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COVID-19 and Wearable Medical Sensors

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

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 2020

Special Issue Editors


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Guest Editor
AP-HP Assistance Publique - Hopitaux de Parisdisabled, Paris, France
Interests: sleep; epidemiology; wearables sensors

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Guest Editor
Université Paris Descartes, APHP, Hôtel-Dieu de Paris, Centre du Sommeil et de la Vigilance et EA 7330 VIFASOM, Paris, France
Interests: wearables sensors; nearables sensors; epidemiology; digital therapeutics; sleep

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Guest Editor
Imperial College London St Mary's Hospital, London W2 1NY, UK
Interests: wearable sensors; digital health; mhealth; implementation strategies
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Special Issue Information

Dear Colleagues,

Since the start of COVID-19, digitisation has further accelerated with remote solutions being at the forefront to minimise risk of viral transmission. Wearables have  considerably grown during the COVID-19 pandemic. As this continues, the potential of wearable solutions will still grow wherever there are demands that need to be met. Such technologies can provide an early-warning system about detecting COVID-19 infection and in infection surveillance. Currently, wearable technologies are smart electronic devices which can be worn to automatically collect, monitor, analyse and communicate data.  A variety of sensing solutions exist, such as a wearable patch, smartwatches, wristbands, biosensors in garments, skin tattoos, and other accessories

The continued advancement in these digital technologies have resulted in a variety of data that can be recorded, including physiological biometric parameters (e.g., heart rate, respiratory rate, temperature), activity levels, and sleep.  This diversification into varying fields has broad enormous potentials, subject to taking in account the reliability and acceptability of the implemented technologies.

One such example is the use of wearable sensors, and digital therapeutics, coupled with digital alerts, which has potential to support clinical decision making, enhance healthcare efficiency, recognise earlier deterioration, and monitor recovery; in doing so, improve clinical outcomes. 

This special issue aims to explore original developments and the use of wearable sensors within the COVID-19 era Submissions should address, but are not limited to, the following topics: the detection of COVID-19; remote monitoring of biometric or non-biometric data; AI technology with e-health aiding clinical decision making and treatment; telehealth technology and monitoring recovery from COVID-19.

Studies testing feasibility, reliability, validation, sensor device concepts, and implementation strategies are welcomed.  This issue welcomes original research contributions and review articles to allow readers to learn about advances in wearable medical sensor technology.

Dr. Arnaud Métlaine
Dr. Maxime Elbaz
Dr. Fahad M. Iqbal
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

  • monitoring, ambulatory
  • patient deterioration
  • remote sensing technology
  • wearable electronic devices
  • m-health
  • e-health
  • digital health
  • wearable technology
  • biosensing techniques
  • ambulatory monitoring
  • outpatient monitoring
  • monitoring, physiologic
  • patient monitoring
  • telemetry
  • biosensors
  • biotechnology

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Published Papers (1 paper)

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Research

10 pages, 634 KiB  
Communication
Wireless Body Area Network for Preventing Self-Inoculation Transmission of Respiratory Viral Diseases
by Łukasz Pawlicki, Alicja Fotyga, Jakub Rewieński, Mateusz Groth, Łukasz Kulas and Grzegorz Fotyga
Sensors 2023, 23(4), 2042; https://doi.org/10.3390/s23042042 - 11 Feb 2023
Viewed by 1551
Abstract
This paper proposes an idea of Wireless Body Area Networks (WBANs) based on Bluetooth Low-Energy (BLE) standards to recognize and alarm a gesture of touching the face, and in effect, to prevent self-inoculation of respiratory viral diseases, such as COVID-19 or influenza A, [...] Read more.
This paper proposes an idea of Wireless Body Area Networks (WBANs) based on Bluetooth Low-Energy (BLE) standards to recognize and alarm a gesture of touching the face, and in effect, to prevent self-inoculation of respiratory viral diseases, such as COVID-19 or influenza A, B, or C. The proposed network comprises wireless modules placed in bracelets and a necklace. It relies on the received signal strength indicator (RSSI) measurements between the bracelet and necklace modules. The measured signal is cleared of noise using the exponential moving average (EMA). Next, we use a classification algorithm based on a Least-Squares Support Vector Machine (LSSVM) in order to detect facial touches. When the results of the classification indicate that the hand is moving toward the face, an alarm is sent through the neck module and the vibrator embedded in the wrist module is switched on. Based on the performed tests, it can be concluded that the proposed solution is characterized by high accuracy and reliability. It should be useful, especially for individuals who are regularly exposed to the risk of respiratory infections. Full article
(This article belongs to the Special Issue COVID-19 and Wearable Medical Sensors)
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