ORIGINAL RESEARCH article
Front. Bioeng. Biotechnol.
Sec. Biosensors and Biomolecular Electronics
This article is part of the Research TopicIntegration of Next-Generation Technologies with Biosensors for Advanced Diagnostics and Personalized MedicineView all 6 articles
Toward Virtual Bladder: Real-Time Bladder Volume Monitoring with Flexible AuCNT Strain Sensors
Provisionally accepted
Youngjun Cho1
Yujin Jo1Minseok Kang1Heejae Shin1Jeongmok Cho2HyungHwa Jeong3HyunSuk Peter Suh4ChangSik John Pak4Jeonhyeong Park1
Soonchul KWON5
Hongsoo Choi1Jaesok Yu1
Hoe Joon Kim1
Sanghoon Lee1*- 1Daegu Gyeongbuk Institute of Science & Technology, Daegu, Republic of Korea
- 2Ewha Womans University Mokdong Hospital, Seoul, Republic of Korea
- 3Soonchunhyang University Hospital Bucheon, Bucheon-si, Republic of Korea
- 4Asan Medical Center, Songpa-gu, Republic of Korea
- 5Kwangwoon University, Nowon-gu, Republic of Korea
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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, we introduce a flexible, stretchable strain sensor composed of gold-coated carbon nanotubes (AuCNTs) embedded in Ecoflex, designed for real-time monitoring of bladder deformation and volume changes. The sensor`s performance was evaluated using two-dimensional (balloon) and three-dimensional (porcine bladder) models, where a three-channel configuration enhanced spatial accuracy compared to single-channel designs. Sensor data enabled the creation of a preliminary "Virtual Bladder" model, providing dynamic visualization of bladder volume changes. While our current model does not yet incorporate multimodal data integration, anatomical variability, or predictive algorithms required for a full clinical digital twin, it serves as a foundational step towards developing advanced closed-loop bladder neuromodulation systems.
Keywords: Digital Twin, Bladder strain sensor, AuCNT, bladder dysfunction, Closed-loopneuromodulation
Received: 02 Oct 2025; Accepted: 02 Dec 2025.
Copyright: © 2025 Cho, Jo, Kang, Shin, Cho, Jeong, Suh, Pak, Park, KWON, Choi, Yu, Kim and Lee. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Sanghoon Lee
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