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Sign Language Recognition System for Deaf Patients: Protocol for a Systematic Review.

Milena Soriano Marcolino^1,2,3, Lucca Fagundes Ramos Oliveira⁴, Lucas Rocha Valle¹

¹Universidade Federal de Minas Gerais, Medical School, Belo Horizonte, Brazil.

JMIR Research Protocols

|January 23, 2025

Summary

This systematic review examines communication systems for deaf individuals in healthcare. It identifies human-machine interfaces designed to improve interactions and overcome communication barriers in health services.

Keywords:

artificial intelligence biomedical technology communication aids for disabled communication barriers computer neural networks computer vision deaf people gestures hearing loss sign language

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Area of Science:

Human-Computer Interaction
Health Informatics
Assistive Technologies

Background:

Individuals with hearing impairments face significant challenges in accessing healthcare.
Communication barriers can lead to adverse health outcomes and iatrogenic events.
Development of automatic communication systems is crucial for this population.

Purpose of the Study:

To systematically review evidence on sign language communication systems for deaf individuals in healthcare.
To identify systems using human-computer interaction techniques tested with users.
To assess usability and application in real-world health contexts.

Main Methods:

Systematic literature search across major databases (MEDLINE, Web of Science, ACM, IEEE) and conferences.
Inclusion criteria: sign language recognition systems in healthcare, tested with human users.
Data extraction, synthesis, and descriptive analysis following PRISMA guidelines.

Main Results:

Study selection concluded July 2024.
Data extraction, synthesis, and reporting are expected by February 2025.
Preliminary search conducted in April 2024.

Conclusions:

This review will identify human-machine systems facilitating communication for deaf patients in health services.
A framework for usability and application in human contexts will be presented.
Findings will highlight systems addressing communication barriers and compare implementation practices.