Anaesthesia machine and state recognition method for driving gas of anaesthesia machine

Abstract

The invention provides an anaesthesia machine and a state recognition method for driving gas of the anaesthesia machine. The anaesthesia machine comprises a breathing loop used for being connected with a patient, a driving gas branch used for providing driving gas for a bellow-free gas driving branch, and the bellow-free gas driving branch with a bellow-free gas driver. The bellow-free gas driver is used for storing driving gas in the inspiration stage and storing gas of the breathing circuit in the expiration stage. The anaesthesia machine obtains the first gas amount flowing into the breathing circuit through the bellows-free gas driver in the inspiration stage and the second gas amount of gas entering the bellows-free gas driver in the breathing circuit in the expiration stage; and determining whether the state of the current driving gas is that the driving gas enters the breathing loop according to the first gas quantity and the second gas quantity. Therefore, a user can know the current state of the driving gas, and the risk that the anesthetic concentration of a breathing circuit is too low is reduced.

Description

Technical Field

[0001] The present invention relates to the field of medical devices, and particularly to an anesthesia machine and a method for identifying the state of its driving gas. Background Art

[0002] Traditional anesthesia machines use a bellows structure to ventilate patients. As shown in Figure 1 , by using a driving gas, the gas in the bellows folding bladder can be pushed into the patient's breathing circuit to complete the breathing process. With the development of technology, it is becoming more and more common to use a volume reflector structure with a spiral-shaped slender pipeline structure instead of the bellows structure for ventilation. Compared with the traditional bellows, the volume reflector removes the folding bladder that isolates the driving gas from the gas in the patient's breathing circuit. Therefore, there is no risk of multiple squeezing and damage of the folding bladder. In addition, without the volume limit of the folding bladder, the volume reflector structure can also achieve a larger tidal volume control range.

[0003] When using an anesthesia machine with a volume reflector for ventilation, during the exhalation phase, the volume reflector receives the patient's exhaled gas, and during the inhalation phase, the driving gas pushes the exhaled gas in the volume reflector back into the breathing circuit, repeating this cycle. During the breathing process, the driving gas is in direct contact with the circuit gas entering the volume reflector. Under the action of gas molecule diffusion, the driving gas and the circuit gas will mix with each other. The driving gas type is oxygen or air without anesthetic, while the circuit exhaled gas usually contains anesthetic gas. When the fresh gas flow rate set by the anesthesia machine flowmeter is not sufficient to make up for the gas consumed by the patient or the gas leaked from the circuit, the mixed gas containing the driving gas will enter the breathing circuit, resulting in the patient receiving a lower anesthetic concentration than expected, and there is a risk of insufficient anesthesia and intraoperative awakening. Summary of the Invention

[0004] The present invention mainly provides an anesthesia machine and a method for identifying the state of its driving gas, aiming to reduce the risk of too low anesthetic concentration in the breathing circuit.

[0005] An embodiment provides an anesthesia machine, including:

[0006] A breathing circuit for connecting to a patient;

[0007] A driving gas branch for providing driving gas for the gas driving branch without a bellows;

[0008] A fresh gas branch for providing fresh gas for the breathing circuit;

[0009] A gas discharge branch for discharging excess gas during the exhalation phase;

[0010] The bellowsless gas driving branch includes a bellowsless gas driver, which is used to store driving gas during the inhalation phase and store the gas in the breathing circuit during the exhalation phase;

[0011] The output end of the driving gas branch is connected to the input end of the gas discharge branch and one end of the bellowsless gas driving branch. The other end of the bellowsless gas driving branch is connected to the first end of the breathing circuit. The fresh gas branch is connected to the second end of the breathing circuit. The third end of the breathing circuit is used to connect to a patient;

[0012] A processing module, configured to:

[0013] Obtain a first gas volume flowing into the breathing circuit through the bellowsless gas driver during the inhalation phase and a second gas volume of the gas in the breathing circuit entering the bellowsless gas driver during the exhalation phase; and

[0014] Determine whether the current state of the driving gas is that the driving gas enters the breathing circuit according to the first gas volume and the second gas volume.

[0015] In an anesthetic machine provided by an embodiment, the processing module determines whether the current state of the driving gas is that the driving gas enters the breathing circuit according to the first gas volume and the second gas volume, including:

[0016] Calculate the difference between the first gas volume and the second gas volume, and compare the difference with a preset threshold; when the difference is greater than the preset threshold, determine that the current state of the driving gas is that the driving gas enters the breathing circuit.

[0017] In an anesthetic machine provided by an embodiment, the anesthetic machine further includes a detection module for detecting at least two gas parameters, and the at least two gas parameters include at least two of driving gas flow rate, fresh gas flow rate, inhalation flow rate in the breathing circuit, exhalation flow rate in the breathing circuit, and pressure when the gas discharge branch discharges gas;

[0018] The processing module is further configured to: input the at least two gas parameters into a pre-trained deep learning model to obtain a result output by the deep learning model;

[0019] The result output by the deep learning model is a third gas volume of the driving gas entering the breathing circuit or a fresh gas recommended amount of the fresh gas branch.

