• 1. MOE Key Laboratory of Biomedical Information Engineering, Xi’an Jiaotong University, Xi’an 710049, P.R.China;
  • 2. State Key Laboratory for Manufacturing System Engineering, Xi’an Jiaotong University, Xi’an 710049, P.R.China;
  • 3. Harvard Medical School and Massachusetts General Hospital, Charlestown, MA 02129-4404, United States;
YAN Xiangguo, Email: xgyan@mail.xjtu.edu.cn
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In order to meet the requirements in the cooperation and competition experiments for an individual patient in clinical application, two human interactive behavior key-press models based on hidden Markov model (HMM) were proposed. To validate the cooperative and competitive models, a verification experimental task was designed and the data were collected. The correlation of the score and subjects’ participation level has been used to analyze the reasonability verification. Behavior verification was conducted by comparing the statistical difference in response time for subjects between human-human and human-computer experiment. In order to verify the physiological validity of the models, we have utilized the coherence analysis to analyze the deep information of prefrontal brain area. Reasonability verification shows that the correlation coefficient for the training data and the testing data is 0.883 1 and 0.578 6 respectively based on cooperation model, and 0.813 1 and 0.617 8 respectively based on the competition model. The behavioral verification result shows that the cooperation and competition models have an accuracy of 71.43% respectively. The results of physiological validity show that the deep information of prefrontal brain area could been extracted based on the cooperation and competition models, and reveal the consistency of coherence between the double key-press cooperative and competitive experiments, respectively. Above all, the high consistency is obtained between the cooperatio/competition model and the double key-press experiment by the behavioral and physiological evaluation results. Consequently, the cooperation and competition models could be applied to clinical trials.

Citation: QIN Long, GAO Lin, ZHANG Quan, WANG Yifei, WEI Yuhui, YAN Xiangguo. Hidden Markov models for human interactive behavior. Journal of Biomedical Engineering, 2019, 36(1): 40-49. doi: 10.7507/1001-5515.201705037 Copy

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