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Applied Sciences
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Applications of Wearable Sensors and Image Processing in Assistive and...
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Applications of Wearable Sensors and Image Processing in Assistive and Rehabilitative Technologies

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".

Deadline for manuscript submissions: 30 August 2024 | Viewed by 4438

Special Issue Editors

Prof. Dr. Hariton-Nicolae Costin

E-Mail Website
Guest Editor
Institute of Computer Science of the Romanian Academy, Iasi Branch, 700481 Iasi, Romania
Interests: biosignal processing; biomedical image processing; artificial intelligence (neural networks, fuzzy systems, bio-inspired algorithms); (bio)sensors/transducers; e-health and telemedicine; assistive technologies
Special Issues, Collections and Topics in MDPI journals
Dr. Cristian Rotariu

E-Mail Website
Guest Editor
Faculty of Medical Bioengineering, Grigore T. Popa University of Medicine and Pharmacy of Iași, 9-13 Kogalniceanu str., 700454 Iași, Romania
Interests: biomedical signal and medical image processing; telemedicine; assistive technologies; wearable medical sensors and devices
Special Issues, Collections and Topics in MDPI journals
Dr. Gladiola Petroiu

E-Mail Website
Guest Editor
Faculty of Medical Bioengineering, Grigore T. Popa University of Medicine and Pharmacy of Iași, 9-13 Kogalniceanu str., 700454 Iași, Romania
Interests: biomedical signal processing; e-health; assistive technologies; wearable medical sensors and devices; robot process automation

Special Issue Information

Dear Colleagues,

This Special Issue (SI) focuses on the use of wearable sensors and image processing technologies in assistive and rehabilitative applications. The SI covers a wide range of topics related to wearable sensors and image processing, including but not limited to the development and implementation of wearable devices, signal and image processing techniques, machine learning algorithms, and clinical applications.

Wearable sensors are sensing devices integrated into wearable objects or directly with the human body in order to provide clinically relevant data for care. Nowadays, many people use wearable devices such as smartwatches, fitness trackers, step-counters, or various medical-purpose wearables.

Assistive technologies based on wearable sensors refer to any medical device or service used to improve the capabilities of people with disabilities. In order to enhance the reliability and accuracy of the medical information, certain medical devices combine the use of wearable devices with image processing tools.

The use of rehabilitative technologies represents an essential component of healthcare systems, enabling people suffering from chronic diseases or the elderly to achieve their goals and simultaneously maintain their quality of life.

The goal of this Special Issue is to provide a platform for researchers, engineers, and clinicians to share their research and insights, and to promote the advancement of wearable sensors and image processing technologies in assistive and rehabilitative applications. This Special Issue accepts submissions of high-quality research papers and review articles on the topic of wearable sensors and image processing applications for assistive technologies used for rehabilitation. Submissions must be original contributions that have not been published before and are not currently under review by other journals.

Potential topics of interest include, but are not limited to:

  • Wearable sensors and systems;
  • Embedded sensor systems in wearable assistive devices;
  • Intelligent sensors and systems for healthcare and assistive technology;
  • Medical image processing in assistive and rehabilitative technologies;
  • Machine learning algorithms applied in rehabilitation and assistive technology;
  • Rehabilitative and assistive technologies;
  • Data security in wearable sensing devices;
  • M-health and p-health systems;
  • Cloud computing with medical imaging, image processing, and analysis;
  • IoT-based systems and cloud computing in IoT-based systems;
  • Big data handling in IoT-based systems;
  • Virtual and augmented reality for medical rehabilitation and assistive technologies;
  • Wearable sensors for accessible and adaptive technologies: visual, motor/mobility, auditory, seizures, and learning/cognitive.

Prof. Dr. Hariton-Nicolae Costin
Dr. Cristian Rotariu
Dr. Gladiola Petroiu
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. Applied Sciences 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 2400 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.

Published Papers (3 papers)

