Automatic target control method for concentration of end-expiratory anesthetic gas of anaesthesia machine and anaesthesia machine

Abstract

The invention belongs to the technical field of anaesthesia machines, and relates to an automatic target control method for the concentration of end-expiratory anesthetic gas of an anaesthesia machine and the anaesthesia machine. Calculating the deviation between the concentration of the end-expiratory anesthetic gas exhaled in the current respiratory cycle and a gas concentration set value; when the deviation and / or the change amount of the end-expiratory anesthetic gas concentration is larger than the threshold value, the flow of fresh gas used for flushing the anesthetic respiratory system is increased, and the anesthetic gas concentration of the fresh gas is adjusted till the deviation and the change amount of the end-expiratory anesthetic gas concentration are smaller than the threshold value; calculating predicted values of the concentration of the end-expiratory anesthetic gas in a plurality of future respiratory cycles; an anesthetic gas concentration optimization model is constructed and solved to obtain the optimal inhaled anesthetic gas concentration variation of each future respiratory cycle, so that the target flow of the fresh gas of each future respiratory cycle is calculated to control the conveying parameters of the fresh gas, and the final-expiratory anesthetic gas concentration is taken as an adjusting target to adjust the flow rate of the fresh gas. And the concentration of the end-expiratory anesthetic gas is effectively controlled through real-time feedback, dynamic prediction and adjustment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of anesthetizing machines, in particular to an anesthetizing machine end-expiratory anesthetic gas concentration automatic target control method and an anesthetizing machine. BACKGROUND

[0002] As a key medical device in general anesthetic surgery, the anesthetizing machine plays an irreplaceable role in regulating the depth of anesthesia of patients and maintaining oxygenation. The end-expiratory anesthetic gas concentration is one of the indicators reflecting the depth of anesthesia of patients, and controlling this parameter within the target range is one of the main purposes of anesthetists adjusting the fresh gas supply of the anesthetizing machine. In recent years, with the increasing number of general anesthetic surgeries in China year by year, the workload of anesthetists is becoming heavier and heavier. Therefore, realizing the automatic target control of the end-expiratory anesthetic gas concentration and making quantitative compensation on this basis will help to reduce the workload of anesthetists and the consumption of anesthetic gas, and improve the timeliness and accuracy of the control of the end-expiratory anesthetic gas concentration.

[0003] At present, the main way to control the end-expiratory anesthetic gas concentration is to manually adjust the output concentration of the anesthetic evaporator and the fresh gas flow, there is no public automatic control method, and there is no clear adjustment basis in the adjustment process. The patent with publication number CN117899320B discloses an anesthetic gas output control method for an anesthetizing machine, which automatically adjusts the anesthetic gas output flow and rate according to the changes in various physiological parameters of the patient, analyzes and judges the physiological condition value based on the collected physiological parameter information, compares the value with the preset threshold interval, and adjusts the anesthetic gas output rate; however, the physiological condition value is a comprehensive index based on the patient's heart rate value, blood pressure value, body temperature value, respiratory rate and blood oxygen value, and there is no direct corresponding relationship between the end-expiratory anesthetic gas concentration. This method does not directly control the end-expiratory anesthetic gas concentration as the direct control target, so it cannot effectively control the end-expiratory anesthetic gas concentration.

[0004] In summary, the anesthetic gas output control method in the prior art cannot directly and effectively control the end-expiratory anesthetic gas concentration, resulting in the inability to meet the demand for accurate and stable anesthesia. SUMMARY

[0005] Therefore, the technical problem to be solved by the present application is to overcome the problem that the anesthetic gas output control method in the prior art cannot directly and effectively control the end-expiratory anesthetic gas concentration, resulting in the inability to meet the demand for accurate and stable anesthesia.

[0006] To solve the above technical problems, the present application provides an anesthetizing machine end-expiratory anesthetic gas concentration automatic target control method applied to a control device of an anesthetizing machine, comprising: S10: acquiring the end-expiratory anesthetic gas concentration of the patient in the current breathing cycle in real time, and calculating the deviation of the end-expiratory anesthetic gas concentration from the set value of the end-expiratory anesthetic gas concentration; S20: if the absolute value of the deviation is greater than or equal to a preset deviation threshold value and / or the absolute value of the change amount of the end-expiratory anesthetic gas concentration is greater than or equal to a preset change amount threshold value, increasing the flow rate of fresh gas used for flushing the anesthetic breathing system, adjusting the anesthetic gas concentration of the fresh gas, and returning to step S10 until the absolute value of the deviation is less than the preset deviation threshold value and the absolute value of the change amount of the end-expiratory anesthetic gas concentration is less than the preset change amount threshold value; S30: inputting the actual value of the end-expiratory anesthetic gas concentration of the last breathing cycle into an anesthetic gas concentration change kinetics model, and outputting the predicted value of the end-expiratory anesthetic gas concentration of the current and future breathing cycles; S40: taking the change amount of the inhaled anesthetic gas concentration of the current and future adjacent breathing cycles as the decision variable, and taking the minimization of the deviation of the predicted value of the end-expiratory anesthetic gas concentration from the set value of the end-expiratory anesthetic gas concentration as the target, to construct an anesthetic gas concentration optimization model; S50: solving the anesthetic gas concentration optimization model to obtain the optimal change amount of the inhaled anesthetic gas concentration of the current and future breathing cycles; based on the optimal change amount of the inhaled anesthetic gas concentration, the volume of the anesthetic breathing system, the maximum value of the anesthetic gas concentration of the fresh gas, and the gas delivery time set value, obtaining the anesthetic gas compensation amount of the current and future breathing cycles and the target flow rate of the fresh gas when the compensation is performed, so as to control the delivery parameters of the fresh gas.

[0007] Preferably, the deviation includes an absolute deviation and a relative deviation; The absolute value of the deviation being greater than or equal to the preset deviation threshold value specifically refers to the absolute value of the absolute deviation being greater than or equal to a preset absolute deviation threshold value / the absolute value of the absolute deviation being less than the preset absolute deviation threshold value and the absolute value of the relative deviation being greater than or equal to a preset relative deviation threshold value; The absolute value of the deviation being less than the preset deviation threshold value specifically refers to the absolute value of the absolute deviation being less than the preset absolute deviation threshold value / the absolute value of the absolute deviation being greater than or equal to the preset absolute deviation threshold value and the absolute value of the relative deviation being less than the preset relative deviation threshold value.

