Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.3
3.4
Journals
Sensors
Special Issues
Interactive, Mobile, Wearable Sensors and Technology for Elderly Care
sensors-logo
Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Interactive, Mobile, Wearable Sensors and Technology for Elderly Care

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

Deadline for manuscript submissions: closed (15 April 2023) | Viewed by 12753

Special Issue Editors

Dr. Ming Liu

E-Mail Website
Guest Editor
Institute of Semiconductors, Chinese Academy of Sciences, Bei**g 100083, China
Interests: medical electronics; artificial intelligence medical applications; low-power digital-analog hybrid SoC design; multi-core processor design; digital low-power design methods; digital signal processing
Dr. Xu Zhang

E-Mail Website
Guest Editor
Institute of Semiconductors, Chinese Academy of Sciences, Bei**g 100083, China
Interests: application-specific integrated circuits and microsystems for implantable neuromodulation; high reliability integration technology of key automotive electronic components; flexible tactile sensor and interface technology for fine operation

Special Issue Information

Dear Colleagues,

The elderly population has been increasing with the improvement of medical technologies, which raises the question of how to realize elderly care efficiently, conveniently, and economically. Elderly care encompasses, but is not limited to, assisted living, long-term care, residential care, hospice care, and home care. The realization of a wide variety of elderly care needs and the broad range of practices are inseparable from sensors. Interactive, mobile, wearable sensors and related technology for elderly care can be one of the answers to efficient, convenient, and economical elderly care.

This Special Issue is addressed to all types of interactive, mobile, and wearable sensors designed for elderly care.

Dr. Ming Liu
Dr. Xu Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at mdpi.longhoe.net 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

  • human–computer interaction
  • wearable devices
  • smart sensors
  • artificial intelligence
  • flexible process
  • mobile applications
  • internet of things
  • sensor network
  • health monitoring
  • medical assistance

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

11 pages, 3557 KiB  
Article
A Hydrogel-Based Electronic Skin for Touch Detection Using Electrical Impedance Tomography
by Huiyang Zhang, Anubha Kalra, Andrew Lowe, Yang Yu and Gautam Anand
Sensors 2023, 23(3), 1571; https://doi.org/10.3390/s23031571 - 1 Feb 2023
Cited by 8 | Viewed by 2496
Abstract
Recent advancement in wearable and robot-assisted healthcare technology gives rise to the demand for smart interfaces that allow more efficient human-machine interaction. In this paper, a hydrogel-based soft sensor for subtle touch detection is proposed. Adopting the working principle of a biomedical imaging [...] Read more.
Recent advancement in wearable and robot-assisted healthcare technology gives rise to the demand for smart interfaces that allow more efficient human-machine interaction. In this paper, a hydrogel-based soft sensor for subtle touch detection is proposed. Adopting the working principle of a biomedical imaging technology known as electrical impedance tomography (EIT), the sensor produces images that display the electrical conductivity distribution of its sensitive region to enable touch detection. The sensor was made from a natural gelatin hydrogel whose electrical conductivity is considerably less than that of human skin. The low conductivity of the sensor enabled a touch-detection mechanism based on a novel short-circuiting approach, which resulted in the reconstructed images being predominantly affected by the electrical contact between the sensor and fingertips, rather than the conventionally used piezoresistive response of the sensing material. The experimental results indicated that the proposed sensor was promising for detecting subtle contacts without the necessity of exerting a noticeable force on the sensor. Full article
(This article belongs to the Special Issue Interactive, Mobile, Wearable Sensors and Technology for Elderly Care)
►▼ Show Figures

Figure 1

12 pages, 966 KiB  
Article
Tele-Assessment of Functional Capacity through the Six-Minute Walk Test in Patients with Diabetes Mellitus Type 2: Validity and Reliability of Repeated Measurements
by Garyfallia Pepera, Evmorfia Karanasiou, Christina Blioumpa, Varsamo Antoniou, Konstantinos Kalatzis, Leonidas Lanaras and Ladislav Batalik
Sensors 2023, 23(3), 1354; https://doi.org/10.3390/s23031354 - 25 Jan 2023
Cited by 9 | Viewed by 2626
Abstract
A tele-assessed 6MWT (TL 6MWT) could be an alternative method of evaluating functional capacity in patients with diabetes mellitus type 2 (DM2). This study aimed to assess the validity and reliability of a TL 6MWT. The functional capacity of 28 patients with DM2 [...] Read more.
A tele-assessed 6MWT (TL 6MWT) could be an alternative method of evaluating functional capacity in patients with diabetes mellitus type 2 (DM2). This study aimed to assess the validity and reliability of a TL 6MWT. The functional capacity of 28 patients with DM2 (75% men) aged 61 ± 13 years was evaluated twice via an indoor, center-based 6MWT (CB 6MWT) and twice outside each patient’s home via a web-based platform TL 6MWT. The study showed a high statistically significant correlation between the CB and TL 6MWT (Pearson’s r = 0.76, p < 0.001). Reliability testing showed no statistically significant differences in the distance covered (CB1: 492 ± 84 m and CB2: 506 ± 86 m versus TL1: 534 ± 87 m and TL2: 542 ± 93 m, respectively) and in the best distance of the TL 6MWT (545 ± 93 m) compared to the best CB distance (521 ± 83 m). Strong internal reliability for both the CB (intraclass correlation coefficient (ICC) = 0.93) and the TL 6MWT (ICC = 0.98) was found. The results indicate that a TL 6MWT performed outdoors can be a highly valid and reliable tool to assess functional capacity in patients with DM2. No learning effect between the TL and CB assessment was found, minimizing the need for repetition. Full article
(This article belongs to the Special Issue Interactive, Mobile, Wearable Sensors and Technology for Elderly Care)
►▼ Show Figures

