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Electronics
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Electronics Application in Medicine & Health Care
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Electronics Application in Medicine & Health Care

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

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 15820

Special Issue Editors

Dr. Gabriella Casalino

E-Mail Website
Guest Editor
Department of Computer Science, University of Bari Aldo Moro, Via Orabona, 4-70125 Bari, Italy
Interests: computational intelligence; knowledge discovery from data; intelligent data analysis; matrix factorizations
Special Issues, Collections and Topics in MDPI journals
Dr. Giuseppe Coviello

E-Mail Website
Guest Editor
Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, Italy
Interests: RF; mixed-signal circuits; embedded systems for healthcare
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid development of electronics applications in daily life has led to increasing demand for more powerful and sophisticated devices in hospitals, public health facilities, and even in home environments. The design of medical devices necessarily requires the expertise of both engineering and medical experts. The use of such novel instruments can effectively enhance the success of clinical surgeries and reduce the pain and time cost of patients. Furthermore, household medical electronics and remote connections with the clinicians allow continuous monitoring of patients and early detection of changes in patients’ state, thus avoiding the worsening of their symptoms. This Special Issue will provide a platform for transdisciplinary researchers to work together and to present state-of-the-art developments of electronics in medicine and healthcare. The topics of interest include but are not limited to the following:

  • Bioelectronics
  • Biophotonics
  • Medical imaging technology, bio-imaging
  • Surgical technology
  • Monitoring devices
  • Respiration technology
  • Drug delivery systems
  • Artificial organs and biomaterials
  • Tissue engineering, bio-inspired materials, and molecular and cellular methods
  • Devices and instruments for rehabilitation
  • Telemedicine, e-health, and mobile health
  • Ambient-assisted living
  • Smart sensors for digital health
  • Artificial intelligence for Digital Health

Dr. Gabriella Casalino
Prof. Giuseppe Coviello
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 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.

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

Published Papers (2 papers)

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Review

20 pages, 1922 KiB  
Review
Edge Devices for Internet of Medical Things: Technologies, Techniques, and Implementation
by Imed Ben Dhaou, Mousameh Ebrahimi, Meriam Ben Ammar, Ghada Bouattour and Olfa Kanoun
Electronics 2021, 10(17), 2104; https://doi.org/10.3390/electronics10172104 - 31 Aug 2021
Cited by 29 | Viewed by 5797
Abstract
The health sector is currently experiencing a significant paradigm shift. The growing number of elderly people in several countries along with the need to reduce the healthcare cost result in a big need for intelligent devices that can monitor and diagnose the well-being [...] Read more.
The health sector is currently experiencing a significant paradigm shift. The growing number of elderly people in several countries along with the need to reduce the healthcare cost result in a big need for intelligent devices that can monitor and diagnose the well-being of individuals in their daily life and provide necessary alarms. In this context, wearable computing technologies are gaining importance as edge devices for the Internet of Medical Things. Their enabling technologies are mainly related to biological sensors, computation in low-power processors, and communication technologies. Recently, energy harvesting techniques and circuits have been proposed to extend the operating time of wearable devices and to improve usability aspects. This survey paper aims at providing an overview of technologies, techniques, and algorithms for wearable devices in the context of the Internet of Medical Things. It also surveys the various transformation techniques used to implement those algorithms using fog computing and IoT devices. Full article
(This article belongs to the Special Issue Electronics Application in Medicine & Health Care)
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24 pages, 2079 KiB  
Review
Development Status and Multilevel Classification Strategy of Medical Robots
by Yingwei Guo, Yingjian Yang, Yang Liu, Qiang Li, Fengqiu Cao, Mengting Feng, Hanhui Wu, Wei Li and Yan Kang
Electronics 2021, 10(11), 1278; https://doi.org/10.3390/electronics10111278 - 27 May 2021
Cited by 11 | Viewed by 7584
Abstract
The combination of artificial intelligence technology and medical science has inspired the emergence of medical robots with novel functions that use new materials and have a neoteric appearance. However, the diversity of medical robots causes confusion regarding their classification. In this paper, we [...] Read more.
The combination of artificial intelligence technology and medical science has inspired the emergence of medical robots with novel functions that use new materials and have a neoteric appearance. However, the diversity of medical robots causes confusion regarding their classification. In this paper, we review the concepts pertinent to major classification methods and development status of medical robots. We survey the classification methods according to the appearance, function, and application of medical robots. The difficulties surrounding classification methods that arose are discussed, for example, (1) it is difficult to make a simple distinction among existing types of medical robots; (2) classification is important to provide sufficient applicability to the existing and upcoming medical robots; (3) future medical robots may destroy the stability of the classification framework. To solve these problems, we proposed an innovative multilevel classification strategy for medical robots. According to the main classification method, the medical robots were divided into four major categories—surgical, rehabilitation, medical assistant, and hospital service robots—and personalized classifications for each major category were proposed in secondary classifications. The technologies currently available or in development for surgical robots and rehabilitation robots are discussed with great emphasis. The technical preferences of surgical robots in the different departments and the rehabilitation robots in the variant application scenes are perceived, by which the necessity of further classification of the surgical robots and the rehabilitation robots is shown and the secondary classification strategy for surgical robots and rehabilitation robots is provided. Our results show that the distinctive features of surgical robots and rehabilitation robots can be highlighted and that the communication between professionals in the same and other fields can be improved. Full article
(This article belongs to the Special Issue Electronics Application in Medicine & Health Care)
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