[0008] Preferably, the adjustment of the anesthetic gas concentration of the fresh gas in step S20 includes: acquiring the deviation of each breathing cycle up to the current breathing cycle, and comparing the minimum value of the absolute values of the deviations of the breathing cycles with a preset minimum deviation value; if the minimum value is greater than or equal to the preset minimum deviation value, keeping the anesthetic gas concentration of the fresh gas unchanged; if the minimum value is less than the preset minimum deviation value, judging whether the current breathing cycle is the first breathing cycle with the absolute value of the deviation being less than a first preset threshold value. if the current respiratory cycle is not the first respiratory cycle whose absolute value of deviation is less than the first preset threshold, keeping the fresh gas anesthetic gas concentration unchanged; if the current respiratory cycle is the first respiratory cycle whose absolute value of deviation is less than the first preset threshold, decreasing the fresh gas anesthetic gas concentration when the deviation of the current respiratory cycle is positive, and increasing the fresh gas anesthetic gas concentration when the deviation of the current respiratory cycle is negative.

[0009] Preferably, the adjusting the fresh gas anesthetic gas concentration in step S20 further comprises: if the number of respiratory cycles in which the fresh gas anesthetic gas concentration is kept unchanged among all respiratory cycles up to the current respiratory cycle is greater than or equal to a preset number of cycles, adjusting the fresh gas anesthetic gas concentration; wherein the adjusting formula of the fresh gas anesthetic gas concentration is expressed as: , wherein, represents the fresh gas anesthetic gas concentration at the moment t; the fresh gas anesthetic gas concentration adjusted at the moment t; represents the end-tidal anesthetic gas concentration set value at the moment t; the end-tidal anesthetic gas concentration at the moment t; represents the proportionality coefficient. Preferably, the process of constructing the anesthetic gas concentration change kinetics model comprises: obtaining the inhaled anesthetic gas concentration of each respiratory cycle up to the current respiratory cycle, calculating the difference between the inhaled anesthetic gas concentration of each respiratory cycle and the inhaled anesthetic gas concentration of the previous respiratory cycle to obtain the inhaled anesthetic gas concentration change amount of each respiratory cycle;

[0010] using the least square method to estimate the correlation coefficient between the inhaled anesthetic gas concentration and the end-tidal anesthetic gas concentration based on the inhaled anesthetic gas concentration and the exhaled anesthetic gas concentration of each respiratory cycle, thereby obtaining the relationship between the inhaled anesthetic gas concentration and the end-tidal anesthetic gas concentration; based on the relationship between the inhaled anesthetic gas concentration and the end-tidal anesthetic gas concentration, constructing the anesthetic gas concentration change kinetics model. Preferably, the relationship between the inhaled anesthetic gas concentration and the end-tidal anesthetic gas concentration is expressed as:

[0011] , , , wherein, , represents the fresh gas anesthetic gas concentration at the moment t; ​an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; , an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle, an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle, ; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; , , , wherein, an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of a respiratory cycle; , This represents the deviation between the end-tidal anesthetic gas concentration and the predicted end-tidal anesthetic gas concentration during the (k-1)th respiratory cycle. This represents the end-tidal concentration of the anesthetic gas during the (k-1)th respiratory cycle; This represents the predicted end-tidal anesthetic gas concentration at the (k-1)th respiratory cycle, after bias correction and taking into account the influence of changes in the concentration of inhaled anesthetic gas.

[0012] Preferably, an anesthetic gas concentration optimization model is constructed using the change in inhaled anesthetic gas concentration between adjacent respiratory cycles as the decision variable and minimizing the deviation between the predicted and set values ​​of the end-tidal anesthetic gas concentration as the objective. This model includes: An objective function for optimizing anesthetic gas concentration is constructed with the goal of minimizing the sum of the square of the weighted L2 norm of the deviation between the setpoint of end-tidal anesthetic gas concentration and the predicted value of end-tidal anesthetic gas concentration after deviation correction and considering the influence of changes in inhaled anesthetic gas concentration, and the square of the weighted L2 norm of the change in inhaled anesthetic gas concentration. A first constraint function for optimizing anesthetic gas concentration is constructed, with the change in inhaled anesthetic gas concentration satisfying a preset first value range as a constraint; a second constraint function for optimizing anesthetic gas concentration is constructed, with the predicted end-tidal anesthetic gas concentration after deviation correction and considering the influence of changes in inhaled anesthetic gas concentration satisfying a preset second value range as a constraint. Based on the objective function for optimizing anesthetic gas concentration, the first constraint function for optimizing anesthetic gas concentration, and the second constraint function for optimizing anesthetic gas concentration, an optimization model for anesthetic gas concentration is obtained.

[0013] Preferably, the objective function for optimizing the anesthetic gas concentration is expressed as: , , in, , This represents a vector consisting of the changes in the concentration of inhaled anesthetic gas during the current k-th respiratory cycle and the next M-1 respiratory cycles. This represents the change in the concentration of the inhaled anesthetic gas during the current k-th respiratory cycle. This represents the change in the concentration of the inhaled anesthetic gas during the (M-1)th respiratory cycle. , This represents a vector consisting of the end-tidal anesthetic gas concentration setpoints for the current k-th respiratory cycle and the next P-1 respiratory cycles. This represents the end-tidal anesthetic gas concentration setpoint for the current k-th respiratory cycle. Indicates the future number The setpoint for the end-tidal anesthetic gas concentration per respiratory cycle; ; , a weight matrix representing a deviation of the predicted value of the end-tidal anesthetic gas concentration from the set value; a weight matrix representing a change amount of the inhaled anesthetic gas concentration; The anesthetic gas concentration optimization first constraint function is represented as: wherein, represents a minimum value of the preset first value range; represents a maximum value of the preset first value range; The anesthetic gas concentration optimization second constraint function is represented as: wherein, represents a minimum value of the preset second value range; represents a maximum value of the preset second value range.

