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Electronics
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Wearable Sensors and Its Applications: Revolutionizing Healthcare, Fitness, and Beyond
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Wearable Sensors and Its Applications: Revolutionizing Healthcare, Fitness, and Beyond

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electronic Materials, Devices and Applications".

Deadline for manuscript submissions: closed (15 April 2025) | Viewed by 3585

Special Issue Editor

Dr. Haider Raad

E-Mail Website
Guest Editor
Xavier Wearable Electronics Research Center, Department of Physics, Xavier University, 3800 Victory Parkway, Cincinnati, OH 45207, USA
Interests: flexible and wearable wireless systems; wearable sensors; Internet of Things; brain–machine interface; telemedicine and wireless body area networks; metamaterials; MIMO
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wearable sensors have emerged as a pivotal technology, revolutionizing various fields, including healthcare, fitness, and environmental monitoring. This Special Issue aims to showcase the latest advancements in wearable sensor design, materials, and applications. Contributions will explore a wide range of topics, such as:

  • Novel sensor materials and fabrication techniques: Advances in flexible, stretchable, and biocompatible materials for wearable sensors;
  • Sensor integration and miniaturization: Techniques for seamlessly integrating sensors into clothing, accessories, or directly on the body;
  • Data processing and analysis: Algorithms for extracting meaningful information from wearable sensor data, including machine learning and artificial intelligence applications;
  • Healthcare applications: Wearable sensors for continuous health monitoring, disease diagnosis, and treatment (telemedicine);
  • Fitness and wellness: Wearable devices for tracking physical activity, sleep, and stress levels;
  • Human–computer interactions: Wearable sensors for enhancing user experiences and enabling new forms of interaction;
  • Antennas for wearable technology and body area networks.

This Special Issue will provide a comprehensive overview of the current state-of-the-art in wearable sensor technology and highlight emerging trends and challenges. By fostering interdisciplinary collaboration and knowledge sharing, this collection of papers will contribute to the continued development and adoption of wearable sensors across various domains.

Dr. Haider Raad
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
  • wearable sensors
  • wearable technology

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Published Papers (1 paper)

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Research

39 pages, 1250 KiB  
Article
Recent Advances in Big Medical Image Data Analysis Through Deep Learning and Cloud Computing
by Mohammed Y. Shakor and Mustafa Ibrahim Khaleel
Electronics 2024, 13(24), 4860; https://doi.org/10.3390/electronics13244860 - 10 Dec 2024
Cited by 2 | Viewed by 2978
Abstract
This comprehensive study investigates the integration of cloud computing and deep learning technologies in medical data analysis, focusing on their combined effects on healthcare delivery and patient outcomes. Through a methodical examination of implementation instances at various healthcare facilities, we investigate how well [...] Read more.
This comprehensive study investigates the integration of cloud computing and deep learning technologies in medical data analysis, focusing on their combined effects on healthcare delivery and patient outcomes. Through a methodical examination of implementation instances at various healthcare facilities, we investigate how well these technologies manage a variety of medical data sources, such as wearable device data, medical imaging data, and electronic health records (EHRs). Our research demonstrates significant improvements in diagnostic accuracy (15–20% average increase) and operational efficiency (60% reduction in processing time) when utilizing cloud-based deep learning systems. We found that healthcare organizations implementing phased deployment approaches achieved 90% successful integration rates, while hybrid cloud architectures improved regulatory compliance by 50%. This study also revealed critical challenges, with 35% of implementations facing data integration issues and 5% experiencing security breaches. Through empirical analysis, we propose a structured implementation framework that addresses these challenges while maintaining high performance standards. Our findings indicate that federated learning techniques retain 95% model accuracy while enhancing privacy protection, and edge computing reduces latency by 40% in real-time processing. By offering quantitative proof of the advantages and difficulties of combining deep learning and cloud computing in medical data analysis, as well as useful recommendations for healthcare organizations seeking technological transformation, this study adds to the expanding body of knowledge on healthcare digitalization. Full article
(This article belongs to the Special Issue Wearable Sensors and Its Applications: Revolutionizing Healthcare, Fitness, and Beyond)
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