Exploring computer vision algorithms in assistive technologies: a systematic literature review

Authors

  • Douglas Klann Universidade do Vale do Itajaí
  • Anita Maria da Rocha Fernandes Universidade do Vale do Itajaí
  • Eduardo Alves da Silva Universidade do Vale do Itajaí
  • Wemerson Delcio Parreira Pontifícia Universidade Católica de Campinas

DOI:

https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1326

Keywords:

Visual Impairment, Systematic Review of Literature, Computational Vision

Abstract

Objective: This article presents a systematic literature review of studies that propose algorithms for computer vision (CV) applications aimed at visually impaired individuals. The objective is to identify these studies and understand the purpose of each solution in mapping applications geared towards digital health access. Method: A systematic literature review was conducted by searching major open-access scientific article databases. Results: Initially, 360 studies were identified, but only six articles were selected based on stringent inclusion and exclusion criteria. Conclusion: The review reveals the existence of research utilizing CV for developing devices with various functionalities for visually impaired individuals. However, none of the studies found address the use of computer vision for technologies focused on health access or reducing accessibility barriers in digital health.

Author Biographies

Douglas Klann, Universidade do Vale do Itajaí

Acadêmico, ADS, Universidade do Vale do Itajaí, Itajaí (SC), Brasil.

Anita Maria da Rocha Fernandes, Universidade do Vale do Itajaí

Prof. Dr., Escola Politécnica, Universidade do Vale do Itajaí, Itajaí (SC), Brasil.

Eduardo Alves da Silva, Universidade do Vale do Itajaí

Prof. MSc., Escola Politécnica, Universidade do Vale do Itajaí, Itajaí (SC), Brasil.

Wemerson Delcio Parreira, Pontifícia Universidade Católica de Campinas

Prof. Dr., Faculdade de Engenharia Elétrica, Pontifícia Universidade Católica de Campinas, Campinas (SP), Brasil.

References

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Aguiar, A. S. C. D., Almeida, P. C. D., Grimaldi, M. R. M., & Guimarães, F. J. (2022). Health education technologies for people with visual impairment: integrative review. Texto & Contexto-Enfermagem, 31, e20210236.

OMS. Relatório Mundial da Visão. Light for the World, 1 edition, 2021. ISBN 9789241516570.

Fank, E., Bevilacqua, F., Duarte, D., & Scapinello, A. INSIDe: Image recognition tool aimed at helping visually impaired people contextualize indoor environments. Revista Brasileira de Computação Aplicada, 11(3), 59-71, 2019.

Ricarte, I. M. & Galvão, M. C. B. Revisão sistemática da literatura: Conceituação, produção e publicação. Logeion: Filosofia da Informação, 6(1):57–73, set. 2019.

Younis, O. et al. A hazard detection and tracking system for people with peripheral vision loss using smart glasses and augmented reality. International Journal of Advanced Computer Science and Applications, 10(2), 2019. doi: 10.14569/IJACSA.2019.0100201

Khan, M. A. et al. An ai-based visual aid with integrated reading assistant for the completely blind. IEEE Transactions on Human-Machine Systems, 50 (6):507–517, 2020. doi: 10.1109/THMS.2020.3027534

Chessa, M. et al. An integrated artificial vision framework for assisting visually impaired users. Computer Vision and Image Understanding, 149:209–228, 2016. ISSN 1077-3142. doi: 10.1016/j.cviu.2015.11.007

Kim, K. et al. Assisting people with visual impairments in aiming at a target on a large wall-mounted display. International Journal of Human-Computer Studies, 86:109–120, 2016. ISSN 1071- 5819. doi: 10.1016/j.ijhcs.2015.10.002.

Tapu, R.; Mocanu, B. & Zaharia, T. Deep-see: Joint object detection, tracking and recognition with application to visually impaired navigational assistance. Sensors, 17(11), 2017. ISSN 1424-8220. doi: 10.3390/s17112473

Mascetti, S. et al. A. Robust traffic lights detection on mobile devices for pedestrians with visual impairment. Computer Vision and Image Understanding, 148, 123-135. 2016 doi: https://doi.org/10.1016/j.cviu.2015.11.017

Published

2024-11-19

How to Cite

Klann, D., Fernandes, A. M. da R., da Silva, E. A., & Parreira, W. D. (2024). Exploring computer vision algorithms in assistive technologies: a systematic literature review. Journal of Health Informatics, 16(Especial). https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1326

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