## 4 Results and Discussion  
As stated earlier, the dynamical analysis of the PPG signal was carried out on 40 young and healthy individuals aged from 18 to 30. However, the main body of this paper only reflects the results of five of them because, in the remaining individuals, the findings are similar (see Figures A1-A3 in Accompanying Material, Appendix A, for further details). Figure 1 shows the time and frequency characteristics of reference signals, that is to say, its time evolution and Power Spectrum Density, respectively, along with the modified 0-1 test results, according to Table 1. Power Spectrum Density gives information to distinguish reference signals between them. Time evolution, Figure 1a-e, allows seeing some regularity in the evolutionary structure of the reference signals. The most regular are periodic and quasi-periodic signals, and the most irregular signals are chaotic and random. However, no discernible difference is apparent among the latter signals, even though the chaotic signal is deterministic and the other, the random signal, is not. As time evolves, new frequency components are added to the signal in the case of the aperiodic signal, thereby avoiding its frequency stability. From the spectral view, Figure 1f-j, the periodic signal has a fundamental frequency and harmonics due to the discontinuity present on the dynamic evolution of the signal, resolved with an infinite number of harmonics in Fourier series expansion. The quasi-periodic signal has two visible peaks, whose frequencies are irrationally related. The aperiodic signal is a continuous spectrum in the working frequency range, and the chaotic and random signals display a broadband spectrum; although, in the chaotic signal, it is not uncommon to distinguish some peaks that rise above the broadband baseline. Concerning the 0-1 test, the diffusion model characterized by the graphic representation of \(q_{c}(n)\) versus \(p_{c}(n)\), Figure 1k-o, describes how the system generating a given signal tries to fill in the surrounding bi-dimensional space. The periodic signal draws up a precise orbit, well-bounded in space; the aperiodic signal covers the entire space bounded by a restrictive area. Conversely, the chaotic and random signals tend to expand erratically by the surrounding space; the dispersion speed is higher for the random signal, according to the coordinate values of the graphic representation, because the chaotic signal is recurring and it usually confirms a clear tendency towards some regions (darker areas) to which it visits most frequently. The quasi-periodic signal presents an intermediate behavior between periodic and aperiodic since it covers the space circumscribed to a restricted area but describing regular paths, in our case elliptical, that do not overlap given the irrational relationship between the constituent frequencies of the signal. The diffusion correlation coefficient value \(K_{m}\), obtained by applying the modified 0-1 test, according to the procedure proposed in Table 1, is shown for all reference signals in Figure 1p-t. For a periodic signal, \(K_{m}\) is tiny (\(K_{m}<0.07\)); in particular, in our case, for our periodic reference signal \(K_{m}=0.0684\), and the case of a pure sine wave with a fundamental frequency at 10 Hz \(K_{m}\approx 0.06\). For a quasi-periodic signal, \(K_{m}\) grows very little (\(\approx\)0.1 or higher) but aiming at an order of magnitude slightly higher; for our quasi-periodic reference signal, \(K_{m}=0.0944\). The \(K_{m}\) value of the aperiodic signal gets away from the periodic values as new frequencies incorporate into the signal; in our aperiodic reference signal, \(K_{m}=0.6962\), when the number of points is 30,000. In the case of a chaotic or random signal \(K_{m}\approx 1\); if it is not known a priori, the modified 0-1 test gives the same answer, even knowing that the 0-1 test was initially designed only for deterministic systems.