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Biosensors
Special Issues
Advances in Flexible and Wearable Biosensors
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Advances in Flexible and Wearable Biosensors

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensors and Healthcare".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 701

Special Issue Editor

Dr. Zhenghan Shi

E-Mail Website
Guest Editor
Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
Interests: biosensors; point-of-care testing; wearable electronics; flexible electronics; bioelectronics; electrochemical sensor

Special Issue Information

Dear Colleagues,

The rapid advancement of flexible and wearable biosensors is transforming the paradigm of biomedical diagnostics and personalized healthcare. By integrating biosensors with high sensitivity, wearable devices serve as an ideal platform for the analysis of easily accessible biofluids such as sweat, saliva, interstitial fluid (ISF), tears, and even exhaled aerosols. These devices, which can seamlessly integrate with the human body, offer continuous and in situ approaches to monitor a variety of biomarkers. Given their capability of providing insights into health information non-invasively in real time, wearable technologies offer great opportunities for health management. However, challenges remain in areas such as highly sensitive sensing of trace biomarkers, reliable and low-power communication, long-term and sustainable power supply, and accurate correlation with physiological states for clinical applications.

This Special Issue aims to highlight the most recent advancements in the development, application, and integration of flexible and wearable biosensors for disease diagnosis and health monitoring. It seeks to provide an overview of the innovative materials, fabrication techniques, sensing mechanisms, and applications of these devices in the context of personalized healthcare. Original research articles as well as review papers are welcome.

I look forward to receiving your contributions to this exciting Special Issue.

Dr. Zhenghan Shi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • flexible biosensors
  • wearable biosensors
  • flexible electronics
  • multimodal biosensing
  • biofluid analysis
  • biochemical detection
  • non-invasive diagnostics
  • wearable health monitoring
  • point-of-care testing (POCT)
  • personalized healthcare

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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19 pages, 6630 KiB  
Article
Improving the Accuracy of a Wearable Uroflowmeter for Incontinence Monitoring Under Dynamic Conditions: Leveraging Machine Learning Methods
by Faezeh Shanehsazzadeh, John O. L. DeLancey and James A. Ashton-Miller
Biosensors 2025, 15(5), 306; https://doi.org/10.3390/bios15050306 - 11 May 2025
Viewed by 519
Abstract
Urinary incontinence affects many women, yet there are no monitoring devices capable of accurately capturing flow dynamics during everyday activities. Building on our initial development of a wearable personal uroflowmeter, this study enhances the device’s performance under realistic, dynamic conditions similar to those [...] Read more.
Urinary incontinence affects many women, yet there are no monitoring devices capable of accurately capturing flow dynamics during everyday activities. Building on our initial development of a wearable personal uroflowmeter, this study enhances the device’s performance under realistic, dynamic conditions similar to those encountered in daily living. We integrated an optimized eight-vane Etoile flow conditioner with a 0.2D opening into the device. Both computational fluid dynamics simulations and experimental tests demonstrated that this flow conditioner significantly reduced turbulence intensity by 82% and stabilized the axial velocity profile by 67%, increasing the R2 of flow rate measurements from 0.44 to 0.92. Furthermore, our machine learning framework—utilizing a support vector machine (SVM) and an extreme gradient boosting (XGBoost) model with principal component analysis (PCA)—accurately predicted the true flow rate with high correlations, robust performance, and minimal overfitting. For the test dataset, the SVM achieved a correlation of 0.86, an R2 of 0.74, and an MAE of 2.8, whereas the XGBoost-PCA model exhibited slightly stronger performance, with a correlation of 0.88, an R2 of 0.76, and an MAE of 2.6. These advances established a solid foundation for developing a reliable, wearable uroflowmeter capable of effectively monitoring urinary incontinence in real-world settings. Full article
(This article belongs to the Special Issue Advances in Flexible and Wearable Biosensors)
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