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Assistive Devices and Sensors
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Assistive Devices and Sensors

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

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 26356

Special Issue Editors

Prof. Dr. Pedro Silva Girão

E-Mail Website
Guest Editor
Instituto de Telecomunicações DEEC/IST, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal
Interests: sensors; transducers; instrumentation; measuring techniques; digital data processing; automated measurement systems; wireless sensor networks; metrology; quality; electromagnetic compatibility
Special Issues, Collections and Topics in MDPI journals
Dr. Octavian Postolache

E-Mail Website
Guest Editor
Instituto de Telecomunicações, Universidade de Aveiro Campus Universitário de, R. Santiago, 3810-193 Aveiro, Portugal
Interests: smart sensors; IoT; digital twin; precision agriculture; digital physical therapy
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Edward Sazonov

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, University of Alabama, Tuscaloosa, AL 35487, USA
Interests: biomedical signal processing; pattern recognition; wearable sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Various assistive devices have already improved life expectancy and quality of life for people with different disabilities. New materials, nanotechnology, new communications technologies have increased the availability and effectiveness of sensors that may improve or maintain the functional capabilities of individuals with disabilities or with specific learning difficulties. Assistive devices enhance learning, working and daily living for persons with disabilities. Smart assistive devices, which include new sensors or advances capabilities of sensors, beside provision of assistance for performing different activities, begin to have increased functionalities such as recognition of users’ motion intent and real-time meaningful assistance in complex daily-living scenarios.

The special issue will cover such advances in sensing technology utilized for smart assistive, orthotic and prosthetic devices. Contributions that address but are not restricted to the following topics related to sensors for assisted living are welcome:

  • Assistive listening device for people with mild or moderate hearing lost
  • Assistive technology to improve dementia care quality
  • Augmentative and alternative communication
  • Augmented reality for wheelchair users
  • Dynamic touch screens
  • Energy expenditure or fatigue detection
  • Eye tracking
  • Gait monitoring, gait recognition, gait diagnosis
  • Internet of Things for assisted living
  • Monitor of progression of speech dysfunction
  • Orientation and mobility aids for individuals with impaired vision
  • Real time speech-to-sign translation
  • Sensors for behaviour imaging software
  • Sensors for prosthesis and orthoses
  • Smart clothing /e-textile technologies
  • Smart crutches
  • Smart walker
  • Technology for assisted therapy for intellectually impaired adults

Submitted papers should present novel contributions and innovative applications. Relevant topical reviews are also welcome.

Prof. Pedro Silva Girão
Dr. Octavian Postolache
Prof. Edward Sazonov
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
  • Smart sensors
  • Internet of Things
  • Augmented reality
  • Wearable devices
  • Smart objects
  • Ambient assisted living
  • Tailored environments

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Published Papers (3 papers)

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Research

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26 pages, 45938 KiB  
Article
Prototype of Robotic Device for Mobility Assistance for the Elderly in Urban Environments
by Daniel Leite, Karla Figueiredo and Marley Vellasco
Sensors 2020, 20(11), 3056; https://doi.org/10.3390/s20113056 - 28 May 2020
Cited by 3 | Viewed by 3305
Abstract
This study aims to develop a prototype of an autonomous robotic device to assist the locomotion of the elderly in urban environments. Among the achievements presented are the control techniques used for autonomous navigation and the software tools and hardware applied in the [...] Read more.
This study aims to develop a prototype of an autonomous robotic device to assist the locomotion of the elderly in urban environments. Among the achievements presented are the control techniques used for autonomous navigation and the software tools and hardware applied in the prototype. This is an extension of a previous work, in which part of the navigation algorithm was developed and validated in a simulated environment. In this extension, the real prototype is controlled by an algorithm based on fuzzy logic to obtain standalone and more-natural navigation for the user of the device. The robotic device is intended to guide an elderly person in an urban environment autonomously, although it also has a manual navigation mode. Therefore, the device should be able to navigate smoothly without sudden manoeuvres and should respect the locomotion time of the user. Furthermore, because of the proposed environment, the device should be able to navigate in an unknown and unstructured environment. The results reveal that this prototype achieves the proposed objective, demonstrating adequate behaviour for navigation in an unknown environment and fundamental safety characteristics to assist the elderly. Full article
(This article belongs to the Special Issue Assistive Devices and Sensors)
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Review

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19 pages, 581 KiB  
Review
A Review of Gait Phase Detection Algorithms for Lower Limb Prostheses
by Huong Thi Thu Vu, Dianbiao Dong, Hoang-Long Cao, Tom Verstraten, Dirk Lefeber, Bram Vanderborght and Joost Geeroms
Sensors 2020, 20(14), 3972; https://doi.org/10.3390/s20143972 - 17 Jul 2020
Cited by 77 | Viewed by 9732
Abstract
Fast and accurate gait phase detection is essential to achieve effective powered lower-limb prostheses and exoskeletons. As the versatility but also the complexity of these robotic devices increases, the research on how to make gait detection algorithms more performant and their sensing devices [...] Read more.
Fast and accurate gait phase detection is essential to achieve effective powered lower-limb prostheses and exoskeletons. As the versatility but also the complexity of these robotic devices increases, the research on how to make gait detection algorithms more performant and their sensing devices smaller and more wearable gains interest. A functional gait detection algorithm will improve the precision, stability, and safety of prostheses, and other rehabilitation devices. In the past years the state-of-the-art has advanced significantly in terms of sensors, signal processing, and gait detection algorithms. In this review, we investigate studies and developments in the field of gait event detection methods, more precisely applied to prosthetic devices. We compared advantages and limitations between all the proposed methods and extracted the relevant questions and recommendations about gait detection methods for future developments. Full article
(This article belongs to the Special Issue Assistive Devices and Sensors)
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26 pages, 538 KiB  
Review
Physiological and Behavior Monitoring Systems for Smart Healthcare Environments: A Review
by Mariana Jacob Rodrigues, Octavian Postolache and Francisco Cercas
Sensors 2020, 20(8), 2186; https://doi.org/10.3390/s20082186 - 12 Apr 2020
Cited by 65 | Viewed by 11917
Abstract
Healthcare optimization has become increasingly important in the current era, where numerous challenges are posed by population ageing phenomena and the demand for higher quality of the healthcare services. The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one [...] Read more.
Healthcare optimization has become increasingly important in the current era, where numerous challenges are posed by population ageing phenomena and the demand for higher quality of the healthcare services. The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one of the best solutions to address these challenges and therefore to prevent and diagnose possible health impairments in people. The remote monitoring of environmental parameters and how they can cause or mediate any disease, and the monitoring of human daily activities and physiological parameters are among the vast applications of IoT in healthcare, which has brought extensive attention of academia and industry. Assisted and smart tailored environments are possible with the implementation of such technologies that bring personal healthcare to any individual, while living in their preferred environments. In this paper we address several requirements for the development of such environments, namely the deployment of physiological signs monitoring systems, daily activity recognition techniques, as well as indoor air quality monitoring solutions. The machine learning methods that are most used in the literature for activity recognition and body motion analysis are also referred. Furthermore, the importance of physical and cognitive training of the elderly population through the implementation of exergames and immersive environments is also addressed. Full article
(This article belongs to the Special Issue Assistive Devices and Sensors)
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