Linear and Nonlinear Directed Connectivity Analysis of the Cardio-Respiratory System in Type 1 Diabetes

Figures

• 

  FIGURE 1. Experimental recording setup.

• 

  FIGURE 2. Example of (A) ECG, (B) breathing and (C) LDF perfusion signals recorded from a young control subject.

• 

  FIGURE 3. Time-frequency ridges of the (A) ECG, (B) breathing and (C) LDF perfusion signals shown in Figure 2. Ridges were estimated by means of the adaptive parametric approach developed in (Iatsenko et al., 2016).

• 

  FIGURE 4. Cardio-respiratory directional coupling strength parameters estimated via DBI (Eqs 4, 5; two per panel), and respective directionality indices (Eq. 6; one per panel) obtained from a control subject (left) and a T1D patient (right).

• 

  FIGURE 5. Box plots of DBI measures of connectivity (Eqs 4–6). Top panel: comparison of all (six) cardio-respiratory coupling parameters estimated with DBI for the control (blue) and T1D (red) groups. Bottom panel: comparison of the (three) directionality indices per pair interaction for the control (blue) and T1D (red) groups. Statistically significant decreases, identified by one-tailed Wilcoxon rank-sum tests, are denoted by (*) above the respective boxes.

• 

  FIGURE 6. Box plots of DTF measures of connectivity in the (0.05, 2) Hz frequency band (Eqs 10, 12). Top panel: median ± first and third quartiles of ssDTF values across all directed interactions for control (blue) and T1D (red) groups. Bottom panel: directionality indices per pair interaction for the control (blue) and T1D (red) groups (*) above boxes denotes p-value < 0.05 estimated from non-parametric one-tailed Wilcoxon rank-sum tests comparing T1D and control groups.