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IoT-Based Health Monitoring and Assistive Systems
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IoT-Based Health Monitoring and Assistive Systems

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

Deadline for manuscript submissions: closed (30 January 2024) | Viewed by 5893

Special Issue Editors

Dr. Kevin Lee

E-Mail Website
Guest Editor
School of Information Technology, Deakin University, Melbourne, VIC 3217, Australia
Interests: Internet of Things; cloud computing; robotics; embedded systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ka Lok Man

E-Mail
Guest Editor
Department of Computer Science and Software Engineering, Xi’an Jiaotong Liverpool University, Suzhou Dushu Lake Higher Education Town, Suzhou Industrial Park, Suzhou, Jiangsu Province, China
Interests: wireless sensor networks; Internet of Things; Artificial Intelligence and photovoltaic
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is expanding at a rapid rate, with devices being deployed in workplaces, homes and in the environment. This is being driven by new low-cost sensors, improved battery technologies, increased embedded processing capabilities and maturing edge computing technologies.

The COVID-19 pandemic has highlighted the need for technologies to support health monitoring. There is also increasing demand to reduce the costs of home and chronic care through the use of IoT technologies. People are also choosing to use self-monitoring devices such as heart-rate monitors, cadence sensors and blood pressure monitors for health and fitness.

This Special Issue is focused on the innovative use of IoT in the development of new health monitoring applications and assistive systems. Submissions are welcome in all areas related to this topic, including IoT health-sensors, real-time health monitoring, smart PPE, body sensors, body area networks, smart clothing, health data analysis, use of AI and ML for IoT sourced health data, IoT health applications and assistive systems.

Dr. Kevin Lee
Prof. Dr. Ka Lok Man
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

  • internet of things
  • smart PPE
  • health monitoring
  • assistive systems
  • smart clothing
  • body sensors
  • body area networks
  • real-time health monitoring

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Published Papers (2 papers)

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Research

28 pages, 5855 KiB  
Article
Automated Adjustment of PPE Masks Using IoT Sensor Fusion
by Ashish Manchanda, Kevin Lee, Gillud David Poznanski and Alireza Hassani
Sensors 2023, 23(3), 1711; https://doi.org/10.3390/s23031711 - 3 Feb 2023
Cited by 3 | Viewed by 2783
Abstract
The COVID-19 pandemic has led to a dramatic increase in the use of PPE by the general public as well as health professionals. Scientists and health organizations have developed measures to protect people and minimize the catastrophic outcomes of COVID, including social distancing, [...] Read more.
The COVID-19 pandemic has led to a dramatic increase in the use of PPE by the general public as well as health professionals. Scientists and health organizations have developed measures to protect people and minimize the catastrophic outcomes of COVID, including social distancing, frequent and periodic sanitizing, vaccinations, protective coverings, and face masks. During this time, the usage of protective face masks has increased dramatically. A mask only provides full safety to the user if it is a proper fit on their face. The aim of this paper is to automatically analyze and improve the fit of a face mask using IoT sensors. This paper describes the creation of a 3D-printed smart face mask that uses sensors to determine the current mask fit and then automatically tightens mask straps. This is evaluated using adjustment response time and the quality of fit achieved using the automatic adjustment approach with a range of sensor types. Full article
(This article belongs to the Special Issue IoT-Based Health Monitoring and Assistive Systems)
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17 pages, 2488 KiB  
Article
Integration of IoT Sensors to Determine Life Expectancy of Face Masks
by Vilanya Ratnayake Mudiyanselage, Kevin Lee and Alireza Hassani
Sensors 2022, 22(23), 9463; https://doi.org/10.3390/s22239463 - 3 Dec 2022
Cited by 4 | Viewed by 2226
Abstract
Personal protective equipment (PPE) is widely used around the world to protect against environmental hazards. With the emergence of the COVID-19 virus, the use of PPE domestically has increased dramatically. People use preventive and protective mechanisms now more than ever, leading to the [...] Read more.
Personal protective equipment (PPE) is widely used around the world to protect against environmental hazards. With the emergence of the COVID-19 virus, the use of PPE domestically has increased dramatically. People use preventive and protective mechanisms now more than ever, leading to the important question of how protective is the PPE that is being used. Face masks are highly recommended or mandatory during the time of the COVID-19 pandemic due to their protective features against aerosol droplets. However, an issue faced by many users of face masks is that they are entirely manual, with users having to decide for themselves whether their mask is still protective or if they should replace their mask. Due to the difficulty in determining this, people tend to overuse masks beyond their optimal usage. The research presented in this paper is an investigation of the viability of integrating IoT sensors into masks that are capable of collecting data to determine its usage. This paper demonstrates the usage of humidity and temperature sensors for the purpose of determining a mask’s usage status based on changes in these variables when a mask is put on and taken off. An evaluation was made on the usage of the two sensors, with the conclusion that a humidity sensor provides more accurate results. From this, we present a framework that takes into consideration the factors that affect a mask’s performance, such as time, humidity and temperature, to calculate the life expectancy of a mask. Full article
(This article belongs to the Special Issue IoT-Based Health Monitoring and Assistive Systems)
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