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Engineering Sensing Systems for Medical Applications
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Engineering Sensing Systems for Medical Applications

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

Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 4384

Special Issue Editors

Prof. Dr. Pete Culmer

E-Mail Website
Guest Editor
School of Mechanical Engineering, University of Leeds, Leeds, UK
Interests: medical engineering; healthcare technology; global healthcare; sensing systems
Dr. Michael Bryant

E-Mail Website
Guest Editor
Institute of Functional Surfaces, School of Mechanical Engineering, University of Leeds, Leeds LS2 9JT, UK
Interests: medical engineering; biomedical devices; biotribology; biomechanics; implants
Prof. David Jayne

E-Mail Website
Guest Editor
Leeds Institute of Biomedical and Clinical Sciences, University of Leeds, Leeds, LS9 7TF, UK
Interests: surgical technologies; surgical devices; surgical sensing systems; robotic surgery

Special Issue Information

Dear Colleagues

Sensing systems are well-established tools in clinical practice across a variety of medical applications, and yet there is increasing demand for new innovations to support rapidly evolving healthcare systems across the globe.

The aim of this Special Issue is to reflect on the latest developments in sensor systems that target medical applications and improvements in healthcare. We particularly invite contributions from interdisciplinary teams with clinical input to discuss development and translation of sensing technology towards clinical practice. This may encompass systems that enable improved clinical assessment, guide more effective intervention or support enhanced long-term condition monitoring.

Topics of interest include (but are not limited to):

  • In vivo sensor systems (e.g., implanted devices);
  • Wearable sensor devices;
  • Sensors at the human-device interfaces (e.g., prosthetics);
  • Integration of sensing systems to inform clinical practice (e.g., Internet of Medical Things).

The team welcomes original research, case studies and reviews, please approach the Guest Editors if you would like to propose an article or discuss these topics beforehand. We look forward to your participation in this Special Issue.

Prof. Dr. Pete Culmer
Dr. Michael Bryant
Prof. David Jayne
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. 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

  • Wearable sensors
  • Implantable sensors
  • Smart sensors
  • Sensor devices and sensor arrays
  • Biomedical monitoring.

Published Papers (2 papers)

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Research

14 pages, 6536 KiB  
Article
Measurement and Processing of Thermographic Data of Passing Persons for Epidemiological Purposes
by Jiří Tesař, Lukáš Muzika, Jiří Skála, Tomáš Kohlschütter and Milan Honner
Sensors 2023, 23(6), 2945; https://0-doi-org.brum.beds.ac.uk/10.3390/s23062945 - 08 Mar 2023
Cited by 2 | Viewed by 1075
Abstract
Non-contact temperature measurement of persons during an epidemic is the most preferred measurement option because of the safety of personnel and minimal possibility of spreading infection. The use of infrared (IR) sensors to monitor building entrances for infected persons has seen a major [...] Read more.
Non-contact temperature measurement of persons during an epidemic is the most preferred measurement option because of the safety of personnel and minimal possibility of spreading infection. The use of infrared (IR) sensors to monitor building entrances for infected persons has seen a major boom between 2020 and 2022 due to the COVID-19 epidemic, but with questionable results. This article does not deal with the precise determination of the temperature of an individual person but focuses on the possibility of using infrared cameras for monitoring the health of the population. The aim is to use large amounts of infrared data from many locations to provide information to epidemiologists so they can have better information about potential outbreaks. This paper focuses on the long-term monitoring of the temperature of passing persons inside public buildings and the search for the most appropriate tools for this purpose and is intended as the first step towards creating a useful tool for epidemiologists. As a classical approach, the identification of persons based on their characteristic temperature values over time throughout the day is used. These results are compared with the results of a method using artificial intelligence (AI) to evaluate temperature from simultaneously acquired infrared images. The advantages and disadvantages of both methods are discussed. Full article
(This article belongs to the Special Issue Engineering Sensing Systems for Medical Applications)
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23 pages, 22043 KiB  
Article
ARACAM: A RGB-D Multi-View Photogrammetry System for Lower Limb 3D Reconstruction Applications
by Marco A. Barreto, Jorge Perez-Gonzalez, Hugh M. Herr and Joel C. Huegel
Sensors 2022, 22(7), 2443; https://0-doi-org.brum.beds.ac.uk/10.3390/s22072443 - 22 Mar 2022
Cited by 7 | Viewed by 2573
Abstract
In the world, there is a growing need for lower limb prostheses due to a rising number of amputations caused primarily, by diabetic foot. Researchers enable functional and comfortable prostheses through prosthetic design by integrating new technologies applied to the traditional handcrafted method [...] Read more.
In the world, there is a growing need for lower limb prostheses due to a rising number of amputations caused primarily, by diabetic foot. Researchers enable functional and comfortable prostheses through prosthetic design by integrating new technologies applied to the traditional handcrafted method for prosthesis fabrication that is still current. That is why computer vision shows to be a promising tool for the integration of 3D reconstruction that may be useful for prosthetic design. This work has the objective to design, prototype, and test a functional system to scan plaster cast molds, which may serve as a platform for future technologies for lower limb reconstruction applications. The image capture system comprises 5 stereoscopic color and depth cameras, each with 4 DOF mountings on an enveloping frame, as well as algorithms for calibration, segmentation, registration, and surface reconstruction. The segmentation metrics of dice coefficient and Hausdorff distance (HD) show strong visual similarity with an average similarity of 87% and average error of 6.40 mm, respectively. Moving forward, the system was tested on a known 3D printed model obtained from a computer tomography scan to which comparison results via HD show an average error of ≤1.93 mm thereby making the system competitive against the systems reviewed from the state-of-the-art. Full article
(This article belongs to the Special Issue Engineering Sensing Systems for Medical Applications)
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