SMART CONTROL SYSTEM AND METHOD BASED ON MACHINE LEARNING FOR MODULATING END-TIDAL CONCENTRATION LEVELS BY MEANS OF ADJUSTMENTS TO THE VOLUME AND CONCENTRATION OF AN INCOMING RESPIRATORY GAS FLOW IN REAL TIME

摘要

The present invention relates to a smart control system and method based on machine learning for modulating end-tidal concentration levels by means of continuous adjustments to the volume and concentration of an incoming respiratory gas flow (Gin) comprising the following steps: (a) continuously sampling and measuring a first pressure and concentration signal (CP10) for the incoming gas flow (Gin) administered in a respiratory device (200) at a current instant of respiration (T0), (b) continuously sampling and measuring a second pressure and concentration signal (CP20) for a respiratory gas flow (Gresp) in the respiratory device (200) at the current instant of respiration (T0), (c) estimating, using the signals sampled and measured in steps (a) and (b) and in concentration and pressure signals (CP1n, CP2n) measured at previous instants of respiration (T-n), a new volume and a new concentration of oxygen and carbon dioxide for the incoming gas flow (Gin) for an instant of inspiration in the immediate future (T1), and (d) adjusting the volume and concentration of oxygen and carbon dioxide in the incoming respiratory gas flow (Gin) within a given inspiration cycle.