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Assistive Technologies for People With Disabilities

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Disabilities".

Deadline for manuscript submissions: closed (17 August 2023) | Viewed by 2860

Special Issue Editors


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Guest Editor
Institute of Media Communications, Faculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, Slovenia
Interests: accessibility; e-learning; telecommunication

E-Mail Website
Guest Editor
Institute of Media Communications, Faculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, Slovenia
Interests: disability; digital media; user experience

Special Issue Information

Dear Colleagues,

People with disabilities are individuals who often require specially designed assistive technology that helps to maintain or improve their functioning and independence. According to the World Health Organization (WHO, 2021), in light of the ageing global population and rise in the number of noncommunicable diseases, more than 2 billion people will need at least one assistive product by 2030, with many older people needing two or more.

Assistive technologies hold great promise as tools for supporting individual functioning and communication needs. Hearing aids, wheelchairs, communication aids, spectacles, prostheses, pill organizers, and memory aids are all examples of assistive products. However, even the most sophisticated technology may be of little use if it does not fit well with the individual’s requirements and usage needs. Today, the research and development of assistive technologies remain limited and specialized, primarily serving specific categories of disabilities, such as blind or deaf people, while focusing less on people with mental and behavioral disabilities.

The Special Issue invites contributions investigating all aspects of the accessibility, usability, and intelligence of assistive technologies for people with disabilities, including the following:

  • User-controlled smart systems
  • Multimodal integration of information in assistive technologies
  • Hearing instrument technology, applications, and usability
  • Accessible and adaptable systems and accessories in smart cities
  • Cognitively controlled systems and accessories
  • Machine and deep learning for ICT-based assistive technologies

Papers addressing these topics are invited for submission to this Special Issue. Those combining a high academic standard coupled with a practical focus on the provision of optimal assistive technology solutions are especially welcome.

Dr. Matjaž Debevc
Dr. Ines Kožuh
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 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
  • accessibility
  • accessible information and communication technology
  • active and assisted living
  • universal design
  • multimodality
  • machine and deep learning
  • extended reality

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Published Papers (1 paper)

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Research

15 pages, 1935 KiB  
Article
Indoor Signs Detection for Visually Impaired People: Navigation Assistance Based on a Lightweight Anchor-Free Object Detector
by Yahia Said, Mohamed Atri, Marwan Ali Albahar, Ahmed Ben Atitallah and Yazan Ahmad Alsariera
Int. J. Environ. Res. Public Health 2023, 20(6), 5011; https://doi.org/10.3390/ijerph20065011 - 12 Mar 2023
Cited by 1 | Viewed by 1874
Abstract
Facilitating the navigation of visually impaired people in indoor environments requires detecting indicating signs and informing them. In this paper, we proposed an indoor sign detection based on a lightweight anchor-free object detection model called FAM-centerNet. The baseline model of this work is [...] Read more.
Facilitating the navigation of visually impaired people in indoor environments requires detecting indicating signs and informing them. In this paper, we proposed an indoor sign detection based on a lightweight anchor-free object detection model called FAM-centerNet. The baseline model of this work is the centerNet, which is an anchor-free object detection model with high performance and low computation complexity. A Foreground Attention Module (FAM) was introduced to extract target objects in real scenes with complex backgrounds. This module segments the foreground to extract relevant features of the target object using midground proposal and boxes-induced segmentation. In addition, the foreground module provides scale information to improve the regression performance. Extensive experiments on two datasets prove the efficiency of the proposed model for detecting general objects and custom indoor signs. The Pascal VOC dataset was used to test the performance of the proposed model for detecting general objects, and a custom dataset was used for evaluating the performance in detecting indoor signs. The reported results have proved the efficiency of the proposed FAM in enhancing the performance of the baseline model. Full article
(This article belongs to the Special Issue Assistive Technologies for People With Disabilities)
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