Color Vision Deficiency Recognition Based on Eye-Tracking Metrics Using Machine Learning Approaches

被引:0
作者
Bitkina, Olga Vl. [1 ]
Park, Jaehyun [2 ]
Ryu, Do-Hyeon [1 ]
机构
[1] Incheon Natl Univ, Dept Ind & Management Engn, Incheon, South Korea
[2] Konkuk Univ, Dept Ind Engn, Neungdong Ro 120, Seoul 05029, South Korea
基金
新加坡国家研究基金会;
关键词
Eye-tracking; color vision deficiency; colorblindness; deuteranopia; protanopia; user experience; DRIVERS; PROTAN;
D O I
10.1080/10447318.2024.2415764
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Individuals with color vision deficiency (CVD) face many difficulties and limitations in their daily lives and professional activities, some of which may prove life-threatening. These negative factors necessitate the development of methods for the identification and classification of CVD. Because CVD is a vision impairment, it is crucial to determine if its presence can be predicted with eye behavior. An experiment was conducted using a driving simulator and eye-tracking glasses. The experiment included 27 people with CVD (12 with deuteranopia, 9 with deuteranomaly, 3 with protanopia, and 3 with protanomaly) and 10 people with normal color vision. Each participant performed multiple driving attempts with color-coded guidelines on the navigator to assess visual search ability. Based on data recorded by an eye tracker, the following three types of cross-validated models were developed: binary classification (presence and absence of CVD), a three-class model to recognize the absence of CVD, protanopia, and deuteranopia, and a five-class model to predict the absence of CVD, deuteranopia, deuteranomaly, protanopia, and protanomaly. These three models yielded respective accuracy levels of over 95%, 66%-78%, and 43%-52%. Overall, it was found that eye-tracking metrics have the potential to classify and predict CVD.
引用
收藏
页码:8928 / 8942
页数:15
相关论文
共 44 条
[1]   Eye Tracking in Driver Attention Research-How Gaze Data Interpretations Influence What We Learn [J].
Ahlstrom, Christer ;
Kircher, Katja ;
Nystrom, Marcus ;
Wolfe, Benjamin .
FRONTIERS IN NEUROERGONOMICS, 2021, 2
[2]  
Alcaraz-Martinez R., 2023, RES SQUARE, DOI [10.21203/rs.3.rs-3349271/v1, DOI 10.21203/RS.3.RS-3349271/V1]
[3]  
[Anonymous], 2022, BUSINESS WIRE SITE
[4]  
[Anonymous], 2023, JP SITE
[5]  
[Anonymous], 2022, CLEVELAND CLIN SITE
[6]   Traffic signal color recognition is a problem for both protan and deutan color-vision deficients [J].
Atchison, DA ;
Pedersen, CA ;
Dain, SJ ;
Wood, JM .
HUMAN FACTORS, 2003, 45 (03) :495-503
[7]   Color Constancy of Red-Green Dichromats and Anomalous Trichromats [J].
Baraas, Rigmor C. ;
Foster, David H. ;
Amano, Kinjiro ;
Nascimento, Sergio M. C. .
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2010, 51 (04) :2286-2293
[8]   Image Content Enhancement Through Salient Regions Segmentation for People With Color Vision Deficiencies [J].
Bruno, Alessandro ;
Gugliuzza, Francesco ;
Ardizzone, Edoardo ;
Giunta, Calogero Carlo ;
Pirrone, Roberto .
I-PERCEPTION, 2019, 10 (03)
[9]  
Charman WN, 1997, OPHTHAL PHYSL OPT, V17, P371, DOI 10.1016/S0275-5408(97)00014-8
[10]  
Cole Barry L, 2002, Clin Exp Optom, V85, P246