Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.0
3.0
Journals
Micromachines
Special Issues
Wearable Biosensors: From Materials to Systems
share announcement

Wearable Biosensors: From Materials to Systems

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "B1: Biosensors".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 1646

Special Issue Editors

Prof. Dr. Ivo Iliev

E-Mail Website
Guest Editor
Department of Electronics, Faculty of Electronic Engineering and Technology, Technical University of Sofia, 8 Kliment Ohridski Blvd., 1000 Sofia, Bulgaria
Interests: wearable devices; remote patient monitoring; capacitive electrodes; CECG
Dr. Mariya Aleksandrova

E-Mail Website
Guest Editor
Department of Microelectronics, Technical University of Sofia, 8 Kliment Ohridski Blvd., 1000 Sofia, Bulgaria
Interests: wearable devices; microfabrication; energy harvesting and storage
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The use of wearable recording systems is increasingly recognized in medical practice as a reliable method for diagnostics and for both clinical and remote healthcare delivery. Scientific research mainly focuses on challenges related to materials, fabrication technologies, software, and hardware solutions, ensuring the accurate recording of biochemical indicators and vital parameters with minimal discomfort for users. For example, capacitive electrodes are used more often for the continuous monitoring of heart rate, respiration, temperature, and other parameters by depositing chemically resistant nanocoatings on various flexible substrates. Biosensors are central to wearable healthcare technologies, enabling the real-time, precise detection of a wide range of biochemical and physiological markers. Their integration into wearable systems offers potential for early diagnosis, continuous health monitoring, and personalized medicine. Advances in biosensor design that incorporate novel materials, innovative fabrication techniques, self-sustainable power supplies, and system integration are essential to overcoming current limitations and unlocking their full potential in medical and health applications. Accordingly, this Special Issue aims to present research papers, short communications, and review articles focusing on innovative methodological developments in wearable biosensors and devices, as well as their applications for various biochemical and biomedical purposes. The Special Issue also seeks to highlight recent progress and future prospects in developing wearable biosensors, from material innovations to system-level implementations, ultimately improving patient outcomes and transforming healthcare practice.

Prof. Dr. Ivo Iliev
Dr. Mariya Aleksandrova
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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. Micromachines 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 2100 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

  • wearable biosensors
  • materials for biomedical sensors
  • nanomaterials for enhanced biosensing
  • personalized healthcare
  • remote health monitoring
  • biocompatible materials
  • soft electronics
  • capacitive electrodes

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

11 pages, 1114 KB  
Article
Evaluation of 3D-Printed Dry Electrodes for Surface Electromyography in Dynamic Muscle Assessment
by Ahmad O. Alokaily, Ahmed A. Aldohbeyb, Mohamed A. Almadi, Fahed K. Alnawfal, Shahad N. Alshamlan, Suhail S. Alshahrani, Khalid Alhussaini, Alaa M. Albishi, Khalid I. Aloraini, Ahmad Zahid Rao and Ziyad Aloqalaa
Micromachines 2026, 17(5), 504; https://doi.org/10.3390/mi17050504 - 22 Apr 2026
Viewed by 268
Abstract
Surface electromyography (sEMG) is widely used to assess muscle activity in clinical and research settings. However, while conventional wet electrodes have advanced considerably in recent years, they are often limited by disposability, reduced comfort, and limited reusability. Recent advances in additive manufacturing provide [...] Read more.
Surface electromyography (sEMG) is widely used to assess muscle activity in clinical and research settings. However, while conventional wet electrodes have advanced considerably in recent years, they are often limited by disposability, reduced comfort, and limited reusability. Recent advances in additive manufacturing provide opportunities to fabricate customizable, low-cost dry electrodes using conductive filaments. This study aimed to evaluate the feasibility and signal performance of in-house-fabricated 3D-printed sEMG electrodes made from three commercially available conductive filaments, (Fili, Filaflex, and Proto-Pasta) differing in base polymer and resistivity, and compared their performance with standard wet electrodes. Surface electrodes were placed over the biceps brachii muscle, and EMG signals were recorded during concentric–eccentric elbow flexion under three loading conditions (3, 5, and 7 kg). Signal quality was assessed using EMG amplitude, signal-to-noise ratio (SNR), and background noise. The results showed no significant differences in SNR or background noise between the 3D-printed electrodes and standard wet electrodes. Among the tested materials, Proto-Pasta electrodes produced the highest mean EMG amplitudes, while Filaflex electrodes showed slightly lower background noise, although these differences were not statistically significant. Overall, the findings indicate that in-house-fabricated 3D-printed electrodes can provide signal quality comparable to conventional wet electrodes, supporting their potential use as low-cost and customizable alternatives for sEMG applications in research and wearable monitoring systems. Full article
(This article belongs to the Special Issue Wearable Biosensors: From Materials to Systems)
►▼ Show Figures

