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Smart Textile Sensors, Actuators, and Related Applications
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Smart Textile Sensors, Actuators, and Related Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".

Deadline for manuscript submissions: 20 December 2025 | Viewed by 3308

Special Issue Editor

Dr. Dhaval Solanki

E-Mail Website
Guest Editor
Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881, USA
Interests: wearable devices; biosignal processing; virtual reality and assistive and physiology-sensitive systems for neuro-rehabilitation

Special Issue Information

Dear Colleagues,

The integration of smart textiles into healthcare has revolutionized wearable technologies, offering innovative solutions for personalized and continuous health monitoring. With advancements in e-textile development, wearable sensors, IoT, and AI, smart textiles now provide cost-effective, accessible, and customizable healthcare services. Despite these benefits, challenges such as flexibility, durability, safety, and energy efficiency must be addressed to create reliable and future-ready wearable systems. This Special Issue focuses on the transformative role of smart textiles in healthcare, exploring their applications in physical health monitoring, telemedicine, and advanced medical interventions. It also highlights the intersections of the hardware innovations, data analytics, and security protocols necessary to realize their full potential. Authors are invited to contribute original research and reviews that delve into cutting-edge developments in smart textiles for healthcare, IoT-enabled e-textiles, augmented reality applications, and secure wearable systems for data-driven medical insights. Authors are invited to submit high quality papers related, but not limited to, the following topics:

  • Smart textiles in healthcare;
  • Wearable e-textile biosensors;
  • IoT-enabled smart fabrics;
  • Flexible and durable health monitoring systems;
  • Secure and scalable e-textile wearable technologies;
  • Smart textile wearables for continuous physical health monitoring;
  • Remote patient tracking and telemedicine through smart textiles;
  • VR/AR-based technologies with smart textiles.

Dr. Dhaval Solanki
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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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

  • smart textiles
  • textile biosensors
  • e-textiles in healthcare
  • IoT-enabled wearable systems
  • flexible and durable health monitoring
  • AI in smart textile applications

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Published Papers (3 papers)

