摘要
为客观有效地获取用户对产品的感性意象需求,将内隐测量技术引入意象提取过程,探求用户非主观意识下认知数据与产品意象间的关系,建立基于内隐联想测验、多模态内隐测量(眼—脑融合)相结合的无意识多模态内隐测量意象提取模型。以标志性实验样本为模型构建的实验样本,进行认知实验;对无意识认知过程中各内隐主数据进行归一化和拟合化处理;建立基于关系分析法和图像分析法的内隐主数据关联函数;将数值加权融合,构建基于无意识多模态内隐测量的意象提取模型。以案例的非标志性样本再次验证了意象提取模型的有效性。结果表明,所提出的无意识多模态内隐测量方法,可直观地表达出各内隐测量数据的关联性;标志性样本在模型构建过程中的使用,可减少模型构建过程的主观性因素;意象提取结果与意象主观评估结果具有一致性和相关性。模型构建过程可为产品意象客观的决策模型提供新的思路,为设计师解读用户对产品的意象认知提供更客观的途径。
To obtain the emotional needs of users for products objectively and effectively,the implicit measurement technology was added in the emotional extraction process.The relationship between user's non-subjective cognitive data and product emotional evaluation was explored,and an emotion extraction model was established.The experimental samples constructed from Iconic Sample(IS)were combined with the implicit association test and multi-mode implicit measurement method to conduct cognitive experiments.Then,each implicit data was normalized and fitted in the process of unconscious cognition.Based on relationship analysis and image analysis,the correlation function of implicit data was established.An emotional extraction model based on the unconscious multimodal implicit measurement was constructed by combining the numerical weights.The results showed that there were consistency and correlation between emotional extraction and subjective evaluation.The model construction process could provide new ideas for the objective decision-making model of product emotions and provide more objective ways for designers to interpret the emotional cognition of users.
作者
郭主恩
林丽
阳明庆
张云鹍
GUO Zhuen;LIN Li;YANG Mingqing;ZHANG Yunkun(School of Mechanical Engineering,Guizhou University,Guiyang 550025,China;Key Laboratory of Advanced Manufacturing Technology,Ministry of Education,Guizhou University,Guiyang 550025,China)
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2022年第4期1150-1163,共14页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(51465007,51865003)
贵州省科技计划资助项目(黔科合平台人才[2018]5781],黔科合基础-ZK[2021]重点055)
贵州大学培育项目([2019]06)。
关键词
设计认知
意象提取
无意识
多模态
内隐测量
设计创新
design cognition
image extraction
unconsciousness
multi-modal
implicit measurement
design innovation