[0014] Preferably, the calculation formula of the anesthetic gas compensation amount is: wherein, represents the anesthetic gas compensation amount of the kth breathing cycle; represents the inhaled anesthetic gas concentration change amount of the kth breathing cycle; represents the anesthetic breathing system volume; The calculation formula of the target flow of the fresh gas when compensation is performed is: wherein, represents the target flow of the fresh gas when compensation is performed in the kth breathing cycle; represents the maximum value of the anesthetic gas concentration of the fresh gas; represents the gas delivery time set value.

[0015] The present application also provides an anesthetic machine, comprising: a fresh gas delivery system for generating fresh gas with anesthetic gas and delivering to the anesthetic breathing system under the control of the control device; an anesthetic breathing system for delivering the fresh gas to the patient, and detecting the end-tidal anesthetic gas concentration and the inhaled anesthetic gas concentration of the patient in real time and transmitting to the control device; a control device, coupled with the fresh gas delivery system and the anesthetic breathing system, for realizing the steps of the anesthetic machine end-tidal anesthetic gas concentration automatic target control method.

[0016] The anesthetic machine end-tidal anesthetic gas concentration automatic target control method provided by the present application has the following beneficial effects: ​​​​​The application directly calculates the deviation of the end-expiratory anesthetic gas concentration from the set value, judges whether the anesthetic gas concentration and the fresh gas flow need to be adjusted based on the deviation, that is, directly taking the end-expiratory anesthetic gas concentration as a direct control target; when the deviation is large and the end-expiratory anesthetic gas concentration is not stable, the fresh gas flow and the anesthetic gas concentration are first coarsely adjusted, so that the end-expiratory anesthetic gas concentration is close to and stable at the set value; at the same time, the end-expiratory anesthetic gas concentration of each future breathing cycle is adjusted through the prediction and quantitative compensation, specifically, by constructing an anesthetic gas concentration dynamic model of the anesthetic machine, the end-expiratory anesthetic gas concentration of the current and future multiple breathing cycles is predicted based on the relatively stable end-expiratory anesthetic gas concentration in the current breathing cycle, so that the prediction value of the end-expiratory anesthetic gas concentration in each future breathing cycle and the deviation of the set value can be calculated, at the same time, since adjusting the fresh gas flow can change the inhaled anesthetic gas concentration of the breathing cycle, thereby affecting the end-expiratory anesthetic gas concentration, therefore, the application takes the minimum deviation of the prediction value of the end-expiratory anesthetic gas concentration from the set value as the target, takes the inhaled anesthetic gas concentration of each breathing cycle as the decision variable, constructs an optimization model and solves it, based on the inhaled anesthetic gas concentration value of each breathing cycle obtained by solving, combined with the volume of the respiratory system, the maximum anesthetic gas concentration in the fresh gas and the input time set value, the fresh gas flow of each breathing cycle within the gas delivery time set value is calculated, so that the end-expiratory anesthetic gas concentration can reach the set value only by adjusting the fresh gas flow within the gas delivery time set value, while the end-expiratory anesthetic gas concentration reaches the set value, the gas consumption is saved. The application directly takes the end-expiratory anesthetic gas concentration as the adjustment target, combines real-time acquisition feedback, dynamic prediction and adjustment, and effectively controls the end-expiratory anesthetic gas concentration of each breathing cycle to reach the set value. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to make the content of the application more easily understood, the application will be further described in detail below according to specific embodiments of the application and in conjunction with the drawings, in which: Figure 1 The application provides an automatic target control method flow chart of the end-expiratory anesthetic gas concentration of an anesthetic machine; Figure 2 The application provides an anesthetic machine structure schematic diagram; Figure 3 The application provides a control principle block diagram of the control device; DRAWINGS: 1, control device; 2, fresh gas delivery system; 21, filter; 22, one-way valve; 23, pressure reducing valve; 24, proportional flow valve; 25, flow sensor; 26, anesthetic evaporator; 3, anesthetic breathing system; 31, anesthetic breathing machine. DETAILED DESCRIPTION

[0018] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0019] Please refer to the following: Figure 1 and Figure 2 , Figure 1 The diagram shown is a flowchart of the automatic target control method for end-tidal anesthetic gas concentration in an anesthesia machine provided in this application. Figure 2 The diagram shown is a schematic diagram of the anesthesia machine provided in this application. The anesthesia machine includes a control device 1, a fresh gas delivery system 2, and an anesthesia breathing system 3.

[0020] The fresh gas delivery system 2 is used to generate fresh gas with a certain concentration of anesthetic gas under the control of the control device 1 and deliver it to the anesthetic respiratory system 3.

[0021] Specifically, the fresh gas delivery system includes multiple delivery branches, each of which includes a filter 21, a one-way valve 22, a pressure reducing valve 23, a proportional flow valve 24, and a flow sensor 25. After entering the fresh gas delivery system 2, the oxygen source flows to each delivery branch. In the first delivery branch, it serves as the driving gas to enable the anesthesia ventilator 31 to operate normally. It then flows to the anesthesia respiratory system 3 via the second delivery branch, and after being mixed with nitrous oxide, oxygen, and anesthetic gas in the third delivery branch, it flows to the anesthesia respiratory system 3 via the anesthesia vaporizer 26. The proportional flow valve 24 and the flow sensor 25 are used to automatically control the flow rate of each delivery branch. The output concentration of the anesthesia vaporizer 26 is maintained at its maximum value. The control device 1 controls the concentration of anesthetic gas in the fresh gas by adjusting the output flow rate of the anesthesia vaporizer 26 and the flow rate of the second delivery branch of the oxygen source.

[0022] The anesthesia respiratory system 3 delivers fresh gas to the patient through the anesthesia ventilator 31. Specifically, the anesthesia ventilator 31 regulates the air pressure within the anesthesia respiratory system 3 to complete the mechanical ventilation function. The anesthesia respiratory system 3 consists of a one-way valve, a carbon dioxide absorber, and various sensors to realize the recycling of exhaled gas and to monitor the patient's respiratory parameters in real time.

[0023] The automatic target control method for end-tidal anesthetic gas concentration in an anesthesia machine provided in this application is applied to control device 1, and the method specifically includes: S10: Real-time acquisition of the patient's end-tidal anesthetic gas concentration during the current respiratory cycle, and calculation of the deviation between the end-tidal anesthetic gas concentration and the set value.

