【摘要】 目的探索多维设计特征产品外观的用户情感测量,建立基于生理指标的用户情感预测模型。方法以马克杯为例,通过外观解构,多维设计要素提取,正交组合设计,建立产品外观原型。利用眼动追踪和脑电技术,采集用户观看产品外观时的眼动数据和脑电信号。结果分析发现,注视点数,注视总时间,扫视路径长度,FP1、FP2、FPZ、F3、FC3、FC4、PZ、PO3、PO4、POZ、O1、OZ电极Gamma波相对功率,以及F3电极点Delta波相对功率等指标在高、中、低三种情感外观均具有显著性差异,且利用这些指标建立的PLS模型,具有较好的拟合度。结论各评价指标能够有效区分用户对马克杯产品外观的高、中、低情感。用户情感预测模型能够有效地预测用户对多维设计特征产品外观的情感,但在跨越不同类别产品时,模型的拟合度有所下降。研究为多维设计特征产品的用户情感测量提供了有效的方法。更多还原

【Abstract】 Objective This study aims to explore the measurement of users’ emotion toward Product Appearance with Multiple Design Features and establish the prediction model of users’ emotion based on physiological indicators.Methods The prototypes of mug product were modeled through decomposing,extracting multiple design features,and orthogonal combinatorial designing.Then,the subjective assessment of emotion,eye-tracking metrics,and electroencephalography signals were collected.Results The results showed that indicators of fixation count,total fixation duration,scan path length,the relative power of gamma rhythm in FP1、FP2、FPZ、F3、FC3、FC4、PZ、PO3、PO4、POZ、O1、OZ electrodes and the relative power of delta rhythm in F3 electrode significantly varied between any two of the high,middle,and low emotional response.The prediction model established through PLS revealed a good fitness.Conclusion Each physiological indicator can effectively distinguish users’ high,medium and low emotional response to the appearance of mug product.The prediction model of users’ emotion can effectively predict their emotional response toward the product appearance with multiple design features.However,the model’s fitness would reduce when crossing different categories of products.This study can provide an effective method for measuring users’ emotional response to products appearance with multiple design features.更多还原