An exploratory study of multimodal interaction modeling based on neural computation
An exploratory study of multimodal interaction modeling based on neural computation作者机构：Beijing Key Laboratory of Human-Computer Interaction Institute of SoftwareChinese Academy of Sciences University of Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of Sciences
出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))
年 卷 期：2016年第59卷第9期
页 面：63-78页
核心收录：
学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 081201[工学-计算机系统结构] 071102[理学-系统分析与集成] 081103[工学-系统工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by National Natural Science Foundation of China(Grant Nos.61232013,61422212,61303162) National High Technology Research and Development Program of China(Grant Nos.2015AA020506,2015AA016305)
主 题：human-computer interaction multimodal integration interaction model touch-included interac tion cognition multisensory integration neural computation brain coding
摘 要：Multimodal interaction serves an important role in human-computer interaction. In this paper we propose a multimodal interaction model based on the latest cognitive research findings. The proposed model combines two proven neural computations, and helps to reveal the enhancement or depression influence of multimodal presentation upon the corresponding interaction task performance. A set of experiments is designed and conducted within the constraints of the model, which demonstrates the observed performance enhancement and depression effects. Our exploration and the experimental results help to further solve the question about how tactile feedback signal contribute the multimodal interaction efficiency which could provide guidelines for designing the tactile feedback in multimodal interaction.
同方期刊数据库