[0024] Specifically, when the control device 1 receives an automatic target control command or starts automatic target control, it begins to acquire the end-tidal anesthetic gas concentration.

[0025] S20: If the absolute value of the deviation is greater than or equal to the preset deviation threshold value and / or the absolute value of the change amount of the end-expiratory anesthetic gas concentration is greater than or equal to the preset change amount threshold value, the flow rate of the fresh gas used to flush the anesthetic respiratory system is increased, the anesthetic gas concentration of the fresh gas is adjusted, and the step S10 is returned to be executed until the absolute value of the deviation is less than the preset deviation threshold value and the absolute value of the change amount of the end-expiratory anesthetic gas concentration is less than the preset change amount threshold value; Specifically, when the deviation is large (i.e., the absolute value of the deviation is greater than or equal to the preset deviation threshold value) and the end-expiratory anesthetic gas concentration is not stable enough (i.e., the absolute value of the change amount of the end-expiratory anesthetic gas concentration is greater than or equal to the preset change amount threshold value, it should be noted that the change amount of the end-expiratory anesthetic gas concentration refers to the difference between the end-expiratory anesthetic gas concentrations of adjacent breathing cycles), the fresh gas flow rate and the anesthetic gas concentration need to be adjusted roughly first.

[0026] For example, increasing the flow rate of the fresh gas used to flush the anesthetic respiratory system can increase the flow rate of the fresh gas to 6 L / min, and then it is determined whether the absolute deviation or the relative deviation is less than 0. If yes, the anesthetic gas concentration in the fresh gas is set to 0 vol%, at this time the fresh gas flow rate output by the anesthetic evaporator 26 will be 0, otherwise it will be the maximum value that the anesthetic evaporator 26 can reach, at this time the flow rate of the second delivery branch of the oxygen gas source will be 0. It should be noted that the anesthetic gas concentration in the fresh gas can also be automatically adjusted by other means, such as using an electrically controlled anesthetic evaporator.

[0027] S30: The actual value of the end-expiratory anesthetic gas concentration of the last breathing cycle is input into the anesthetic gas concentration change kinetics model, and the predicted values of the end-expiratory anesthetic gas concentration of the current and future breathing cycles are output.

[0028] S40: The change amount of the inhaled anesthetic gas concentration of the current and future adjacent breathing cycles is taken as a decision variable, and the deviation between the predicted value of the end-expiratory anesthetic gas concentration and the set value of the end-expiratory anesthetic gas concentration is minimized as an objective, to construct an anesthetic gas concentration optimization model.

[0029] S50: The anesthetic gas concentration optimization model is solved to obtain the optimal change amount of the inhaled anesthetic gas concentration of the current and future breathing cycles; based on the optimal change amount of the inhaled anesthetic gas concentration, the volume of the anesthetic respiratory system, the maximum anesthetic gas concentration of the fresh gas, and the gas delivery time set value, the anesthetic gas compensation amount of the current and future breathing cycles and the target flow rate of the fresh gas when the compensation is performed are obtained, so as to control the delivery parameters of the fresh gas.

[0030] It should be noted that in the rough adjustment stage before step S40, the fresh gas is in a continuous delivery state, whether in the inhalation stage or the exhalation stage, the purpose is to make the concentration change rapidly, reach the vicinity of the set value quickly and enter the steady state, and after entering the compensation stage of step S40, the fresh gas delivery mode is switched from continuous to intermittent, and the gas compensation amount of each breathing cycle is obtained by solving the optimization problem, thereby saving gas consumption. Specifically, the gas compensation refers to that in the exhalation stage of the breathing cycle, the set gas delivery time is the compensation time, and the fresh gas is compensated at the target flow rate during the time, and the flow rate of the fresh gas is 0 during the remaining time. Not only can the end-expiratory anesthetic gas concentration be adjusted, but also the gas consumption can be saved.

[0031] Further, the deviation of the present application includes an absolute deviation and a relative deviation.

[0032] Specifically, the absolute deviation is , wherein, represents the end-expiratory anesthetic gas concentration at the time t, represents the end-expiratory anesthetic gas concentration set value at the time t. The relative deviation is

[0033] The relative deviation is .

[0034] Further, the absolute value of the deviation is greater than or equal to a preset deviation threshold, specifically: the absolute value of the absolute deviation is greater than or equal to a preset absolute deviation threshold / the absolute value of the absolute deviation is less than a preset absolute deviation threshold and the absolute value of the relative deviation is greater than or equal to a preset relative deviation threshold. The absolute value of the deviation is less than a preset deviation threshold, specifically: the absolute value of the absolute deviation is less than a preset absolute deviation threshold / the absolute value of the absolute deviation is greater than or equal to a preset absolute deviation threshold and the absolute value of the relative deviation is less than a preset relative deviation threshold.

[0035] Further, the step S20 of adjusting the anesthetic gas concentration of the fresh gas comprises: Step 1-1: Obtain the deviation of each breathing cycle up to the current breathing cycle, and compare the minimum value of the absolute values of the deviations of each breathing cycle with a preset minimum deviation value.

[0036] Step 1-2: If the minimum value is greater than or equal to the preset minimum deviation value, the anesthetic gas concentration of the fresh gas is kept unchanged.

[0037] Step 1-3: If the minimum value is less than the preset minimum deviation value, it is judged whether the current breathing cycle is the first breathing cycle with the absolute value of the deviation less than a first preset threshold.

[0038] ​Steps 1-4: If the current respiratory cycle is not the first respiratory cycle in which the absolute value of the deviation is less than the first preset threshold, then keep the concentration of the anesthetic gas in the fresh gas constant.

[0039] Steps 1-5: If the current respiratory cycle is the first respiratory cycle in which the absolute value of the deviation is less than the first preset threshold, then when the deviation of the current respiratory cycle is positive, decrease the concentration of anesthetic gas in the fresh gas; when the deviation of the current respiratory cycle is negative, increase the concentration of anesthetic gas in the fresh gas.