Figure 1

13 pages, 1340 KB  
Article
Method for Patterning of Conductive Polymers on Flexible Substrates with Possible Applications for Wearable Sensing
by Mariya Aleksandrova, Georgi Nikolov, Valentin Mateev, Rade Tomov and Ivo Iliev
Micromachines 2026, 17(4), 467; https://doi.org/10.3390/mi17040467 - 12 Apr 2026
Viewed by 298
Abstract
This study presents a novel fabrication approach for the precise patterning of conductive polymer coatings (graphene/PEDOT:PSS) on flexible substrates. Traditional lithographic methods often result in chemical or thermal degradation of polymer chains, compromising electrical conductivity. The proposed method utilizes an inversely structured gold [...] Read more.
This study presents a novel fabrication approach for the precise patterning of conductive polymer coatings (graphene/PEDOT:PSS) on flexible substrates. Traditional lithographic methods often result in chemical or thermal degradation of polymer chains, compromising electrical conductivity. The proposed method utilizes an inversely structured gold nanocoating (400–450 nm) as a sacrificial template. By employing a selective lift-off process in a potassium iodide solution, high-resolution polymer topologies are achieved without damaging the active material. The resulting structures exhibit a sheet resistance of 90–100 Ω/sq and maintain linear sensitivity to temperature and humidity, making them suitable for next-generation wearable medical diagnostics. Full article
(This article belongs to the Special Issue Wearable Biosensors: From Materials to Systems)
►▼ Show Figures

Figure 1

16 pages, 1864 KB  
Article
A Novel Fabric Strain Sensor Array with Hybrid Deep Learning for Accurate Knee Movement Recognition
by Tao Chen, Xiaobin Chen and Fei Wang
Micromachines 2026, 17(1), 56; https://doi.org/10.3390/mi17010056 - 30 Dec 2025
Viewed by 679
Abstract
This paper presents a novel lightweight fabric strain sensor array specifically designed for comprehensive knee joint monitoring. The sensor system features a unique two-layer design incorporating eight strategically positioned sensing elements, enabling effective spatial mapping of strain distribution across the knee during movement. [...] Read more.
This paper presents a novel lightweight fabric strain sensor array specifically designed for comprehensive knee joint monitoring. The sensor system features a unique two-layer design incorporating eight strategically positioned sensing elements, enabling effective spatial mapping of strain distribution across the knee during movement. This configuration offers advantages in capturing complex multi-axis kinematics (flexion/extension, rotation) and localized tissue deformation when compared to simpler sensor layouts. To evaluate the system, ten subjects performed three distinct activities (seated leg raise, standing, walking), generating resistance data from the sensors. A hybrid deep learning model (CNN + BiLSTM + Attention) processed the data and significantly improved performance to 95%. This enhanced accuracy is attributed to the model’s ability to extract spatial-temporal features and leverage long-term dependencies within the time-series sensor data. Furthermore, channel attention analysis within the deep learning model identified sensors 2, 4, and 6 as major contributors to classification performance. The results demonstrate the feasibility of the proposed fabric sensor array for accurately recognizing fundamental knee movements. Despite limitations in the diversity of postures, this system holds significant promise for future applications in rehabilitation monitoring, sports science analytics, and personalized healthcare within the medical and athletic domains. Full article
(This article belongs to the Special Issue Wearable Biosensors: From Materials to Systems)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop