A Systematic Review of Assistive Tools for Individuals with Visual Impairments: Advancements in Assistive Technologies, Internet of Things and Computer Vision

Caytuiro-Silva N.E.; Castro-Gutierrez E.G.; Peña-Alejandro J.M. · CEUR Workshop Proceedings (2023)

Resumen

Visual impairment significantly impacts the lives of millions globally, affecting daily activities and independence. Assistive technologies have emerged as promising tools to enhance autonomy and inclusion for individuals with visual disabilities. Despite numerous tools addressing mobility, navigation, orientation, and object recognition, many remain as proposals or prototypes, with limited impact on the visually impaired community. A comprehensive systematic review is crucial to assess the current state of assistive technology, IoT, and Computer Vision, identifying limitations, areas for improvement, and opportunities for new solutions. This review aims to analyze and synthesize theoretical and practical literature related to assistive tools for individuals with visual impairments. Conducting an exhaustive search on academic databases such as IEEE and Scopus, the review focuses on keywords like computer vision, deep learning, blind or visually impaired. Inclusion and exclusion criteria will guide study selection, with a focus on evaluating study quality. The systematic review analyzes recent technological advancements in assistive tools for the visually impaired, assessing limitations and contributions found in the literature. Key aspects, such as the accuracy and reliability of IoT and Computer Vision-based assistive technologies, are thoroughly evaluated. The University Isabel I systematic review method is employed, involving a manual search of 71 articles from journals, conference proceedings, and books. The findings provide valuable insights for future research, offering a current overview of existing assistive tools for visual impairment. Limitations and improvements identified guide and inspire future research in assistive technologies, IoT, and computer vision. Results reveal a higher publication rate in the Institute of Electrical and Electronics Engineers (IEEE) journal from the United States. The predominant limitation is technological dependence (16.46%), while the most significant contribution lies in the accuracy of detecting objects of interest (11.70%). This systematic review aims to broaden the understanding of existing assistive tools for visual impairment, focusing on technological advancements in Computer Vision and IoT. It anticipates guiding future research towards developing more effective assistive tools for visually impaired individuals.

Instituciones: Universidad Católica de Santa María