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Research

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19 pages, 5105 KiB  
Article
Development and Assessment of a Soft Wearable for sEMG-Based Hand Grip Detection and Control of a Virtual Environment
by Lohith Chatragadda, Aiden Fletcher, Sam Zhong, Fabian A. Vargas, Nishtha Bhagat, Kunal Mankodiya, Matthew J. Delmonico and Dhaval Solanki
Sensors 2025, 25(8), 2431; https://doi.org/10.3390/s25082431 - 12 Apr 2025
Viewed by 668
Abstract
Background: As the number of individuals diagnosed with neurodegenerative disorders (NDs) rises, there is a growing need to enhance both the quantity and quality of approaches used to treat these debilitating conditions. The progression of NDs can cause muscle weakness in the lower [...] Read more.
Background: As the number of individuals diagnosed with neurodegenerative disorders (NDs) rises, there is a growing need to enhance both the quantity and quality of approaches used to treat these debilitating conditions. The progression of NDs can cause muscle weakness in the lower or upper limbs. We particularly focus on the area of the upper limb, specifically grip rehabilitation, by developing a system (VRGrip) that can reliably record electromyography (EMG) events of the hand flexor muscles to control an adaptive and engaging game using grip exertion. The purpose of this study was to determine the feasibility of using the VRGrip system. Methods: We prototyped a three-component wearable system consisting of an e-textile forearm band (E-band), data acquisition module (DAM), and a computer game. This allows participants to play a game by squeezing their dominant hand. A feasibility study was completed with 9 individuals who self-reported an ND (including Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS), Charcot–Marie–Tooth disease (CMT), spinal muscular atrophy (SMA), and essential tremor (ET)) and 12 individuals who self-reported to be relatively healthy (RH). Each participant completed 15 min of gameplay (three trials of five minutes), where they would squeeze a resistive ball to trigger in-game actions. The user experience was then evaluated via a User Satisfaction Evaluation Questionnaire (USEQ; scored 0–30, with 30 being best). Results: Analysis of the grip detection reliability during the feasibility study resulted in an F1 score of 0.8343 ± 0.1208 for the healthy participant group and 0.8401 ± 0.1034 for the ND participant group. The USEQ (Avg. score: 4.65 ± 0.51) indicated that participants found the system comfortable, engaging, and enjoyable. Additionally, we potentially identified age-related changes in muscle fatigue. Conclusion: The results of this study demonstrate that our VRGrip system could be used for hand grip detection in a virtual environment. In the future, we aim to conduct longitudinal studies to determine if repeated use of the system has merit for grip rehabilitation. Full article
(This article belongs to the Special Issue Smart Textile Sensors, Actuators, and Related Applications)
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19 pages, 3686 KiB  
Article
Respiratory Monitoring with Textile Inductive Electrodes in Driving Applications: Effect of Electrode’s Positioning and Form Factor on Signal Quality
by James Elber Duverger, Victor Bellemin, Geordi-Gabriel Renaud Dumoulin, Patricia Forcier, Justine Decaens, Ghyslain Gagnon and Alireza Saidi
Sensors 2025, 25(7), 2035; https://doi.org/10.3390/s25072035 - 25 Mar 2025
Viewed by 341
Abstract
This paper provides insights into where and how to integrate textile inductive electrodes into a car to record optimal-quality respiratory signals. Electrodes of various shapes and sizes were integrated into the seat belt and the seat back of a driving simulator car seat. [...] Read more.
This paper provides insights into where and how to integrate textile inductive electrodes into a car to record optimal-quality respiratory signals. Electrodes of various shapes and sizes were integrated into the seat belt and the seat back of a driving simulator car seat. The electrodes covered various parts of the body: upper back, middle back, lower back, chest, and waist. Three subjects completed driving circuits with their breathing signals being recorded. In general, signal quality while driving versus sitting still was similar, compared to a previous study of ours with no body movements. In terms of positioning, electrodes on seat belt provided better signal quality compared to seat back. Signal quality was directly proportional to electrode’s height on the back, with upper back outperforming both middle and lower back. Electrodes on the waist provided either similar or superior signal quality compared to electrodes on the chest. In terms of form factor, rectangular shape outperformed circular shape on seat back. Signal quality is proportional to the size of circular electrodes on seat back, and inversely proportional to size of rectangular electrode on seat belt. Full article
(This article belongs to the Special Issue Smart Textile Sensors, Actuators, and Related Applications)
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Other

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19 pages, 450 KiB  
Systematic Review
Smart Textile Technology for the Monitoring of Mental Health
by Shonal Fernandes, Alberto Ramos, Mario Vega-Barbas, Carolina García-Vázquez, Fernando Seoane and Iván Pau
Sensors 2025, 25(4), 1148; https://doi.org/10.3390/s25041148 - 13 Feb 2025
Viewed by 1919
Abstract
In recent years, smart devices have proven their effectiveness in monitoring mental health issues and have played a crucial role in providing therapy. The ability to embed sensors in fabrics opens new horizons for mental healthcare, addressing the growing demand for innovative solutions [...] Read more.
In recent years, smart devices have proven their effectiveness in monitoring mental health issues and have played a crucial role in providing therapy. The ability to embed sensors in fabrics opens new horizons for mental healthcare, addressing the growing demand for innovative solutions in monitoring and therapy. The objective of this review is to understand mental health, its impact on the human body, and the latest advancements in the field of smart textiles (sensors, electrodes, and smart garments) for monitoring physiological signals such as respiration rate (RR), electroencephalogram (EEG), electrodermal activity (EDA), electrocardiogram (ECG), and cortisol, all of which are associated with mental health disorders. Databases such as Web of Science (WoS) and Scopus were used to identify studies that utilized smart textiles to monitor specific physiological parameters. Research indicates that smart textiles provide promising results compared to traditional methods, offering enhanced comfort for long-term monitoring. Full article
(This article belongs to the Special Issue Smart Textile Sensors, Actuators, and Related Applications)
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