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  • 标题:Dynamic switched non-parametric identification of the human physiological response under virtual reality stimuli ⁎
  • 本地全文:下载
  • 作者:Gustavo Hernández-Melgarejo ; Rita Q. Fuentes-Aguilar ; Alejandro Garcia-Gonzalez
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:7878-7884
  • DOI:10.1016/j.ifacol.2020.12.1968
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this work, it is proposed a Switched Differential Neural Networks structure (SDNN) to model the human physiological response in a virtual stimuli scenario. Two physiological variables are assessed: electrocardiography and electrodermal activity, which provide a reflex response after stimuli. The proposed approach is focused on the representation of two discrete primary states, relaxation and stress as the response of the virtual stimuli. A switched dynamic approach is set, in which the trigger of an stimuli generates a change in the heartbeat rate as well as in the skin conductivity, constructing the switch between the mentioned states. The SDNN allows to obtain a model structure whose dynamics corresponds to the rate of change of the physiological variables, given as result a particular class of uncertain switched systems. The proposed non-parametric identification in this switched structure is implemented and experimentally assessed showing appropriate convergence rates in, both, switching regions and the continuous states.
  • 关键词:KeywordsUncertain dynamic systemsswitching systemsnon-parametric identificationvirtual realityphysiological signals
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