Submit to Special Issue Submit Abstract to Special Issue Review for Applied Sciences Propose a Special Issue

Journal Menu

Journal Browser

Applications of Wearable Sensors and Image Processing in Assistive and Rehabilitative Technologies

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Benefits of Publishing in a Special Issue
Published Papers

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

Deadline for manuscript submissions: 30 October 2025 | Viewed by 10335

Share This Special Issue

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 Issues, Collections and Topics in MDPI journals

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.

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (6 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

25 pages, 4084 KiB

Open AccessArticle

Effectiveness of Virtual Reality-Based Multi-Therapy Systems for Physio-Psychological Rehabilitation: A Clinical Study

by Iulia-Cristina Stanica, Simona Magdalena Hainagiu, Alberta Milicu, Maria-Iuliana Dascalu and Giovanni-Paul Portelli

Appl. Sci. 2024, 14(19), 9093; https://doi.org/10.3390/app14199093 - 8 Oct 2024

Viewed by 1228

Abstract

The worldwide increase in the number of disorders requiring rehabilitation is weighing more and more on healthcare systems, seriously affecting the quality of life of patients. Emergent technologies and techniques should be used more and more in both physical and psychological rehabilitation, after a thorough study of their potential and effects. Our paper presents an original virtual reality-based system including gamified immersive physio-psychological exercises, which was tested in a clinical setting with 25 patients suffering from various musculoskeletal, neuromotor, or mental disorders. A thorough testing protocol was followed during a two-week period, including repeated trials, progress tracking, and objective and subjective instruments used for data collection. A statistical analysis helped us identify interesting correlations between complex virtual reality games and people’s performance, and the high level of relaxation and stress relief (4.57 out of 5 across all games) which can be offered by VR-based psychotherapy exercises, as well as the increased ease of use (4.26 out of 5 perceived across all games) of properly designed training exercises regardless of patients’ level of VR experience (84% of patients with no or low experience and no patient with high experience). Full article

(This article belongs to the Special Issue Applications of Wearable Sensors and Image Processing in Assistive and Rehabilitative Technologies)

► Show Figures

Figure 1

11 pages, 898 KiB

Open AccessArticle

Intra-Reliability of a Wearable Near-Infrared Sensor for Monitoring the Intensity of Exercise

by Kamil Michalik, Marcin Smolarek, Michał Nowak, Basilio Pueo and Piotr Żmijewski

Appl. Sci. 2024, 14(13), 5856; https://doi.org/10.3390/app14135856 - 4 Jul 2024

Viewed by 1008

Abstract

The Q-LAC analyzer, a portable device employing near-infrared spectroscopy (NIRS), was designed to measure muscle oxygen saturation (SmO₂) during physical exercise. This study aimed to assess the reliability of the Q-LAC analyzer in determining SmO₂ levels during incremental cycling exercise. Thirteen physically active males (age 28.1 ± 5.3 y; height 181.2 ± 5.7 cm; body mass 79.9 ± 11.1 kg; BMI 24.2 ± 2.4 kg/m²) participated in this study. A submaximal incremental exercise test (SIET) on an electromagnetic cycle ergometer with a seven-day interval was performed twice. SmO₂ levels in the vastus lateralis (VL) muscle of the dominant leg were simultaneously recorded using the Q-LAC device during both tests. The study calculated the intraclass correlation coefficient (ICC), the coefficient of variation (CV), the standard error of measurement (SEM), the smallest worthwhile change (SWC), and mean detectable change (MDC). A within-within-subjects ANOVA revealed no statistically significant effects for session (F_1,12 = 0.97, p = 0.34, η² = 0.07) and the interaction between session and workload (F_4,48 = 0.19, p = 0.94, η² = 0.02). ICC values ranged from 0.72 to 0.91. Furthermore, the analysis of CV, SEM, and SWC indicated that SmO₂ measurements obtained with the Q-LAC device exhibit good reliability but marginal sensitivity. In conclusion, the portable Q-LAC analyzer provides consistent measurements of muscle oxygen saturation during low-to-moderate-intensity exercise on a cycle ergometer. Full article

(This article belongs to the Special Issue Applications of Wearable Sensors and Image Processing in Assistive and Rehabilitative Technologies)

► Show Figures

Figure 1

22 pages, 5665 KiB

Open AccessArticle

Empowering Active and Healthy Ageing: Integrating IoT and Wearable Technologies for Personalised Interventions

by Jensen Selwyn Joymangul, Ileana Ciobanu, Francesco Agnoloni, Jure Lampe, Chiara Pedrini, Angela Pinto, Bruna Franceschini, Damien Nicolas, Elena Tamburini, Francesca Cecchi, Mihai Berteanu and Djamel Khadraoui

Appl. Sci. 2024, 14(11), 4789; https://doi.org/10.3390/app14114789 - 31 May 2024

Viewed by 1111

Abstract

Social isolation and loneliness greatly contribute to negative health consequences in older adults. Technological solutions can be an asset in promoting social connections and healthy behaviours. This paper presents an innovative structure for an Internet of Things (IoT) platform specifically tailored for older persons. The framework utilises a supervised learning algorithm to classify users into four identified profiles to facilitate the adoption and engagement of technology. The platform incorporates wearables, such as socks and smart bands, to track physical activity, and a messaging module to encourage social interaction. The platform processes the acquired data to quantify steps and deliver tailored interventions remotely to the older adults through the AGAPE Assistant, the mHealth solution of the platform. Furthermore, the AGAPE Assistant has a user interface design for older adults, with a focus on their specific needs. Additionally, improving digital literacy among older adults is crucial for maximizing the long-term compliance and benefits of such technological solutions. On the other hand, AGAPE Monitor is a web application used by formal caregivers to configure the tailored interventions. The platform’s usability was assessed using different usability scale questionnaires, which revealed a mild level of user satisfaction and acceptance. The proposed framework is currently being deployed on more than 112 older adults across three countries: Italy, Romania, and Portugal. The proposed framework provides a holistic solution to encourage active ageing by adopting technology, implementing hybrid interventions, and promoting social interactions. Full article

(This article belongs to the Special Issue Applications of Wearable Sensors and Image Processing in Assistive and Rehabilitative Technologies)

► Show Figures

Figure 1

19 pages, 15010 KiB

Open AccessArticle

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 1066

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 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)

► Show Figures

Figure 1

16 pages, 6771 KiB

Open AccessArticle

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 - 7 Oct 2023

Cited by 1 | Viewed by 1433

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 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)

► Show Figures

Figure 1

13 pages, 1853 KiB

Open AccessArticle

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 5 | Viewed by 1638

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 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)

► Show Figures

Journal Menu

Journal Browser

Applications of Wearable Sensors and Image Processing in Assistive and Rehabilitative Technologies

Share This Special Issue

Special Issue Editors

Special Issue Information

Benefits of Publishing in a Special Issue

Published Papers (6 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI