摘要
目的 探讨3D观影诱发视疲劳的变化规律,制订一种综合性的视疲劳评价指标。方法 采用皮尔逊相关系数和回归分析的方法,选取10名被试在3D观影场景下诱发疲劳实验,分析被试主观视疲劳自评指标、客观人眼闪光融合频率、深度知觉指标的变化规律及指标之间的相关性。结果 (1)观看3D电影120分钟后被试的闪光融合频率变化范围为2.9-8.3Hz;(2)视疲劳状态时被试间深度感知能力表现出较大的个体差异;(3)视疲劳主观指标与客观指标变量呈现较强的线性相关性,(4)客观闪光融合频率和深度知觉变量的回归模型判定系数R2为0.514-0.595。结论 主、客观视疲劳评价指标均能反映观看3D电影80分钟后被试达到视疲劳状态,多指标结合作为评估视疲劳的判别参数更加合理有效。
Objective To explore the changing patterns of 3D viewing-induced visual fatigue and to develop a comprehensive visual fatigue evaluation index.Methods Using Pearson's correlation coefficient and regression analysis,10 subjects were selected for the experiment of inducing fatigue in 3D viewing scenes,and the change patterns of subjective visual fatigue self-assessment indexes,objective human eye flash fusion frequency and depth perception indexes and the correlation between the indexes were analyzed.Results(1)The range of change in flash fusion frequency of the subjects after 120 minutes of viewing 3D movies was 2.9-8.3 Hz;(2)the depth perception ability showed large individual differences between subjects during the state of visual fatigue;(3)the subjective indicators of visual fatigue showed a strong linear correlation with the objective indicator variables,(4)the coefficient of determination of the regression model for the objective flash fusion frequency and depth perception variables,R2,was 0.514-0.595.Conclusion Both subjective and objective visual fatigue evaluation indicators can reflect the state of visual fatigue after 80 minutes of viewing 3D movies,and the combination of multiple indicators is more reasonable and effective as a discriminatory parameter for assessing visual fatigue.
作者
孙军亚
孙瑞山
SUN Jun-ya;SUN Rui-shan(College of Safety Science and Engineering,Civil Aviation University of China,Tianjin 300300,China)
出处
《人类工效学》
2023年第2期31-36,共6页
Chinese Journal of Ergonomics
基金
国家自然科学基金青年基金项目(编号:71701202)
天津市教委科研计划项目(编号:2020KJ029)。
关键词
职业健康
深度知觉
闪光融合频率
3D电影
视疲劳诱发
主客观综合指标
皮尔逊相关系数
回归分析
用户体验
occupational health
depoth perception
eye flash fusion frequence
3D movie
Induction of visual fatigue
comprehensive subjective and objective indicators
pearson correlation coefficient analysis
linear regression
user experience
