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Electronics
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Wearable Device Design and Its Latest Applications
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Wearable Device Design and Its Latest Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Bioelectronics".

Deadline for manuscript submissions: 15 September 2025 | Viewed by 1844

Special Issue Editor

Dr. Changhao Xu

E-Mail Website
Guest Editor
Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125, USA
Interests: machine learning; wearable sensors; medical device; robotics; digital medicine

Special Issue Information

Dear Colleagues,

Wearable devices are integrated analytical devices that can be worn on the body. These devices, encompassing smartwatches, wristbands, fabrics, patches, rings, or tattoos, serve not only as extensions of digital connectivity but also as a mobile platform for health management. They can track not only vital signs such as heart rate, blood pressure, and oxygen saturation, but also biochemical signals such as glucose, ion concentrations, and hormones at a molecular level. To date, these wearable devices provide real-time health insights, and the integration of artificial intelligence has further enhanced the predictive capabilities of health monitoring and disease diagnostics, allowing for early detection and personalized medicine.

This Special Issue of Electronics entitled “Wearable Device Design and its Latest Applications” is devoted to presenting the latest advances in wearable devices, with a particular emphasis on current developments in designs, materials, sensors, integrated systems, and robotic and biomedical applications. We welcome authors to submit their research on topics including, but not limited to, the following:

  • Soft materials for conformal skin contact;
  • Innovative wearable sensors towards new biomarkers;
  • Integrated wearable device designs and system integrations;
  • Cost-efficient and mass-producible fabrication methods for wearables;
  • Energy harvesting and power-efficient wearable systems;
  • Efficient data collection and analysis;
  • Privacy and data protection in wearable devices;
  • Artificial intelligence and machine learning tools for health predictions;
  • Exploration of integrated systems for robotics and human–machine interfaces;
  • Exploration of integrated systems for healthcare and disease applications.

Dr. Changhao Xu
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. Electronics 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 2400 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 devices
  • soft materials
  • electronic skin
  • artificial intelligence
  • nanomaterials
  • biosensors
  • bioelectronics
  • electrochemistry
  • human&ndash
  • machine interfaces
  • precision medicine
  • personalized healthcare

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

Published Papers (2 papers)

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Research

16 pages, 9045 KiB  
Article
Stabilization of Signal Decomposition Based on Frequency Entrainment Phenomena
by Keina Kitaura, Takashi Kusaka, Koji Shimatani and Takayuki Tanaka
Electronics 2025, 14(6), 1163; https://doi.org/10.3390/electronics14061163 - 16 Mar 2025
Viewed by 299
Abstract
With advancements in the miniaturization and lightweight design of computers and electronic devices, wearable sensors are now widely utilized in fields such as healthcare and medicine. Signals obtained from wearable sensors often contain a mix of biological signals and noise. Typically, wearable sensor [...] Read more.
With advancements in the miniaturization and lightweight design of computers and electronic devices, wearable sensors are now widely utilized in fields such as healthcare and medicine. Signals obtained from wearable sensors often contain a mix of biological signals and noise. Typically, wearable sensor measurements focus on a single signal of interest (SoI), treating other signals as noise. While methods for separating multiple signals exist, the stable tracking of frequency variations during signal separation remains an unresolved challenge. Biological signal and human motion measurements often face issues such as noise, temporal disconnections, dropouts, and frequency variations. To address these challenges, we developed a method that can stably separate and extract SoI from measurement data. We demonstrated the effectiveness of the proposed method through simulations replicating common measurement issues. By applying the method, we show that SoI frequency estimates can be obtained with a high accuracy. Furthermore, we confirm that the method can separate multiple SoIs from a single measurement dataset, highlighting its utility. Finally, we validate that the proposed method can reliably extract multiple SoIs, such as heart rate, walking rhythm, and breathing rate, from actual data measured using stretch sensors, achieving results consistent with simulations. Full article
(This article belongs to the Special Issue Wearable Device Design and Its Latest Applications)
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21 pages, 1560 KiB  
Article
WMLinks: Wearable Smart Devices and Mobile Phones Linking through Bluetooth Low Energy (BLE) and WiFi Signals
by Naixuan Guo, Zhaofeng Chen, Heyang Xu, Yu Liu, Zhechun Zhao and Sen Xu
Electronics 2024, 13(16), 3268; https://doi.org/10.3390/electronics13163268 - 17 Aug 2024
Cited by 2 | Viewed by 1047
Abstract
Wearable smart devices have gradually become indispensable devices in people’s lives. Their security and privacy have gained increasing popularity among the public due to their ability to monitor and record various aspects of users’ daily activities and health data. These devices maintain a [...] Read more.
Wearable smart devices have gradually become indispensable devices in people’s lives. Their security and privacy have gained increasing popularity among the public due to their ability to monitor and record various aspects of users’ daily activities and health data. These devices maintain a wireless connection with mobile phones through periodic signal transmissions, which can be intercepted and analyzed by external observers. While these signal packets contain valuable information about the device owner, the identity of the actual user remains unknown. In this study, we propose two approaches to link wearable smart devices with users’ mobile phones, which serve as electronic identities, to enable novel applications such as multi-device authentication and user-device graph construction for targeted advertising. To establish this linkage, we propose two approaches: a passive-sniffing-based linking approach and an active-interference-based linking approach, which solve the problem of sniffing Bluetooth Low Energy broadcast packets in two stages of Bluetooth Low Energy communication. Through experiments conducted across three scenarios, we demonstrate that seven wearable devices can be successfully linked with an accuracy rate exceeding 80%, with accuracy rates approaching 100% when a device is recorded more than 11 times. Additionally, we find that four wearable devices can be linked via an active-interference-based linking approach with an accuracy rate exceeding 70%. Our results highlight the potential of wearable devices and mobile phones as a means of establishing user identities and enabling the development of more sophisticated applications in the field of wearable technology. Full article
(This article belongs to the Special Issue Wearable Device Design and Its Latest Applications)
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