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Sensors-Enabled Assistive Technologies for Health Monitoring and Elderly Care

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

Deadline for manuscript submissions: 1 July 2024 | Viewed by 606

Special Issue Editors


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Guest Editor
School of Computing, Engineering and the Built Environment, Edinburgh Napier University, Edinburgh EH10 5QT, UK
Interests: robotics and intelligent control; applied artificial intelligence; data analysis; data sciences with applications in digital healthcare and manufacturing systems; applications of emerging technology, such as RFID, wireless technology, etc. into healthcare and manufacturing systems
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Design, Northumbria University, Newcastle Upon Tyne NE1 8ST, UK
Interests: digital design technology; smart product and service design; design optimization; digital manufacturing, smart cities; design for emotion; crowdsouring product and service design and development
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Faculty of Technology, University of Sunderland, Sunderland, UK
Interests: smart systems and digital healthcare; artificial intelligence; machine learning; wireless sensor network
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Population aging has profound implications for healthcare systems worldwide.  According to projections, the global population aged 65 years or older will grow from 10% in 2022 to 16% by 2050.  This demographic shift presents numerous challenges, particularly for underserved groups such as low-income individuals, those in inadequate housing, those with disabilities or chronic health conditions, primary caregivers, and ethnic minorities or immigrants.  These populations often encounter poor health outcomes and have limited access to healthcare services.

This Special Issue, titled ‘Sensors-Enabled Assistive Technologies for Health Monitoring and Elderly Care’, aims to highlight innovative sensing technologies designed to meet the unique healthcare needs of older adults.  Sensor-based assistive technologies offer potential solutions for maintaining health, independence, and quality of life among elderly populations, while also reducing the burden on formal healthcare systems and caregivers.

We welcome submissions that focus on the development and application of sensors-enabled digital health platforms, assistive robots equipped with various sensing technologies, wearables and other assistive products for monitoring health metrics, as well as software solutions that utilize sensors data for proactive, personalized, predictive, preventive, and precision healthcare.  Original research papers and review articles that explore the recent advancements in these areas are particularly encouraged.

Prof. Dr. Hongnian Yu
Prof. Dr. Shengfeng Qin
Prof. Dr. Yongqiang Cheng
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

  • assistive technology
  • assistive robots
  • body area sensor networks
  • digital healthcare
  • personalized healthcare
  • tele-health technology
  • wearable sensors
  • smart environment

Published Papers (1 paper)

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Review

20 pages, 1631 KiB  
Review
Advancements in Cerebrospinal Fluid Biosensors: Bridging the Gap from Early Diagnosis to the Detection of Rare Diseases
by Ghazal Hatami-Fard and Salzitsa Anastasova-Ivanova
Sensors 2024, 24(11), 3294; https://doi.org/10.3390/s24113294 - 22 May 2024
Viewed by 297
Abstract
Cerebrospinal fluid (CSF) is a body fluid that can be used for the diagnosis of various diseases. However, CSF collection requires an invasive and painful procedure called a lumbar puncture (LP). This procedure is applied to any patient with a known risk of [...] Read more.
Cerebrospinal fluid (CSF) is a body fluid that can be used for the diagnosis of various diseases. However, CSF collection requires an invasive and painful procedure called a lumbar puncture (LP). This procedure is applied to any patient with a known risk of central nervous system (CNS) damage or neurodegenerative disease, regardless of their age range. Hence, this can be a very painful procedure, especially in infants and elderly patients. On the other hand, the detection of disease biomarkers in CSF makes diagnoses as accurate as possible. This review aims to explore novel electrochemical biosensing platforms that have impacted biomedical science. Biosensors have emerged as techniques to accelerate the detection of known biomarkers in body fluids such as CSF. Biosensors can be designed and modified in various ways and shapes according to their ultimate applications to detect and quantify biomarkers of interest. This process can also significantly influence the detection and diagnosis of CSF. Hence, it is important to understand the role of this technology in the rapidly progressing field of biomedical science. Full article
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