[0040] Specifically, the change in the concentration of the anesthetic gas in the fresh gas during steps 1-5 is expressed as follows: , in, express The absolute value of the change in the concentration of the anesthetic gas in the fresh gas at any given time; This represents the proportionality coefficient. ; express The concentration of anesthetic gas in constantly fresh gas; express The concentration of inhaled anesthetic gas at any given time.

[0041] Optionally, in adjusting the concentration of anesthetic gas in the fresh gas, in addition to adjusting according to the above steps 1-1 to 1-5, further adjustments can be made based on the number of adjustment cycles for the concentration of anesthetic gas in the fresh gas.

[0042] Specifically, adjusting the concentration of the anesthetic gas in the fresh gas in step S20 further includes: Steps 1-6: If the number of respiratory cycles in which the concentration of anesthetic gas in fresh gas is maintained is greater than or equal to the preset number of cycles up to the current respiratory cycle, then adjust the concentration of anesthetic gas in fresh gas. The formula for adjusting the concentration of anesthetic gas in fresh gas is expressed as follows: , in, express The concentration of anesthetic gas in the fresh gas after constant adjustment; express The setpoint for the concentration of anesthetic gas at the end of each breath; express The concentration of anesthetic gas at the end of the exhalation period; This represents the proportionality coefficient.

[0043] Furthermore, when the deviation of the current respiratory cycle is small and the concentration of end-tidal anesthetic gas is sufficiently stable, the adjustment mode can be switched from continuous delivery to quantitative compensation. Specifically, steps S30 to S50 are executed.

[0044] Further, the constructing process of the anesthesia gas concentration change dynamics model in step S30 includes: Step 2-1: Obtain the inhaled anesthesia gas concentration of each breath cycle until the current breath cycle, and calculate the difference between the inhaled anesthesia gas concentration of each breath cycle and the inhaled anesthesia gas concentration of the previous breath cycle to obtain the inhaled anesthesia gas concentration change amount of each breath cycle.

[0045] Step 2-2: Estimate the correlation coefficient between the inhaled anesthesia gas concentration and the end-tidal anesthesia gas concentration based on the inhaled anesthesia gas concentration and the exhaled anesthesia gas concentration of each breath cycle by using the least square method, so as to obtain the relationship between the inhaled anesthesia gas concentration and the end-tidal anesthesia gas concentration.

[0046] Step 2-3: Construct the anesthesia gas concentration change dynamics model based on the relationship between the inhaled anesthesia gas concentration and the end-tidal anesthesia gas concentration.

[0047] Specifically, the relationship between the inhaled anesthesia gas concentration and the end-tidal anesthesia gas concentration is expressed as: , , wherein, , represents the end-tidal anesthesia gas concentration data vector composed of the end-tidal anesthesia gas concentrations of the N breath cycles; represents the end-tidal anesthesia gas concentration of the n th breath cycle; represents the inhaled anesthesia gas concentration data matrix composed of the inhaled anesthesia gas concentration change amounts of the N breath cycles; represents the inhaled anesthesia gas concentration change amount of the n th breath cycle; represents the number of breath cycles required for the end-tidal anesthesia gas concentration change amount to be less than the preset change threshold when the inhaled anesthesia gas concentration changes; , represents the correlation coefficient vector between the inhaled anesthesia gas concentration and the end-tidal anesthesia gas concentration, represents the correlation coefficient, . Specifically, the correlation coefficient vector is identified in an offline manner by the embodiment of the present application, and the calculation formula is: , wherein, represents the inhaled anesthesia gas concentration data matrix, , wherein, represents the end-tidal anesthesia gas concentration data vector, ​The correlation coefficient vector estimate between the concentration of inhaled anesthetic gas and the concentration of anesthetic gas at the end of each respiratory cycle is obtained by measuring the concentration of inhaled anesthetic gas and the concentration of anesthetic gas at the end of each respiratory cycle. Preferably, to reduce data storage and save memory space, the correlation coefficient vector can also be processed online. The identification process is performed using the following formula: , , in, , , , Represents the identity matrix. It is a constant. .

[0048] Furthermore, the kinetic model for the change in anesthetic gas concentration is expressed as follows: , , , in, This represents the predicted end-tidal concentration of anesthetic gas at the current k-th respiratory cycle, after bias correction but without considering the influence of changes in the concentration of inhaled anesthetic gas in the current and future P-1 respiratory cycles. This represents the predicted end-tidal concentration of anesthetic gas at the current (k-1)th respiratory cycle, after deviation correction and taking into account the influence of changes in the concentration of inhaled anesthetic gas in the current and future (P-1)th respiratory cycles. This represents the predicted end-tidal concentration of anesthetic gas at the current (k-1)th respiratory cycle, after deviation correction but without considering the influence of changes in the concentration of inhaled anesthetic gas in the current and future (P-1)th respiratory cycles. This represents the deviation correction weight vector, used to weight the deviation. This represents the predicted end-tidal concentration of anesthetic gas at the current k-th respiratory cycle, after deviation correction but without considering the effect of changes in the concentration of inhaled anesthetic gas. This represents the predicted end-tidal concentration of anesthetic gas at the current k-th respiratory cycle, after bias correction but without considering the effect of changes in the concentration of inhaled anesthetic gas in the future P-1-th respiratory cycle. Indicates the use of The correlation coefficient vector estimate between the concentration of inhaled anesthetic gas and the concentration of anesthetic gas at the end of each respiratory cycle is obtained by measuring the concentration of inhaled anesthetic gas and the concentration of anesthetic gas at the end of each respiratory cycle. , This represents the deviation between the end-tidal anesthetic gas concentration and the predicted end-tidal anesthetic gas concentration during the (k-1)th respiratory cycle. end-tidal anesthetic gas concentration of the kth breath cycle; end-tidal anesthetic gas concentration prediction value of the kth breath cycle after bias correction and considering the influence of the change in the inhaled anesthetic gas concentration.

[0049] Further, since the anesthetic gas concentration of fresh gas can only change within a limited range, and the end-tidal anesthetic gas concentration needs to be constrained within a safe range, the application takes the inhaled anesthetic gas concentration change amount of future breath cycles as a decision variable, and constructs a planning problem with constraints.

