It is studied the MIT-BIH Normal Sinus Rhythm Database using a statistical technique of analysis, that is based on the Wavelet and Hilbert Transforms. With that technique, it was previously found, that there is a collective and intrinsic dynamical be
havior up to a scale of 64 heartbeats. Now it is shown, that using the Biorthogonal wavelet bior3.1 such a behavior reaches the scale 1024. That result confirms, that the circulatory system is out of equilibrium. According to the Statistical Mechanics of Tsallis, and a recent interpretation of G. Wilk et al. respect to the non extensive parameter q, the healthy human being is characterized by q=1.70+/-0.01.
It is feasible to obtain any basic rule of the already known Quantum Mechanics applying the Hamilton-Jacobi formalism to an interacting system of 2 fermionic degrees of freedom. The interaction between those fermionic variables unveils also a primitive spin and zitterbewegung.
A tetra of sets which elements are time series of interbeats has been obtained from the databank Physionet-MIT-BIH, corresponding to the following failures at the humans heart: Obstructive Sleep Apnea, Congestive Heart Failure, and Atrial Fibrillatio
n. Those times series has been analyzed statistically using an already known technique based on the Wavelet and Hilbert Transforms. That technique has been applied to the time series of interbeats for 87 patients, in order to find out the dynamics of the heart. The size of the times series varies around 7 to 24 h. while the kind of wavelet selected for this study has been any one of: Daubechies, Biortoghonal, and Gaussian. The analysis has been done for the complet set of scales ranging from: 1-128 heartbeats. Choosing the Biorthogonal wavelet: bior3.1, it is observed: (a) That the time series hasnt to be cutted in shorter periods, with the purpose to obtain the collapsing of the data, (b) An analytical, universal behavior of the data, for the first and second diseases, but not for the third.