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Research

19 pages, 15010 KiB  
Article
A Study on the Fabrication of Pressure Measurement Sensors and Intention Verification in a Personalized Socket of Intelligent Above-Knee Prostheses: A Guideline for Fabricating Flexible Sensors Using Velostat Film
by Na-Yeon Park, Su-Hong Eom and Eung-Hyuk Lee
Appl. Sci. 2024, 14(2), 734; https://doi.org/10.3390/app14020734 - 15 Jan 2024
Viewed by 616
Abstract
Intelligent transfemoral prostheses, which have recently been studied, are equipped with a microcontroller, providing appropriate motion functions for their walking environments. Thus, studies have been conducted to estimate user intentions in locomotion movements by applying biomechanical sensors inside the socket. Among them, a [...] Read more.
Intelligent transfemoral prostheses, which have recently been studied, are equipped with a microcontroller, providing appropriate motion functions for their walking environments. Thus, studies have been conducted to estimate user intentions in locomotion movements by applying biomechanical sensors inside the socket. Among them, a pressure sensor is used to determine the intentions of locomotion movements through changes in the internal pressure of the prosthetic socket. However, existing studies have a problem in that the reproducibility of pressure change data is degraded due to the non-detection and saturation of the pressure measurement value. Accordingly, this study proposes a fabrication method for a wide and flexible pressure sensor that can solve this problem and a method for the identification of user intentions in locomotion movements using it. The proposed system was fabricated with Velostat film, which has a smaller noise impact and can be fabricated in various sizes and shapes. The fabricated sensor was attached to four points inside the socket, confirming the possibility of detecting the intention of six movements according to the multi-critical detection method. The proposed pressure-sensor-based intention detection system can be applied individually by prosthetic users through simple tasks. Moreover, it will be universally applicable for commercialization. Full article
(This article belongs to the Special Issue Applications of Wearable Sensors and Image Processing in Assistive and Rehabilitative Technologies)
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16 pages, 6771 KiB  
Article
The Effects of Structural Characteristics of the Rollator on the Elderly’s Gait Strategies in Various Walking Environments
by Ji-Yong Jung and Jung-Ja Kim
Appl. Sci. 2023, 13(19), 11044; https://doi.org/10.3390/app131911044 - 07 Oct 2023
Cited by 1 | Viewed by 838
Abstract
A rollator, one of the most widely used among walking assistance devices, can assist the elderly with stable walking in their daily lives. In this study, we investigated how the structural characteristics of two types of rollators affect the upper and lower extremity [...] Read more.
A rollator, one of the most widely used among walking assistance devices, can assist the elderly with stable walking in their daily lives. In this study, we investigated how the structural characteristics of two types of rollators affect the upper and lower extremity muscle activity and plantar pressure of the elderly in various walking environments. We quantified muscle activity (upper and lower limbs) and plantar pressure (mean force, peak pressure, and contact area) of 11 older adults walking in various environments (flat, obstacle, uneven, and sloped terrain) using two types of rollators. Upper extremity muscle activity was highest in the obstacle terrain and the uneven terrain, and a significant difference was found due to the structural differences of the rollator. Additionally, it was observed that lower extremity muscle activity and plantar pressure patterns appeared in accordance with the gait strategy to maintain stability in an unstable or inclined walking environment. In other words, it was confirmed that the weight of the rollator, the size of the wheel, grip type, and the auxiliary tools had a great effect on the upper and lower extremity muscle activity and plantar pressure of the elderly during walking. From the results of this study, it can be suggested that it is absolutely necessary to consider the biomechanical characteristics of the elderly and the structure of the rollator, which appear differently depending on the walking environment, in the development of walking aids. In the future, more clinical data will be collected, and based on this a rollator that can safely assist the elderly in various walking environments will be developed. Full article
(This article belongs to the Special Issue Applications of Wearable Sensors and Image Processing in Assistive and Rehabilitative Technologies)
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13 pages, 1853 KiB  
Article
Prototype Results of an Internet of Things System Using Wearables and Artificial Intelligence for the Detection of Frailty in Elderly People
by Bogdan-Iulian Ciubotaru, Gabriel-Vasilică Sasu, Nicolae Goga, Andrei Vasilățeanu, Iuliana Marin, Maria Goga, Ramona Popovici and Gora Datta
Appl. Sci. 2023, 13(15), 8702; https://doi.org/10.3390/app13158702 - 27 Jul 2023
Cited by 2 | Viewed by 1069
Abstract
As society moves towards a preventative approach to healthcare, there is growing interest in scientific research involving technology that can monitor and prevent adverse health outcomes. The primary objective of this paper is to develop an Internet of Things (IoT) wearable system based [...] Read more.
As society moves towards a preventative approach to healthcare, there is growing interest in scientific research involving technology that can monitor and prevent adverse health outcomes. The primary objective of this paper is to develop an Internet of Things (IoT) wearable system based on Fried’s phenotype that is capable of detecting frailty. To determine user requirements, the system’s architecture was designed based on the findings of a questionnaire administered to individuals confirmed to be frail. A functional prototype was successfully developed and tested under real-world conditions. This paper introduces the methodology that was used to analyze the data collected from the prototype. It proposes an interdisciplinary approach to interpret wearable sensor data, providing a comprehensive overview through both visual representations and computational analyses facilitated by machine learning models. The findings of these analyses offer insights into the ways in which different types of activities can be classified and quantified as part of an overall physical activity level, which is recognized as an important indicator of frailty. The results provide the foundations for a new generation of affordable and non-intrusive systems able to detect and assess early signs of frailty. Full article
(This article belongs to the Special Issue Applications of Wearable Sensors and Image Processing in Assistive and Rehabilitative Technologies)
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