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Next-Generation Wearable Technologies: Integrating Smart Sensing, Biomedical Innovation, and Sustainable...
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Next-Generation Wearable Technologies: Integrating Smart Sensing, Biomedical Innovation, and Sustainable Energy Solutions

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "E：Engineering and Technology".

Deadline for manuscript submissions: closed (30 November 2025) | Viewed by 2112

Special Issue Editor

Dr. Alwathiqbellah Ibrahim

E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of Texas at Tyler, 3900 University Blvd., Tyler, TX 75799, USA
Interests: micro-electromechanical systems (MEMSs); vibrations; the linear and nonlinear dynamics of mechanical systems; solid mechanics and biomechanics; energy-harvesting systems; smart materials and orthopedic devices; novel sensor systems for human and animal health monitoring; wearable sensors; smart materials; next-generation diagnostic tools
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue explores next-generation wearable technologies, focusing on the integration of smart sensing, biomedical innovation, and sustainable energy solutions. It explores the innovative progress made in the development of intelligent, energy-efficient, and multifunctional wearable systems that can enhance various industries, including healthcare, fitness, and smart devices. These advancements are driving the evolution of wearable and biomedical technologies, enabling real-time monitoring, adaptive sensing, and sustainable operations in interconnected smart ecosystems.

This Special Issue aims to showcase cutting-edge advancements, address key challenges, and discuss emerging trends in wearable technologies, including smart sensing, biomedical applications, and self-powered systems. Potential topics of interest include but are not limited to the following:

  • Smart sensors and innovative sensing mechanisms for wearable applications;
  • Biomedical and health-monitoring wearable technologies;
  • Energy-harvesting and self-powered systems for wearables;
  • Advanced materials and designs for intelligent wearable devices;
  • The integration of sensing, energy management, and wireless communication in wearables;
  • Machine learning and AI-driven data processing for wearable applications;
  • Wearable technologies for healthcare, rehabilitation, fitness, and environmental monitoring.

Dr. Alwathiqbellah Ibrahim
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 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 technologies
  • smart sensors
  • biomedical sensing
  • self-powered systems
  • energy harvesting
  • health monitoring
  • adaptive sensing
  • sustainable electronics

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Published Papers (2 papers)

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Research

26 pages, 23199 KB  
Article
Development and Validation of a Multimodal Wearable Belt for Abdominal Biosignal Monitoring with Application to Irritable Bowel Syndrome
by Amir Mohammad Karimi Forood, Sibi M. Pandian, Riley Q. McNaboe, Thuany De Carvalho Lachos, Daniel Octavio Lantigua and Hugo F. Posada-Quintero
Micromachines 2025, 16(11), 1255; https://doi.org/10.3390/mi16111255 - 1 Nov 2025
Viewed by 687
Abstract
Visceral pain in Irritable Bowel Syndrome (IBS) is difficult to evaluate objectively due to its complex physiological nature and lack of reliable biomarkers. Given the complexity of IBS, a multimodal physiological monitoring approach, combining electrodermal activity (EDA), electrocardiogram (ECG), and surface electromyography (sEMG), [...] Read more.
Visceral pain in Irritable Bowel Syndrome (IBS) is difficult to evaluate objectively due to its complex physiological nature and lack of reliable biomarkers. Given the complexity of IBS, a multimodal physiological monitoring approach, combining electrodermal activity (EDA), electrocardiogram (ECG), and surface electromyography (sEMG), offers a promising approach to capture the autonomic and muscular responses linked to visceral pain. However, no existing wearable device supports simultaneous EDA, ECG, and sEMG acquisition from the abdomen in a format suitable for long-term, real-world use. This study presents the development and validation of a novel wearable belt for concurrent ECG, sEMG, and EDA monitoring, with EDA measured at both the torso and wrist. The system was built using modified BITalino platforms with custom-fabricated reusable electrodes and Bluetooth connectivity for real-time smartphone display. Signal quality was validated against laboratory-grade systems in 20 healthy participants during a four-stage protocol involving cognitive, orthostatic, muscular, and combined stress tasks. Time and frequency-domain analyses showed high correlations and comparable spectral features across all modalities. The belt maintained stable skin contact even during movement-intensive tasks. By enabling anatomically targeted, multimodal data acquisition, this wearable system supports real-world visceral pain assessment in IBS and is ready for deployment in ambulatory and home-based monitoring scenarios. Full article
(This article belongs to the Special Issue Next-Generation Wearable Technologies: Integrating Smart Sensing, Biomedical Innovation, and Sustainable Energy Solutions)
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20 pages, 23523 KB  
Article
A Wrist Brace with Integrated Piezoelectric Sensors for Real-Time Biomechanical Monitoring in Weightlifting
by Sofia Garcia, Ethan Ortega, Mohammad Alghamaz, Alwathiqbellah Ibrahim and En-Tze Chong
Micromachines 2025, 16(7), 775; https://doi.org/10.3390/mi16070775 - 30 Jun 2025
Viewed by 1143
Abstract
This study presents a self-powered smart wrist brace integrated with a piezoelectric sensor for real-time biomechanical monitoring during weightlifting activities. The system was designed to quantify wrist flexion across multiple loading conditions (0 kg, 0.5 kg, and 1.0 kg), leveraging mechanical strain-induced voltage [...] Read more.
This study presents a self-powered smart wrist brace integrated with a piezoelectric sensor for real-time biomechanical monitoring during weightlifting activities. The system was designed to quantify wrist flexion across multiple loading conditions (0 kg, 0.5 kg, and 1.0 kg), leveraging mechanical strain-induced voltage generation to capture angular displacement. A flexible PVDF film was embedded within a custom-fitted wrist brace and tested on male and female participants performing controlled wrist flexion. The resulting voltage signals were analyzed to extract root-mean-square (RMS) outputs, calibration curves, and sensitivity metrics. To interpret the experimental results analytically, a lumped-parameter cantilever beam model was developed, linking wrist flexion angles to piezoelectric voltage output based on mechanical deformation theory. The model assumed a linear relationship between wrist angle and induced strain, enabling theoretical voltage prediction through simplified material and geometric parameters. Model-predicted voltage responses were compared with experimental measurements, demonstrating a good agreement and validating the mechanical-electrical coupling approach. Experimental results revealed consistent voltage increases with both wrist angle and applied load, and regression analysis demonstrated strong linear or mildly nonlinear fits with high R2 values (up to 0.994) across all conditions. Furthermore, surface plots and strain sensitivity analyses highlighted the system’s responsiveness to simultaneous angular and loading changes. These findings validate the smart wrist brace as a reliable, low-power biomechanical monitoring tool, with promising applications in injury prevention, rehabilitation, and real-time athletic performance feedback. Full article
(This article belongs to the Special Issue Next-Generation Wearable Technologies: Integrating Smart Sensing, Biomedical Innovation, and Sustainable Energy Solutions)
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