摘要
以放松减压为目标的情绪调节及放松状态评估有助于提升国民身心健康。针对降低生理信号采集导致的放松情绪诱发困难,使用附着型人体传感器采集受试者的心率信号进行放松状态识别,使用混合音频诱发受试者产生放松情绪,从二维情绪量表中换算获得放松状态标签。采集受试者的心率信号,从心率信号中提取时域特征、频域特征和心拍数。基于多层感知机和长短时记忆网络构建放松评估模型,实现放松状态识别。实验结果表明,相比于目前的研究成果,该放松识别模型具有更优的分类性能,能够为情绪调节与放松状态评估问题提供一种新的可靠解决方法。
Emotion regulation and relaxation state assessment aiming at relaxation and stress reduction can help improve the physical and mental health of the people.In order to reduce the difficulty of inducing relaxation caused by the acquisition of physiological signals,this paper uses the attached human sensor to collect the heart rate signal of the subjects to identify the relaxation state.Mixed audio is used to induce the subjects to produce a relaxed mood,and the relaxed state label is converted from the two-dimensional mood scale.The heart rate signal of the subject is collected,and the time domain feature,frequency domain feature and heart rate are extracted from the heart rate signal.Based on multilayer perceptron and long-short-term memory network,a relaxation evaluation model is constructed to realize relaxation state recognition.The experimental results show that,compared with the current research results,the relaxation recognition model proposed in this paper has better classification performance,and may provide a new and reliable method for emotion regulation and relaxation state assessment.
作者
张雅斓
董子瑞
杜飞龙
魏云
卢瑞东
班晓娟
ZHANG Yalan;DONG Zirui;DU Feilong;WEI Yun;LU Ruidong;BAN Xiaojuan(School of Intelligence Science and Technology,University of Science and Technology Beijing,Haidian Beijing 100083;Shunde Innovation School,University of Science and Technology Beijing,Foshan Guangdong 528300;Institute of Artificial Intelligence,University of Science and Technology Beijing,Haidian Beijing 100083;Panasonic Appliances(China)Co.,Ltd,Hangzhou 310018;Beijing Key Laboratory of Knowledge Engineering for Materials Science,University of Science and Technology Beijing,Haidian Beijing 100083)
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2023年第2期289-295,共7页
Journal of University of Electronic Science and Technology of China
基金
广东省自然科学基金(2021A1515012285)。
关键词
特征融合
心率信号
心率变异性特征信号
放松评估模型
放松减压
feature fusion
heart rate(HR)signal
heart rate variability(HRV)features signal
relaxation evaluation model
stress relief
