多生理信号信息融合技术的情绪识别发展  

Overview of emotion recognition development of multi-physiological signal information fusion technology

作　　者：杨捷鸿 焦学军[2] 曹勇[2] 李启杰 楚洪祚 黄梦盈 姜劲[2] YANG Jiehong;JIAO Xuejun;CAO Yong;LI Qijie;CHU Hongzuo;HUANG Mengying;JIANG Jin(Department of Graduate School,Space Engineering University,Beijing 101416,China;Key Laboratory of Human Factors Engineering,China Astronaut Research and Training Centre,Beijing 100094)

机构地区：[1]航天工程大学研究生院,北京101416 [2]中国航天员科研训练中心人因工程国防科技重点实验室,北京100094

出　　处：《生物医学工程研究》2021年第4期420-427,共8页Journal Of Biomedical Engineering Research

基　　金：国家自然科学基金资助项目(81671861);人因工程国防科技重点实验室试验技术课题资助项目(SYFD061905,YYJJ190604)。

摘　　要：近年来,焦虑、抑郁症的发生率大幅增加,有效识别情绪并对负面情绪进行及时干预和排解显得尤为必要。现阶段情绪识别的研究主要有针对非生理信号和生理信号的识别。其中,生理信号采集的数据更为客观。随着便携式、可穿戴设备的快速发展,基于生理信号的情绪识别显示出广阔的应用前景。由于利用单一生理信号对情绪分类准确率的提升陷入了瓶颈,不少学者开始研究融合多种生理信号进行情绪识别。本文从基于生理信号的情绪识别、信息融合、分类等方面,梳理了近年来多生理信号在情绪识别领域的发展进程和研究现状,并归纳总结了目前存在的主要问题和挑战。In recent years,the incidence of anxiety and depression has increased significantly.It is particularly necessary to effectively recognize emotions and to intervene and resolve negative emotions in a timely manner.At present,the research of emotion recognition mainly includesnon-physiological signals and physiological signals.Among them,the data collected by physiological signals is more objective.With the rapid development of portable and wearable devices,emotion recognition based on physiological signals has shown broad application prospects.Because of using single physiological signal to improve the accuracy of emotion classification has fallen into a bottleneck,and many scholars have begun to study the fusion of multiple physiological signals for emotion recognition.Based on physiological signals of emotion recognition,information fusion and classification,we comb the development process and research status of multiple physiological signals in the field of emotion recognition in recent years,and summarize the main problems and challenges that currently exist.

关 键 词：情绪识别 多生理信号 脑电 功能性近红外光谱技术 特征提取 虚拟现实 

分 类 号：R318[医药卫生—生物医学工程] B842.6[医药卫生—基础医学]