ABSTRACT
Quantifiers were introduced to convert recurrence plots into a statistical analysis of dynamical properties. It is shown that the Shannon entropy, if properly computed, increases as the chaotic regime is developed as expected. Recurrence plots and a new estimator for the Shannon entropy are then used to identify asynchronisms in non-invasive mechanical ventilation. It is thus shown that the phase coherence-easily identified using a Shannon entropy-is relevant in the quality of the mechanical ventilation. In particular, some patients with chronic respiratory diseases or healthy subjects can have a high rate of asynchronisms but a regular breathing rhythm.
Subject(s)
Respiration, Artificial/statistics & numerical data , Female , Humans , Male , Models, Statistical , Nonlinear Dynamics , Obesity Hypoventilation Syndrome/physiopathology , Obesity Hypoventilation Syndrome/therapy , Pulmonary Disease, Chronic Obstructive/physiopathology , Pulmonary Disease, Chronic Obstructive/therapy , Respiration, Artificial/methods , Respiratory MechanicsABSTRACT
Recurrence plots were introduced to quantify the recurrence properties of chaotic dynamics. Hereafter, the recurrence quantification analysis was introduced to transform graphical interpretations into statistical analysis. In this spirit, a new definition for the Shannon entropy was recently introduced in order to have a measure correlated with the largest Lyapunov exponent. Recurrence plots and this Shannon entropy are thus used for the analysis of the dynamics underlying patient assisted with a mechanical noninvasive ventilation. The quality of the assistance strongly depends on the quality of the interactions between the patient and his ventilator which are crucial for tolerance and acceptability. Recurrence plots provide a global view of these interactions and the Shannon entropy is shown to be a measure of the rate of asynchronisms as well as the breathing rhythm.