[0050] Specifically, in step S40, the inhaled anesthetic gas concentration change amount of adjacent breath cycles is taken as a decision variable, and the bias minimization between the end-tidal anesthetic gas concentration prediction value and the end-tidal anesthetic gas concentration set value is taken as the target, to construct an anesthetic gas concentration optimization model, including: Step 3-1: taking the sum of the square of the weighted two-norm of the bias between the end-tidal anesthetic gas concentration set value and the end-tidal anesthetic gas concentration prediction value after bias correction and considering the influence of the change in the inhaled anesthetic gas concentration, and the square of the weighted two-norm of the inhaled anesthetic gas concentration change amount as the target, to construct an anesthetic gas concentration optimization objective function.

[0051] Step 3-2: taking the inhaled anesthetic gas concentration change amount satisfying the preset first value range as a constraint, to construct an anesthetic gas concentration optimization first constraint function; taking the end-tidal anesthetic gas concentration prediction value after bias correction and considering the influence of the change in the inhaled anesthetic gas concentration satisfying the preset second value range as a constraint, to construct an anesthetic gas concentration optimization second constraint function.

[0052] Step 3-3: based on the anesthetic gas concentration optimization objective function, the anesthetic gas concentration optimization first constraint function and the anesthetic gas concentration optimization second constraint function, to obtain an anesthetic gas concentration optimization model.

[0053] Specifically, the anesthetic gas concentration optimization objective function is expressed as: , , wherein, , represents a vector composed of the inhaled anesthetic gas concentration change amount of the current kth and future M-1 breath cycles, represents the inhaled anesthetic gas concentration change amount of the current kth breath cycle, represents the inhaled anesthetic gas concentration change amount of the future M-1 breath cycle; , represents a vector composed of the end-tidal anesthetic gas concentration set value of the current kth and future P-1 breath cycles, This represents the end-tidal anesthetic gas concentration setpoint for the current k-th respiratory cycle. Indicates the future number The setpoint for the end-tidal anesthetic gas concentration per respiratory cycle; ; , A weight matrix representing the deviation between the predicted and set values ​​of end-tidal anesthetic gas concentration; , Weight matrix representing the change in concentration of inhaled anesthetic gas; The first constraint function for optimizing anesthetic gas concentration is expressed as: , in, This represents the minimum value within the preset first range of values; This indicates the maximum value within the preset first value range; The second constraint function for optimizing anesthetic gas concentration is expressed as: , in, This represents the minimum value within the preset second range of values; This indicates the maximum value within the preset second value range.

[0054] The boundary values ​​of the preset first value range and the preset second value range are represented as follows: , , Specifically, the concentration of inhaled anesthetic gas in each respiratory cycle can be set with an upper and lower limit individually. For example, in the current k-th respiratory cycle, This refers to the upper and lower limits of the inhaled anesthetic gas concentration for that respiratory cycle. At the same time, for each respiratory cycle, in order to ensure that the inhaled anesthetic gas concentration for that respiratory cycle does not exceed the limit, it is necessary to combine the inhaled anesthetic gas concentration of the previous respiratory cycle to constrain the increase in the inhaled anesthetic gas concentration for that respiratory cycle.

[0055] Furthermore, after obtaining the concentration of inhaled anesthetic gas for each respiratory cycle, the compensation amount of anesthetic gas for each respiratory cycle is calculated based on the volume of the anesthetic respiratory system. Then, based on the compensation amount of anesthetic gas, the maximum concentration of anesthetic gas in fresh gas, and the set value of gas delivery time, the target flow rate of fresh gas during compensation in each respiratory cycle is calculated to control the delivery flow rate of the fresh gas delivery system.

[0056] Specifically, the formula for calculating the compensation amount of anesthetic gas is as follows: , in, a compensation amount of the anesthetic gas for the kth breathing cycle; a concentration change amount of the inhaled anesthetic gas for the kth breathing cycle; an anesthetic breathing system volume; A calculation formula of the target flow of the fresh gas when compensation is performed is: , wherein, a target flow of the fresh gas when compensation is performed for the kth breathing cycle; a maximum value of the anesthetic gas concentration of the fresh gas; a gas delivery time set value.

[0057] It should be noted that the gas delivery time set value is less than or equal to the expiratory time set value of the current breathing cycle, and only needs to control the fresh gas flow at the target flow within the gas delivery time set value (i.e. when compensation is performed), and when the actual gas delivery time exceeds the gas delivery time set value, the fresh gas flow is 0.

[0058] As Figure 3 shown is a control principle block diagram of the control device provided by the embodiment of the present application, including an upper end-expiratory anesthetic gas concentration controller and a lower fresh gas flow controller, wherein a channel characteristic between the end-expiratory anesthetic gas concentration and the fresh gas flow, a channel characteristic between the fresh gas flow and the control signal. In order to achieve target-controlled compensation of the end-expiratory anesthetic gas concentration, the end-expiratory anesthetic gas concentration controller guides the flow controller to control the flow of each delivery branch gas to which target value, and the flow controller controls the fresh gas flow and the anesthetic gas concentration in the fresh gas based on the guidance of the end-expiratory anesthetic gas concentration controller.

[0059] Based on the above-mentioned embodiment provided by the anesthesia machine end-expiratory anesthetic gas concentration automatic target control method, the embodiment of the present application further provides an anesthesia machine, as Figure 2 shown, the anesthesia machine specifically includes a control device 1, a fresh gas delivery system 2 and an anesthetic breathing system 3.

[0060] The control device 1 is coupled with the fresh gas delivery system 2 and the anesthetic breathing system 3, and is used to realize the steps of the above-mentioned anesthesia machine end-expiratory anesthetic gas concentration automatic target control method.

[0061] The fresh gas delivery system 2 is used to generate fresh gas with anesthetic gas and deliver it to the anesthetic breathing system 3 under the control of the control device 1.

[0062] The anaesthesia breathing system 3 is used to deliver fresh gas to the patient, to detect the end-tidal anaesthetic gas concentration and the inspired anaesthetic gas concentration of the patient in real time and to transmit them to the control device 1.

[0063] Those skilled in the art will appreciate that embodiments of the application can be supplied as methods, systems, or computer program products. Accordingly, the application can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the application can be embodied in the form of a computer program product on one or more computer readable storage media (including, but not limited to, disk memory, CD-ROMs, optical storage media, etc.) having computer usable program code embodied therein.

