The article describes methods of adaptive control of the preset resistance in the respiratory complexes with regard to changes in the human condition based on the results of identifying the respiratory system parameters, as well as on the results of modeling of the respiratory system presented as a combination of airway generations, the last of which ends with alveoli. The presented algorithms lay the basis for building intelligent medical systems involving adaptive corrective action.

The paper deals with the problem of data processing in adaptive detection of inspiration / expiration by machines for treating sleep apnea using statistical decision theory and based on preliminary analysis of human respiration. The authors establish a law of noise distribution and develop an inspiration and expiration detection algorithm which envisages calculation of the likelihood ratio, which is compared with the threshold values, at each step. As a result, a conclusion is drawn, and a decision is taken on the need to initiate the treatment of sleep apnea with the machine. The use of this algorithm reduces the detection time by 2-3 times, making it possible to carry out preliminary adjustment of parameters for each patient. The problem of definition of person s respiratory system condition with the use of the methods based on a task of the dosed values of resistance/pressure of switching in a respiratory contour with the subsequent creation of diagnostic matrixes state, in which every line characterizes parameters value at a certain loading for the throttle and relay modes of complexes correcting influence is solved.