A human-machine interaction system for visual acuity test based on gesture recognition

Changfeng Li

doi:10.1117/12.3010579

1 December 2023 A human-machine interaction system for visual acuity test based on gesture recognition

Changfeng Li

Proceedings Volume 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023); 1294032 (2023) https://doi.org/10.1117/12.3010579
Event: Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 2023, Sipsongpanna, China

Abstract

Visual acuity (VA) assessment is a critical screening method for evaluating ocular function and identifying ophthalmic disorders such as myopia. However, conventional VA tests reliant on human-human interaction suffer from limitations such as subjectivity, dependence on medical professionals, optotype memorization, and fixed subject-optotype distance. To address these limitations, this paper introduces an innovative Human-Machine Interaction (HMI) system specifically designed for VA assessment. The HMI system consists of a computer, an external camera, dedicated HMI software, and gesture input as its key components. The intelligent core of the system is the HMI software, which incorporates static gesture recognition, optotype size design, and a VA retrieval algorithm. The primary function of the HMI software is to process real-time data captured by the camera, dynamically adjust optotype sizes based on gesture recognition facilitated by the MediaPipe Hands module, and retrieve VA levels using the VA retrieval algorithm. Experimental results involving 50 participants demonstrate an average accuracy rate of 96.2% in gesture recognition, with specific accuracy rates ranging from 93.6% to 99.2% for different directions. The overall performance validates the HMI system's effectiveness in achieving highly accurate VA assessments.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Changfeng Li "A human-machine interaction system for visual acuity test based on gesture recognition", Proc. SPIE 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 1294032 (1 December 2023); https://doi.org/10.1117/12.3010579

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Gesture recognition

Visualization

Detection and tracking algorithms

Cameras

Design and modelling

Computing systems

Binary data

Show All Keywords

Keywords/Phrases

Search In:

Publication Years