[0064] The present application is described in reference to the flowchart and / or block diagrams of the methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart and / or block diagrams, and combinations of blocks in the flowchart and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processing system or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0065] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0066] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0067] Obviously, the above embodiments are merely example for clearly illustrating, and are not limitation to the embodiments. Based on the above description, other different forms of changes or variations can be made by those skilled in the art. Here, all the embodiments are not required to be enumerated, and the obvious changes or variations derived from the above are still within the protection scope of the present application.

Claims

1. A method of automatically target controlling the end-tidal concentration of an anaesthetic gas from an anaesthesia machine, characterised in that, The control device applied to an anesthesia machine comprises: S10: Real-time acquisition of end-expiratory anesthetic gas concentration of a patient in a current breathing cycle, calculation of deviation of the end-expiratory anesthetic gas concentration from a set value of the end-expiratory anesthetic gas concentration; S20: If an absolute value of the deviation is greater than or equal to a preset deviation threshold value and / or an absolute value of a change amount of the end-expiratory anesthetic gas concentration is greater than or equal to a preset change amount threshold value, the flow of fresh gas used for flushing the anesthetic breathing system is increased, the anesthetic gas concentration of the fresh gas is adjusted, and the step S10 is executed until the absolute value of the deviation is less than the preset deviation threshold value and the absolute value of the change amount of the end-expiratory anesthetic gas concentration is less than the preset change amount threshold value; S30: Input of an actual value of the end-expiratory anesthetic gas concentration of a previous breathing cycle into an anesthetic gas concentration change kinetics model, and output of predicted values of the end-expiratory anesthetic gas concentration of the current and future breathing cycles; S40: Construction of an anesthetic gas concentration optimization model by taking the change amount of the inhaled anesthetic gas concentration of the current and future adjacent breathing cycles as decision variables and taking minimization of the deviation of the predicted values of the end-expiratory anesthetic gas concentration from the set value of the end-expiratory anesthetic gas concentration as a target; S50: Solution of the anesthetic gas concentration optimization model, obtaining of optimal change amounts of the inhaled anesthetic gas concentration of the current and future breathing cycles, and obtaining of anesthetic gas compensation amounts of the current and future breathing cycles and target flow of the fresh gas for compensation based on the optimal change amounts of the inhaled anesthetic gas concentration, a volume of the anesthetic breathing system, a maximum value of the anesthetic gas concentration of the fresh gas, and a gas delivery time set value, so as to control delivery parameters of the fresh gas.

2. The method of claim 1, wherein, The deviation includes an absolute deviation and a relative deviation; The absolute value of the deviation being greater than or equal to the preset deviation threshold value specifically refers to that an absolute value of the absolute deviation is greater than or equal to a preset absolute deviation threshold value / the absolute value of the absolute deviation is less than the preset absolute deviation threshold value and an absolute value of the relative deviation is greater than or equal to a preset relative deviation threshold value; The absolute value of the deviation being less than the preset deviation threshold value specifically refers to that the absolute value of the absolute deviation is less than the preset absolute deviation threshold value / the absolute value of the absolute deviation is greater than or equal to the preset absolute deviation threshold value and the absolute value of the relative deviation is less than the preset relative deviation threshold value.

3. The method of claim 1, wherein, The step S20 of adjusting the anesthetic gas concentration of the fresh gas comprises: Acquisition of the deviation of each breathing cycle up to the current breathing cycle, comparison of a minimum value in absolute values of the deviations of each breathing cycle with a preset minimum deviation value; If the minimum value is greater than or equal to the preset minimum deviation value, the anesthetic gas concentration of the fresh gas is kept unchanged; If the minimum value is less than the preset minimum deviation value, it is judged whether the current breathing cycle is the first breathing cycle with the absolute value of the deviation being less than a first preset threshold value; If the current breathing cycle is not the first breathing cycle with the absolute value of the deviation being less than the first preset threshold value, the anesthetic gas concentration of the fresh gas is kept unchanged; If the current breathing cycle is the first breathing cycle with the absolute value of the deviation being less than the first preset threshold value, the anesthetic gas concentration of the fresh gas is decreased when the deviation of the current breathing cycle is positive, and the anesthetic gas concentration of the fresh gas is increased when the deviation of the current breathing cycle is negative.

4. The automatic target control method for end-tidal anesthetic gas concentration in an anesthesia machine according to claim 3, characterized in that, The step S20 of adjusting the anesthetic gas concentration of the fresh gas further comprises: If the number of breath cycles in which the fresh gas anesthetic gas concentration is maintained is greater than or equal to the preset number of breath cycles in each breath cycle up to the current breath cycle, the fresh gas anesthetic gas concentration is adjusted; The adjustment formula of the fresh gas anesthetic gas concentration is: ， wherein denotes the fresh gas concentration of the anesthetic gas at the time instant; denotes the end-tidal anesthetic gas concentration set value at the time instant; denotes the end-tidal anesthetic gas concentration at the time instant; denotes a proportionality factor.

5. The method of claim 1, wherein, The construction process of the anesthetic gas concentration change dynamics model includes: The inhaled anesthetic gas concentration of each breath cycle up to the current breath cycle is obtained, the difference between the inhaled anesthetic gas concentration of each breath cycle and the inhaled anesthetic gas concentration of the previous breath cycle is calculated, and the inhaled anesthetic gas concentration change amount of each breath cycle is obtained; The correlation coefficient between the inhaled anesthetic gas concentration and the end-tidal anesthetic gas concentration is estimated based on the inhaled anesthetic gas concentration and the exhaled anesthetic gas concentration of each breath cycle by using the least square method, so as to obtain the relationship between the inhaled anesthetic gas concentration and the end-tidal anesthetic gas concentration; Based on the relationship between the inhaled anesthetic gas concentration and the end-tidal anesthetic gas concentration, the anesthetic gas concentration change dynamics model is constructed.

