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Special Issue "Sensor Technologies for Caring People with Disabilities"

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

Deadline for manuscript submissions: closed (15 November 2018)

Special Issue Editors

Guest Editor
Prof. Dr. Francisco José García-Peñalvo

GRIAL Research Group, Computer Science Department, Research Institute for Educational Sciences, University of Salamanca, Paseo de Canelejas 169, Salamanca 37008, Spain
Website | E-Mail
Interests: technological ecosystems; human–computer interaction; learning technologies
Guest Editor
Dr. Manuel Franco-Martín

Department of Psychiatry, Zamora Hospital, Zamora, Spain
Website | E-Mail
Interests: psychiatry; dementia; caring for people with disabilities

Special Issue Information

Dear Colleagues,

According to the World Health Organization, over a billion people, about 15% of the world's population, have some form of disability. Furthermore, rapid growth of the aging population is causing an increase in chronic health conditions, and therefore a rise in the population rates of disability. Additionally, people with disabilities have less access to health care services and are more prone to experience unmet health care needs.

In this sense, recent advances in sensor research and innovation have boosted the prospects of the use of these technologies for assisting people with disabilities. Sensors are used for many different purposes in regards to disabled people. Monitoring and alarm systems, for example, can ameliorate the adverse effects of unpredictable events, such as sudden illness, falls, or wandering. Pressure sensors have been employed in robotics for the treatment of children with autism. IMUs and laser systems have been used in building a virtual cane for the blind. In sort, the use of sensors can improve the quality of life of people with disabilities, as well as promoting their independence.

Taking the above into account, research in sensor technologies for the disabled is an open field which needs attention from the research community. Thus, the aim of this Special Issue is to present recent developments on sensor technologies for caring people with disabilities, focusing on the different configurations that can be used and novel applications in the field. Additionally, unlike other sensor areas, there are some aspects not strictly related with the technology that could be envisaged such as: User acceptance, privacy, safety, standardization or the required qualification for the use of the sensor technologies.

This Special Issue invites contributions on the following topics (but is not limited to them):

  • Sensors in health monitoring
  • Sensors in rehabilitation
  • Indoor navigation aid
  • Real time tracking of disabled people
  • Assisted living
  • Home Medical Assistance
  • Privacy, safety or standardization issues

Prof. Dr. Francisco José García-Peñalvo
Dr. Manuel Franco-Martín
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 papers will be 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 monthly 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 1800 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

  • Sensors
  • Disabled people
  • Assisted living
  • Assisting systems
  • Health monitoring
  • Wearable technologies
  • Indoor positioning
  • Human activity recognition
  • Vital sign monitoring
  • Personalized medicine

Published Papers (2 papers)

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Research

Open AccessArticle Support for Employees with ASD in the Workplace Using a Bluetooth Skin Resistance Sensor–A Preliminary Study
Sensors 2018, 18(10), 3530; https://doi.org/10.3390/s18103530
Received: 7 September 2018 / Revised: 17 October 2018 / Accepted: 17 October 2018 / Published: 19 October 2018
PDF Full-text (8736 KB) | HTML Full-text | XML Full-text
Abstract
The application of a Bluetooth skin resistance sensor in assisting people with Autism Spectrum Disorders (ASD), in their day-to-day work, is presented in this paper. The design and construction of the device are discussed. The authors have considered the best placement of the
[...] Read more.
The application of a Bluetooth skin resistance sensor in assisting people with Autism Spectrum Disorders (ASD), in their day-to-day work, is presented in this paper. The design and construction of the device are discussed. The authors have considered the best placement of the sensor, on the body, to gain the most accurate readings of user stress levels, under various conditions. Trial tests were performed on a group of sixteen people to verify the correct functioning of the device. Resistance levels were compared to those from the reference system. The placement of the sensor has also been determined, based on wearer convenience. With the Bluetooth Low Energy block, users can be notified immediately about their abnormal stress levels via a smartphone application. This can help people with ASD, and those who work with them, to facilitate stress control and make necessary adjustments to their work environment. Full article
(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)
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Open AccessArticle Visual Localizer: Outdoor Localization Based on ConvNet Descriptor and Global Optimization for Visually Impaired Pedestrians
Sensors 2018, 18(8), 2476; https://doi.org/10.3390/s18082476
Received: 13 June 2018 / Revised: 25 July 2018 / Accepted: 26 July 2018 / Published: 31 July 2018
PDF Full-text (14560 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Localization systems play an important role in assisted navigation. Precise localization renders visually impaired people aware of ambient environments and prevents them from coming across potential hazards. The majority of visual localization algorithms, which are applied to autonomous vehicles, are not adaptable completely
[...] Read more.
Localization systems play an important role in assisted navigation. Precise localization renders visually impaired people aware of ambient environments and prevents them from coming across potential hazards. The majority of visual localization algorithms, which are applied to autonomous vehicles, are not adaptable completely to the scenarios of assisted navigation. Those vehicle-based approaches are vulnerable to viewpoint, appearance and route changes (between database and query images) caused by wearable cameras of assistive devices. Facing these practical challenges, we propose Visual Localizer, which is composed of ConvNet descriptor and global optimization, to achieve robust visual localization for assisted navigation. The performance of five prevailing ConvNets are comprehensively compared, and GoogLeNet is found to feature the best performance on environmental invariance. By concatenating two compressed convolutional layers of GoogLeNet, we use only thousands of bytes to represent image efficiently. To further improve the robustness of image matching, we utilize the network flow model as a global optimization of image matching. The extensive experiments using images captured by visually impaired volunteers illustrate that the system performs well in the context of assisted navigation. Full article
(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)
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