计算机工程2026，Vol.52Issue(2)：110-124,15.DOI:10.19678/j.issn.1000-3428.0069495
基于瞳孔直径动态数字分析的情感评估
Affective Assessment Based on Dynamic Digital Analysis of Pupil Diameter
摘要
Abstract
In recent years,emotion recognition research based on physiological signal measurements has gradually gained traction.In particular,Pupil Diameter(PD)is considered a promising physiological indicator that can intuitively reflect changes in an individual's emotional state.However,challenges persist in the denoising process of pupil signals and accuracy of emotion recognition.To address these issues,this study proposes a dual-filter denoising method and a digital classification method based on machine learning.The study aims to effectively denoise the PD signal while retaining subtle features related to emotions and improve the accuracy of assessing subjects'different emotional states.First,an emotion induction experiment is designed based on auditory and visual stimuli to guide subjects through emotional states ranging from calm to startled,stressed,and pleasant.Simultaneously,eye-tracking devices are used to collect continuous data on the PD signal.To mitigate noise in the data,cubic spline interpolation is employed to compensate for the signal loss caused by blinking and system noise from equipment.Subsequently,a dual preprocessing step using Kalman filtering and wavelet denoising is applied to the raw data.Then,using four key features extracted from the pupil data,the emotional states of the subjects are classified and compared across five classification algorithms,achieving an average accuracy of 84.38％.The performance of each model is evaluated.The Multilayer Perceptron(MLP)demonstrates the best performance,achieving the highest accuracy of 87.07％.Finally,the performance of the four features in distinguishing different emotional states is compared using Receiver Operating Characteristic(ROC)curves.关键词
情感评估/瞳孔直径/卡尔曼滤波/小波去噪/沃尔什变换/机器学习/接收者操作特征曲线Key words
affective assessment/Pupil Diameter(PD)/Kalman filtering/wavelet denoising/Walsh transform/machine learning/Receiver Operating Characteristic(ROC)curves分类
信息技术与安全科学引用本文复制引用
武子璇,刘银华..基于瞳孔直径动态数字分析的情感评估[J].计算机工程,2026,52(2):110-124,15.基金项目
国家重点研发计划(2020YFB1313600). （2020YFB1313600）
