Figure 4. Logical scheme of the overall short-time emotion recognition concept.

The autonomic nervous system acts on the cardiovascular system modulating its electrical activity. This activity affects the heartbeat dynamics, which can be non-invasively revealed by the analysis and modeling of the RR interval series. To perform this task, we propose to consider a point-process probability density function in order to characterize cardiovascular dynamics at each moment in time. In particular, we use Wiener-Volterra nonlinear autoregressive integrative functions to estimate quantitative tools such as spectrum and bispectrum from the linear and nonlinear terms, respectively. Given the instantaneous spectra and high-order spectra, several features are combined to define the feature set, which is the input of the personalized pattern recognition procedure. Support vector machines are engaged to perform this task by adopting a leave-one-out procedure.