Prediction of state anxiety by machine learning applied to photoplethysmography data

Figure 1. (A) PPG system employed; (B) PPG probe were made of a LED at 940 nm of wavelength and a silicon photomultiplier (SiPM).

Figure 2. Schematic representation of the preprocessing steps of PPG signals and an example of the pulse average PPG with associated standard errors (shaded areas).

Figure 3. Histogram of the distribution of SA estimated by means of STAI-Y.

Figure 4. Histogram of the distribution of correlation coefficients estimated with a bootstrap procedure.

Figure 5. (A) Correlation and (B) Bland–Altman plot of SA and SAp for the GLM based estimation.

Figure 6. (A) Histogram reporting the distribution of AUC obtained with a Bootstrap procedure; (B) ROC of SAp in assessing high contingent anxiety (SA > 40).