Research on electroencephalogram emotion recognition based on the feature fusion algorithm of auto regressive model and wavelet packet entropy / 生物医学工程学杂志

Focused on the world-wide issue of improving the accuracy of emotion recognition, this paper proposes an electroencephalogram (EEG) signal feature extraction algorithm based on wavelet packet energy entropy and auto-regressive (AR) model. The auto-regressive process can be approached to EEG signal as much as possible, and provide a wealth of spectral information with few parameters. The wavelet packet entropy reflects the spectral energy distribution of the signal in each frequency band. Combination of them gives a better reflect of the energy characteristics of EEG signals. Feature extraction and fusion are implemented based on kernel principal component analysis. Six emotional states from a public multimodal database for emotion analysis using physiological signals (DEAP) are recognized. The results show that the recognition accuracy of the proposed algorithm is more than 90%, and the highest recognition accuracy is 99.33%. It indicates that this algorithm can extract the feature of EEG emotion well, and it is a kind of effective emotion feature extraction algorithm, providing support to emotion recognition.

Methods and Applications of Psychological Stress State Assessment / 生物医学工程学杂志

In this paper, the response of individual's physiological system under psychological stress state is discussed, and the theoretical support for psychological stress assessment research is provided. The two methods, i.e., the psychological stress assessment of questionnaire and physiological parameter assessment used for current psychological stress assessment are summarized. Then, the future trend of development of psychological stress assessment research is pointed out. We hope that this work could do and provide further support and help to psychological stress assessment studies.

Affective computing--a mysterious tool to explore human emotions / 生物医学工程学杂志

Perception, affection and consciousness are basic psychological functions of human being. Affection is the subjective reflection of different kinds of objects. The foundation of human being's thinking is constituted by the three basic functions. Affective computing is an effective tool of revealing the affectiveness of human being in order to understand the world. Our research of affective computing focused on the relation, the generation and the influent factors among different affections. In this paper, the affective mechanism, the basic theory of affective computing, is studied, the method of acquiring and recognition of affective information is discussed, and the application of affective computing is summarized as well, in order to attract more researchers into this working area.