6. The method of claim 5, wherein the step of determining the target concentration of the end-tidal anesthetic gas comprises the step of: The relationship between the inhaled anesthetic gas concentration and the end-tidal anesthetic gas concentration is: ​ ， ， wherein, , denotes an end-tidal anesthetic gas concentration data vector composed of end-tidal anesthetic gas concentrations of respiratory cycles; denotes an end-tidal anesthetic gas concentration of the th respiratory cycle; an inhaled anesthetic gas concentration data matrix composed of inhaled anesthetic gas concentration change amounts of respiratory cycles; denotes an inhaled anesthetic gas concentration change amount of the th respiratory cycle; denotes a number of respiratory cycles required for an end-tidal anesthetic gas concentration change amount to be less than a preset change amount threshold when an inhaled anesthetic gas concentration is changed; , denotes a correlation coefficient, ; The anesthetic gas concentration change dynamics model is: ， ， ， wherein, represents the end-tidal anesthetic gas concentration prediction value at the current kth breath cycle, which is corrected for bias but does not take into account the effect of the change in inhaled anesthetic gas concentration for the current and future P-1 breath cycles; represents the end-tidal anesthetic gas concentration prediction value at the current k-1th breath cycle, which is corrected for bias and takes into account the effect of the change in inhaled anesthetic gas concentration for the current and future P-1 breath cycles; represents the end-tidal anesthetic gas concentration prediction value at the current k-1th breath cycle, which is corrected for bias but does not take into account the effect of the change in inhaled anesthetic gas concentration for the current and future P-1 breath cycles; represents the bias correction weight vector, which is used to weight the bias; represents the end-tidal anesthetic gas concentration prediction value at the current kth breath cycle, which is corrected for bias but does not take into account the effect of the change in inhaled anesthetic gas concentration for the current breath cycle; represents the end-tidal anesthetic gas concentration prediction value at the current kth breath cycle, which is corrected for bias but does not take into account the effect of the change in inhaled anesthetic gas concentration for the future P-1 breath cycle; represents the correlation coefficient vector estimate of inhaled anesthetic gas concentration and end-tidal anesthetic gas concentration, which is obtained using the inhaled anesthetic gas concentration and end-tidal anesthetic gas concentration of P breath cycles; represents the correlation coefficient vector estimate of inhaled anesthetic gas concentration and end-tidal anesthetic gas concentration, which is obtained using the inhaled anesthetic gas concentration and end-tidal anesthetic gas concentration of P breath cycles; , represents the bias of the end-tidal anesthetic gas concentration at the k-1th breath cycle and the end-tidal anesthetic gas concentration prediction value; represents the end-tidal anesthetic gas concentration at the k-1th breath cycle; represents the end-tidal anesthetic gas concentration prediction value at the k-1th breath cycle, which is corrected for bias and takes into account the effect of the change in inhaled anesthetic gas concentration.

7. The method of claim 6, wherein the step of determining the target concentration of the end-tidal anesthetic gas comprises the step of: The inhaled anesthetic gas concentration change amount of the adjacent breath cycle is taken as the decision variable, and the minimization of the deviation between the end-tidal anesthetic gas concentration prediction value and the set value is taken as the target, to construct the anesthetic gas concentration optimization model, including: ​ The sum of the square of the weighted two-norm of the deviation between the end-tidal anesthetic gas concentration set value and the end-tidal anesthetic gas concentration prediction value after the deviation correction and considering the influence of the inhaled anesthetic gas concentration change, and the square of the weighted two-norm of the inhaled anesthetic gas concentration change amount is taken as the target, to construct the anesthetic gas concentration optimization objective function; The inhaled anesthetic gas concentration change amount meets the preset first value range as the constraint, to construct the anesthetic gas concentration optimization first constraint function; the end-tidal anesthetic gas concentration prediction value after the deviation correction and considering the influence of the inhaled anesthetic gas concentration change meets the preset second value range as the constraint, to construct the anesthetic gas concentration optimization second constraint function; Based on the anesthetic gas concentration optimization objective function, the anesthetic gas concentration optimization first constraint function and the anesthetic gas concentration optimization second constraint function, the anesthetic gas concentration optimization model is obtained.

8. The method of claim 7, wherein the step of determining the target concentration of the end-tidal anesthetic gas comprises the step of: The anesthetic gas concentration optimization objective function is: ​ ， ， wherein, , represents a vector composed of the inhaled anesthetic gas concentration change amount of the current kth and future M-1th respiratory cycles, represents the inhaled anesthetic gas concentration change amount of the current kth respiratory cycle, represents the inhaled anesthetic gas concentration change amount of the future M-1th respiratory cycle; , represents a vector composed of the end-tidal anesthetic gas concentration set value of the current kth and future P-1th respiratory cycles, represents the end-tidal anesthetic gas concentration set value of the current kth respiratory cycle, represents the end-tidal anesthetic gas concentration set value of the future P-1th respiratory cycle; ; ; , represents a weight matrix of the deviation of the end-tidal anesthetic gas concentration predicted value from the set value; , represents a weight matrix of the inhaled anesthetic gas concentration change amount; The anesthetic gas concentration optimization first constraint function is: ， wherein, represents a minimum value of the preset first value range; represents a maximum value of the preset first value range; The anesthetic gas concentration optimization second constraint function is: ， wherein, represents a minimum value of the preset second value range; represents a maximum value of the preset second value range.

9. The method of claim 1, wherein, The calculation formula of the anesthetic gas compensation amount is: ， wherein, represents the amount of compensation of the anesthetic gas for the kth breathing cycle; represents the amount of change in the concentration of the inhaled anesthetic gas for the kth breathing cycle; represents the volume of the anesthetic breathing system; The calculation formula of the target flow of the fresh gas when compensation is performed is: ， wherein, represents a target flow rate of fresh gas when the kth respiratory cycle is compensated for; represents a maximum value of anesthetic gas concentration of fresh gas; represents a gas delivery time set value.

10. An anaesthesia machine characterised in that, It includes: A fresh gas delivery system for generating fresh gas with anesthetic gas under the control of the control device and delivering to the anesthetic breathing system; An anesthetic breathing system for delivering fresh gas to a patient, real-time detecting the end-tidal anesthetic gas concentration and the inhaled anesthetic gas concentration of the patient and transmitting to the control device; A control device coupled with the fresh gas delivery system and the anesthetic breathing system, for realizing the steps of the end-tidal anesthetic gas concentration automatic target control method of the anesthetic machine according to any one of claims 1 to 9.

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