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Journal Article 7

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2022 1

2019 1

2015 2

2010 1

2009 1

Keywords

Emotion recognition 3

emotion 2

Affect computing 1

Attention mechanism 1

Electroencephalogram (EEG) 1

Facial expression 1

Fusion algorithm 1

Kansei Engineering 1

Kinect 1

Music 1

Neural network 1

Personality traits 1

Physiological signals 1

Real-time classification 1

Speech emotion recognition 1

Support vector machine (SVM) 1

Unsupervised feature learning 1

Wavelet transform 1

architectural wall coatings 1

chromatic-light emotion 1

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Speech emotion recognitionwith unsupervised feature learning

Zheng-wei HUANG,Wen-tao XUE,Qi-rong MAO

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 5, Pages 358-366 doi: 10.1631/FITEE.1400323

Abstract: Emotion-based features are critical for achieving high performance in a speech emotion recognition (SERmachines), which have promise for learning task-related features by using unlabeled data, to speech emotion

Keywords： Speech emotion recognition Unsupervised feature learning Neural network Affect computing

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UsingKinect for real-time emotion recognition via facial expressions

Qi-rong MAO,Xin-yu PAN,Yong-zhao ZHAN,Xiang-jun SHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 4, Pages 272-282 doi: 10.1631/FITEE.1400209

Abstract: Emotion recognition via facial expressions (ERFE) has attracted a great deal of interest with recentIn this paper, we propose a real-time emotion recognition approach based on both 2D and 3D facial expressionExperiments on both an emotion dataset and a real-time video show the superior performance of our method

Keywords： Kinect Emotion recognition Facial expression Real-time classification Fusion algorithm Support vector

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Review of sentiment analysis: An emotional product development view

Frontiers of Engineering Management Pages 592-609 doi: 10.1007/s42524-022-0227-z

Abstract: Furthermore, after conceptualizing emotion as Kansei and introducing emotional product development and

Keywords： sentiment analysis emotion product development Kansei Engineering

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Overall HIEs deconstruction method and its application

Li LIN, Chengqi XUE,

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 4, Pages 466-471 doi: 10.1007/s11465-009-0076-z

Abstract: Based on the human interface elements (HIEs) as the emotional carriers, this paper researches the general analysis steps of hierarchical HIEs and puts forward a new systematical deconstruction method for Kansei engineering fields. A mobile phone is taken as the research subject, the emotional design rules are inferred based on the multiple-orientation information of human interfaces, and the emotional change law is grasped from a new perspective. The research on the deconstruction method promotes the study of Kansei engineering and is a significant guide and reference for the theory and practice of related product design fields.

Keywords： product design relationship model human interface design rules emotion

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Research on a quantificational method for chromatic-light emotions of architectural wall coatings in landscape illumination

Ting WANG, Ma JIAN, Gang LIU, Xiaoxi LIU, Mingyu ZHANG

Frontiers of Structural and Civil Engineering 2010, Volume 4, Issue 4, Pages 498-502 doi: 10.1007/s11709-010-0096-0

Abstract: Research on quantificational methods for chromatic-light emotion is an effective way of finding out theThis paper took chromatic-light-induced-emotion towards architectural wall coatings in landscape as the

Keywords： landscape illumination architectural wall coatings chromatic-light emotion quantitative research

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Using psychophysiologicalmeasures to recognize personalmusic emotional experience Research Articles

Le-kai ZHANG, Shou-qian SUN, Bai-xi XING, Rui-ming LUO, Ke-jun ZHANG

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 7, Pages 964-974 doi: 10.1631/FITEE.1800101

Abstract:

Music can trigger human emotion. This is a psychophysiological process.In this study, we explore a new method of personal music emotion recognition based on human physiological

Keywords： Music Emotion recognition Physiological signals Wavelet transform

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A personality-guided affective brain–computer interface for implementation of emotional intelligence in machines Research Article

Shaojie LI, Wei LI, Zejian XING, Wenjie YUAN, Xiangyu WEI, Xiaowei ZHANG, Bin HU,zhangxw@lzu.edu.cn,bh@lzu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 8, Pages 1158-1173 doi: 10.1631/FITEE.2100489

Abstract: Affective brain–computer interfaces have become an increasingly important topic to achieve emotional intelligence in human–machine collaboration. However, due to the complexity of signals and the individual differences in emotional response, it is still a great challenge to design a reliable and effective model. Considering the influence of on emotional response, it would be helpful to integrate personality information and EEG signals for . This study proposes a personality-guided attention neural network that can use personality information to learn effective EEG representations for . Specifically, we first use a convolutional neural network to extract rich temporal and regional representations of EEG signals, and a special convolution kernel is designed to learn inter- and intra-regional correlations simultaneously. Second, inspired by the fact that electrodes within distinct brain scalp regions play different roles in , a personality-guided regional- is proposed to further explore the contributions of electrodes within a region and between regions. Finally, attention-based long short-term memory is designed to explore the temporal dynamics of EEG signals. Experiments on the AMIGOS dataset, which is a dataset for multimodal research for affect, , and mood on individuals and groups, show that the proposed method can significantly improve the performance of subject-independent and outperform state-of-the-art methods.

Keywords： Electroencephalogram (EEG) Emotion recognition Attention mechanism Personality traits