[0020] In an anesthesia machine provided by an embodiment, the processing module is further configured to obtain the variation trend of the anesthetic concentration or the variation trend of the oxygen concentration; and when the variation trend of the anesthetic concentration is a decrease in the anesthetic concentration, determine that the state of the current driving gas is: the driving gas enters the breathing circuit; or, when the variation trend of the oxygen concentration is an increase in the oxygen concentration, determine that the state of the current driving gas is: the driving gas enters the breathing circuit.

[0021] An embodiment provides a method for identifying the state of the driving gas of an anesthesia machine, the anesthesia machine including: a breathing circuit for connecting a patient, a driving gas branch for providing driving gas for a bellows-free gas driving branch, and a bellows-free gas driving branch having a bellows-free gas driver; the bellows-free gas driver is configured to store the driving gas in the inhalation phase and store the gas in the breathing circuit in the exhalation phase; the method includes:

[0022] Obtaining a first gas volume flowing from the bellows-free gas driver into the breathing circuit during the inhalation phase and a second gas volume of the gas in the breathing circuit entering the bellows-free gas driver during the exhalation phase;

[0023] Determining whether the state of the current driving gas is: the driving gas enters the breathing circuit according to the first gas volume and the second gas volume;

[0024] If so, output the state of the current driving gas.

[0025] According to the anesthesia machine and the method for identifying the state of the driving gas according to the above embodiments, the anesthesia machine obtains a first gas volume flowing from the bellows-free gas driver into the breathing circuit during the inhalation phase and a second gas volume of the gas in the breathing circuit entering the bellows-free gas driver during the exhalation phase; and then determines whether the state of the current driving gas is: the driving gas enters the breathing circuit according to the first gas volume and the second gas volume. In this way, the user can know the state of the current driving gas, thereby reducing the risk of too low anesthetic concentration in the breathing circuit. Description of the Drawings

[0026] Figure 1 Schematic diagram of the working principle of the bellows in an anesthesia machine in the prior art;

[0027] Figure 2 Structural block diagram of an embodiment of the anesthesia machine provided by the present invention;

[0028] Figure 3 Flowchart of an embodiment of the method for identifying the state of the driving gas provided by the present invention;

[0029] Figure 4 Schematic diagram of an embodiment of the positions of the first sensor and the second sensor;

[0030] Figure 5Schematic diagram of another embodiment of the positions of the first sensor and the second sensor;

[0031] Figure 6 Schematic diagram of an embodiment of the position of the third sensor;

[0032] Figure 7 Schematic diagram of another embodiment of the position of the third sensor;

[0033] Figure 8 Schematic diagram of the positions of five sensors for detecting gas parameters;

[0034] Figure 9 Schematic diagram of an embodiment of the position of the fourth sensor;

[0035] Figure 10 Schematic diagram of another embodiment of the position of the fourth sensor. Detailed implementation manners

[0036] The present invention will be further described in detail below in conjunction with the accompanying drawings through specific implementation manners. Similar elements in different implementation manners are labeled with related similar element numbers. In the following implementation manners, many detailed descriptions are provided to enable a better understanding of the present application. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, or methods. In some cases, some operations related to the present application are not shown or described in the specification, which is to avoid overwhelming the core part of the present application with excessive descriptions. For those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the descriptions in the specification and the general technical knowledge in the art.

[0037] In addition, the features, operations, or characteristics described in the specification can be combined in any appropriate manner to form various implementation manners. At the same time, the steps or actions in the method descriptions can also be reordered or adjusted in an obvious manner by those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for clearly describing a certain embodiment and do not mean a necessary sequence, unless it is stated that a certain sequence must be followed.

[0038] The serial numbers assigned to the components herein, such as "first", "second", etc., are only used to distinguish the described objects and do not have any sequential or technical meaning. And the "connection" and "coupling" mentioned in the present application, unless otherwise specified, both include direct and indirect connection (coupling).

[0039] When ventilating with an anesthesia machine system having a volume reflector, different amounts or concentrations of gas entering and exiting the volume reflector can affect the state of the breathing circuit. In the present invention, a gas sensor in the anesthesia machine monitors the amount or concentration of gas entering and exiting the volume reflector during inhalation and exhalation to identify whether the current mixed gas enters the breathing circuit or whether there is excess anesthetic gas discharged into the atmosphere. This will be illustrated by some embodiments below.

[0040] As Figure 2 shown, the anesthesia machine provided by the present invention includes a processing module 10, a driving gas branch 20, a breathing circuit 40, a gas discharge branch 50, and a fresh gas branch 60.