Figure 1

10 pages, 574 KiB  
Communication
Virtual Reality—A Supplement to Posturography or a Novel Balance Assessment Tool?
by Oskar Rosiak, Anna Puzio, Dorota Kaminska, Grzegorz Zwolinski and Magdalena Jozefowicz-Korczynska
Sensors 2022, 22(20), 7904; https://doi.org/10.3390/s22207904 - 17 Oct 2022
Cited by 4 | Viewed by 2550
Abstract
Virtual reality (VR) is a well-established technology in medicine. Head-mounted displays (HMDs) have made VR more accessible in many branches of medical research. However, its application in balance evaluation has been vague, and comprehensive literature on possible applications of VR in posture measurement [...] Read more.
Virtual reality (VR) is a well-established technology in medicine. Head-mounted displays (HMDs) have made VR more accessible in many branches of medical research. However, its application in balance evaluation has been vague, and comprehensive literature on possible applications of VR in posture measurement is scarce. The aim of this review is to conduct a literature search on the application of immersive VR delivered using a head-mounted display in posturographic measurements. A systematic search of two databases, PubMed and Scopus, using the keywords “virtual reality” and “posturography,” was performed following PRISMA guidelines for systematic reviews. Initial search results returned 89 non-duplicate records. Two reviewers independently screened the abstracts. Sixteen papers fulfilled the inclusion criteria and none of the exclusion criteria and were selected for complete text retrieval. An additional 16 records were identified from citation searching. Ultimately, 21 studies were included in this review. virtual reality is often used as additional visual stimuli in static and dynamic posturography evaluation. Only one study has attempted to evaluate a VR environment in a head-mounted display as an independent method in the assessment of posture. Further research should be conducted to assess HMD VR as a standalone posturography replacement. Full article
(This article belongs to the Special Issue Interactive, Mobile, Wearable Sensors and Technology for Elderly Care)
►▼ Show Figures

Figure 1

Review

Jump to: Research

18 pages, 2140 KiB  
Review
A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults
by Manting Chen, Hailiang Wang, Lisha Yu, Eric Hiu Kwong Yeung, Jiajia Luo, Kwok-Leung Tsui and Yang Zhao
Sensors 2022, 22(18), 6752; https://doi.org/10.3390/s22186752 - 7 Sep 2022
Cited by 18 | Viewed by 4480
Abstract
Falls have been recognized as the major cause of accidental death and injury in people aged 65 and above. The timely prediction of fall risks can help identify older adults prone to falls and implement preventive interventions. Recent advancements in wearable sensor-based technologies [...] Read more.
Falls have been recognized as the major cause of accidental death and injury in people aged 65 and above. The timely prediction of fall risks can help identify older adults prone to falls and implement preventive interventions. Recent advancements in wearable sensor-based technologies and big data analysis have spurred the development of accurate, affordable, and easy-to-use approaches to fall risk assessment. The objective of this study was to systematically assess the current state of wearable sensor-based technologies for fall risk assessment among community-dwelling older adults. Twenty-five of 614 identified research articles were included in this review. A comprehensive comparison was conducted to evaluate these approaches from several perspectives. In general, these approaches provide an accurate and effective surrogate for fall risk assessment. The accuracy of fall risk prediction can be influenced by various factors such as sensor location, sensor type, features utilized, and data processing and modeling techniques. Features constructed from the raw signals are essential for predictive model development. However, more investigations are needed to identify distinct, clinically interpretable features and develop a general framework for fall risk assessment based on the integration of sensor technologies and data modeling. Full article
(This article belongs to the Special Issue Interactive, Mobile, Wearable Sensors and Technology for Elderly Care)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop