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Wearable Sensors for Remote Health Monitoring of Older Adults

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

Deadline for manuscript submissions: closed (28 February 2024) | Viewed by 1519

Special Issue Editor


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Guest Editor
Robarts Research Institute and Schulich School of Medicine & Dentistry, University of Western Ontario, London, ON, Canada
Interests: biophotonics; bio-optics; wearable technology; wearable AI; brain mapping; bionic eye; mental health
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The aging population worldwide presents unique healthcare challenges, and wearable sensors technology provide a proactive approach to address them. Wearable sensors collect valuable data on vital signs, physical activity, sleep patterns, and more, which enables continuous and non-invasive monitoring of various health parameters and helps to detect early signs of health deterioration, prevent falls, monitor chronic conditions, and provide personalized care based on individual needs. By facilitating remote health monitoring, wearable sensors contribute to reducing hospital visits, promoting preventive care, and enabling timely interventions, thus empowering older adults to lead healthier and more independent lives and offering tremendous potential in improving the quality of life and care for the aging population.

This Special Issue seeks to showcase cutting-edge research on smart Wearable Sensors for Remote Health Monitoring of Older Adults. Topics of interest include but are not limited to:

  • Sensor technology advancements for accurate and unobtrusive health monitoring of aging population.
  • Integration of wearable sensors with telehealth and telemedicine platforms and applications in remote health monitoring of older adults.
  • Mobile health interventions targeting elderly well-being and chronic disease management.
  • Long-term care solutions empowered by wearable sensor technology.
  • Zero-effort technology and passive sensing for continuous health monitoring.
  • Wearable sensor technologies for remote health monitoring of older adults.
  • Novel applications of wearable sensors in elderly care and well-being.
  • Wearable AI algorithms and analytics for remote health monitoring.
  • Data analytics and machine learning techniques for interpreting sensor data.
  • User experience and acceptance of wearable sensor devices among older adults.
  • Privacy and security considerations in remote health monitoring systems.
  • Ethical considerations and privacy concerns in wearable-sensor-based remote monitoring.
  • Clinical validation and effectiveness of wearable-sensor-based monitoring systems.
  • Challenges and future directions in wearable sensor technology for older adults.

Dr. Ehsan Kamrani
Guest Editor

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.

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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 technology
  • wearable AI
  • sensor technology
  • telemedicine
  • remote health monitoring
  • mobile health
  • elderlies’ well-being
  • older adults
  • aging, long-term care
  • zero-effort technology

Published Papers (1 paper)

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Research

12 pages, 1625 KiB  
Article
Validation of the Short Physical Performance Battery via Plantar Pressure Analysis Using Commercial Smart Insoles
by Chan Woong Jang, Kyoungmin Park, Min-Chul Paek, Sanghyun Jee and Jung Hyun Park
Sensors 2023, 23(24), 9757; https://doi.org/10.3390/s23249757 - 11 Dec 2023
Viewed by 1162
Abstract
This cross-sectional study, conducted at a tertiary care hospital’s rehabilitation clinic, aimed to validate Short Physical Performance Battery (SPPB) results obtained through plantar pressure analysis using commercial smart insoles (SPPB-SI) and to compare these results to manually acquired results by an experienced examiner [...] Read more.
This cross-sectional study, conducted at a tertiary care hospital’s rehabilitation clinic, aimed to validate Short Physical Performance Battery (SPPB) results obtained through plantar pressure analysis using commercial smart insoles (SPPB-SI) and to compare these results to manually acquired results by an experienced examiner (SPPB-M). This study included 40 independent-walking inpatients and outpatients aged 50 or older. SPPB-SI and SPPB-M were administered concurrently, with the smart insoles providing plantar pressure data that were converted into time–pressure curves. Two interpreters assessed the curves, determining component completion times for the SPPB-SI scores. Among the 40 participants (mean age: 72.98, SD: 9.27), the mean total SPPB-SI score was 7.72 ± 2.50, and the mean total SPPB-M score was 7.95 ± 2.63. The time recordings and measured scores of each SPPB-SI component exhibited high reliability with inter- and intra-interpreter correlation coefficients of 0.9 and 0.8 or higher, respectively. The intraclass correlation coefficient between the total SPPB-SI and SPPB-M scores was 0.831 (p < 0.001), and that between the component scores of the two measurements ranged from 0.837 to 0.901 (p < 0.001). Consistent correlations with geriatric functional parameters were observed for both SPPB-SI and SPPB-M. This study underscores the potential of commercial smart insoles as reliable tools for conducting SPPB assessments. Full article
(This article belongs to the Special Issue Wearable Sensors for Remote Health Monitoring of Older Adults)
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