[0041] The driving gas branch 20 is used to provide driving gas for the bellows-free gas driving branch 30. In some embodiments, the anesthesia machine may further include a bellows-free gas driving branch 30. The driving gas can be oxygen, air, an oxygen-air mixture, etc. The driving gas branch 20 may include a driving gas interface 210 for connecting to a driving gas source. The driving gas source is used to provide the driving gas, which can be a hospital gas pipeline, a gas cylinder, a compressor, etc.

[0042] The breathing circuit 40 is used to connect to a patient.

[0043] The fresh gas branch 60 is used to provide fresh gas for the breathing circuit 40. The fresh gas may include at least one of air, oxygen, and nitrous oxide. The fresh gas branch 60 may further include a flow meter. The fresh gas branch 60 is connected to an evaporation canister, and the fresh gas is converted into fresh gas with anesthetic drugs for the breathing circuit 40 after passing through the evaporation canister.

[0044] The gas discharge branch 50 is used to discharge excess gas during the exhalation phase, and it may include an exhalation valve. During the exhalation phase, the excess gas is discharged by the exhalation valve.

[0045] The bellows-free gas driving branch 30 includes a bellows-free gas driver 310. The bellows-free gas driver 310 is used to store at least the driving gas during the inhalation phase and at least the gas in the breathing circuit 40 during the exhalation phase. The bellows-free gas driver 310 is used to replace the function of a traditional bellows, and it can adopt a volume reflector. The volume reflector can be a slender pipeline. To save space, the slender pipeline can be bent into various shapes, such as a disk shape. The slender pipeline is used to prevent the driving gas from entering the breathing circuit 40 as much as possible.

[0046] The output end of the driving gas branch 20 is connected to the input end of the gas discharge branch 50 and one end of the non-bellows gas driving branch 30. The other end of the non-bellows gas driving branch 30 is connected to the first end 1 of the breathing circuit 40. The fresh gas branch 60 is connected to the second end 2 of the breathing circuit 40. The third end 3 of the breathing circuit 40 is used to connect to a patient.

[0047] In this embodiment, the breathing circuit 40 may include an inhalation branch 410 and an exhalation branch 420. One end of the inhalation branch 410 is the second end 2 of the breathing circuit 40 and is connected to the fresh gas branch 60. The other end of the inhalation branch 410 is the third end 3 of the breathing circuit 40 and is connected to the patient. One end of the exhalation branch 420 is the first end 1 of the breathing circuit 40 and is connected to the non-bellows gas driver 310. The other end of the exhalation branch 420 is the third end 3 of the breathing circuit 40 and is connected to the patient. The fresh gas provided by the fresh gas branch 60 is delivered to the patient through the inhalation branch 410. One end of the exhalation branch 420 may also be connected to one end of the inhalation branch 410 through the absorption device 70. The absorption device 70 is used to absorb carbon dioxide and may employ a carbon dioxide absorption canister. The gas exhaled by the patient enters the non-bellows gas driver 310 and the absorption device 70 through the exhalation branch 420.

[0048] The anesthesia machine may further include a man-machine interaction device 80. The man-machine interaction device 80 is used for man-machine interaction, such as outputting visual information and receiving user input. The man-machine interaction device 80 includes an input device and may also include a display. The input device is used to receive user input and may employ a keyboard, operation buttons, mouse, trackball, touchpad, etc., or may also employ a touch screen integrated with the display.

[0049] The processing module 10 is used to control the anesthesia machine to implement various functions of the anesthesia machine. For example, in the inhalation phase, the processing module 10 controls the fresh gas branch 60 to provide fresh gas to the inhalation branch 410; it also controls the driving gas branch 20 to provide driving gas to the non-bellows gas driver 310, so that at least part of the gas in the non-bellows gas driver 310 enters the inhalation branch 410. The gas in the non-bellows gas driver 310 that enters the inhalation branch 410 is preferably the gas that enters the non-bellows gas driver 310 from the exhalation branch 420 during the exhalation phase, that is, preferably no driving gas enters the inhalation branch 410. In the exhalation phase, the processing module 10 controls the driving gas branch 20 to stop providing driving gas or reduce the amount of driving gas output, so that part of the gas in the exhalation branch 420 enters the non-bellows gas driver 310, thereby pushing at least part of the gas in the non-bellows gas driver 310 to be discharged to the atmosphere through the exhalation valve. The processing module 10 may employ a device with arithmetic processing capabilities such as a processor.

