Abstract
We conducted a statistical analysis of the data, which are included in the regulatory and adaptive capabilities (RAC) estimation algorithm, to obtain the forecasting of maximum boundary (Max.B.) of synchronization range of cardiac and respiratory rhythms, in order to minimize the definition time of RAC of the human body by the method of the cardiorespiratory synchronism (CRS). The following factors have been examined as the basis of the Max.B. forecast: the minimum boundary of the synchronization range, duration of evolution synchronization at the minimum boundary, Initial respiratory rate, Initial heart rate, age, height, weight, gender, menstrual cycle phase (only for women), diastolic and systolic blood pressure values. Linear and quadratic regression models, and neural network techniques - multilayer perceptron and radial basis function network have been analyzed. Neural network regression has shown the best accuracy: the value of synchronization range of cardiac and respiratory rhythms value can be forecast by these factors with the relative error of 20-30%, the probability will be grow up to level of 80-90%.
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