title: [Study of emotion recognition under stress based on physiological signals by PSO-kNN method].
abstract: In this paper, experiments were designed for inducing neutral, terrified, excited, annoying emotions, and also low, middle, high, three levels of tension emotions of stress state, respectively. Based on the multi physiological signals generated by the subjects in emotions, such as heart rate and respiration rate and so on, we extracted features from these data which had been eliminated the baseline. Then the Particle Swarm Optimization method was adopted to optimize the features selection from the features of multi physiological signals, and combined with k-Nearest Neighbor algorithm, different emotions and varying degree tensions were classified. The result shows that the classification accuracy of the kNN method with SPO and baseline eliminated is better than the traditional kNN method.
authors.affiliation: School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240.
authors.forename: Hongyang
authors.initials: H
authors.lastname: Sun
authors.forename: Zuyang
authors.initials: Z
authors.lastname: Xu
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
authors.forename: Pei
authors.initials: P
authors.lastname: Lei
authors.forename: Kaijie
authors.initials: K
authors.lastname: Wu
authors.forename: Xinyu
authors.initials: X
authors.lastname: Chai
mesh_terms: D000465:Algorithms; D035841:Behavioral Research / Q000295:instrumentation* / Q000379:methods*; D004644:Emotions; D006801:Humans; D013315:Stress, Psychological