (AuCNTs) embedded in Ecoflex. We specifically designed a three-channel configuration to capture anisotropic expansion and evaluated the sensor's performance using both two-dimensional balloon models and ex-vivo three-dimensional porcine bladder models. As a result, the AuCNT sensor demonstrated high sensitivity, and the three-channel design significantly enhanced spatial accuracy compared to single-channel approaches. Based on these measurements, we created a preliminary "Virtual Bladder" model that provides dynamic, real-time visualization of bladder volume changes. While our current model requires further development to incorporate multimodal data and anatomical variability, it serves as a foundational step towards developing advanced digital twin frameworks and closed-loop neuromodulation systems for bladder dysfunction.

Indexed as

AuCNTbladder dysfunctionbladder strain sensorclosed-loop neuromodulationdigital twin

Identifiers

PMID41561357
PMCPMC12813022

What OpenQuestion holds

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LicenceCC BY
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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.