[0050] Of course, the processing module 10 is also capable of identifying the state of the driving gas. The specific process is as Figure 3 shown, including the following steps:

[0051] Step 1: The processing module 10 obtains the first gas volume flowing into the breathing circuit 40 through the non-bellows gas driver 310 during the inhalation phase and the second gas volume of the gas in the breathing circuit 40 entering the non-bellows gas driver 310 during the exhalation phase. Here, the inhalation phase and the exhalation phase can be in the same breathing cycle or in different breathing cycles. For example, the second gas volume is obtained during the exhalation phase of the previous breathing cycle, and the first gas volume is obtained during the inhalation phase of the current breathing cycle.

[0052] The anesthesia machine may further include a detection module. The detection module is used to detect or assist in detecting the first gas volume and is used to detect or assist in detecting the second gas volume. There are various forms of the detection module for detecting these two gas volumes, mainly due to the different numbers and installation positions of the sensors. Examples are given below respectively.

[0053] In the first method, as Figure 4 and 5 shown, the detection module may include a first sensor 910 and a second sensor 920. The first sensor 910 is arranged in the driving gas branch 20. The driving gas interface 210 can be connected to one end of the non-bellows gas driver 310 and the gas discharge branch 50 through the first sensor 910, that is, the first sensor 910 is located at the rear end of the driving gas interface 210. The second sensor 920 is arranged in the gas discharge branch 50. As Figure 4 shown, the second sensor 920 can be located at the rear end of the expiratory valve; as Figure 5 shown, the second sensor 920 can also be located at the front end of the expiratory valve.

[0054] During the inhalation phase, the processing module 10 can subtract the flow rate detected by the second sensor 920 from the flow rate detected by the first sensor 910 to obtain the first gas volume Vr1. The flow rate detected by the second sensor 920 during the exhalation phase is the second gas volume Vr2. The processing module 10 can obtain the second gas volume Vr2 by acquiring the flow rate detected by the second sensor 920 during the exhalation phase.

[0055] In the second method, as Figure 6 and 7As shown, the detection module may include a third sensor 930. The third sensor 930 may be disposed in the bellows-free gas drive branch 30. The flow rate detected by the third sensor 930 during the inhalation phase is the first gas volume Vr1, and the flow rate detected by the third sensor 930 during the exhalation phase is the second gas volume Vr2. That is, the processing module 10 obtains the flow rate detected by the third sensor 930 during the inhalation phase as the first gas volume Vr1, and obtains the flow rate detected by the third sensor 930 during the exhalation phase as the second gas volume Vr2.

[0056] As Figure 6 shown, the third sensor 930 may be located at the front end of the bellows-free gas driver 310; as Figure 7 shown, the third sensor 930 may also be located at the rear end of the bellows-free gas driver 310.

[0057] The first gas volume Vr1 and the second gas volume Vr2 may be flow rate, flow velocity, volume, or the gas volume accumulated by the flow velocity, etc., as long as they can reflect the amount of gas. In fact, the flow rate, volume, flow velocity, and the gas volume accumulated by the flow velocity can be converted into each other, and essentially belong to a kind of parameter. In this embodiment, the flow rate is taken as an example for illustration. Correspondingly, the first sensor 910, the second sensor 920, and the third sensor 930 may all be flow sensors.

[0058] In the third method, the detection module included in the anesthesia machine is used to detect at least two gas parameters. The at least two gas parameters include at least two of the driving gas flow rate, fresh gas flow rate, inhalation flow rate in the breathing circuit, exhalation flow rate in the breathing circuit, and pressure when the gas discharge branch discharges gas.

[0059] As Figure 8As shown, the detection module may include at least two of a driving gas sensor 940, a fresh gas sensor 960, an inhalation sensor 980, an exhalation sensor 970, and a pressure sensor 950. Among them, the driving gas sensor 940 is arranged in the driving gas branch 20 and is used to detect the flow rate of the driving gas. For example, the driving gas sensor 940 is a driving gas flow sensor, and the processing module 10 can detect the driving gas flow rate through it. The driving gas flow sensor can be connected in series between the driving gas interface 20 and the bellowsless gas driver 30. The driving gas flow sensor can be the aforementioned first sensor. The fresh gas sensor 960 is arranged in the fresh gas branch 60 and is used to detect the flow rate of the fresh gas. The inhalation sensor 980 is arranged in the inhalation branch 410 and is used to detect the inhalation flow rate of the breathing circuit during the inhalation phase. The inhalation sensor 980 can be an inhalation flow sensor, and the processing module 10 can detect the inhalation flow rate in the inhalation branch 410 through it. The exhalation sensor 970 is arranged in the exhalation branch 420 and is used to detect the exhalation flow rate of the breathing circuit during the exhalation phase. The exhalation sensor 970 can be an exhalation flow sensor, and the processing module 10 can detect the exhalation flow rate in the exhalation branch 420 through it. The pressure sensor 950 is arranged in the gas discharge branch 50 and is used to detect the pressure when the gas discharge branch discharges gas. The processing module 10 detects the pressure when the gas discharge branch 50 discharges gas through the pressure sensor 950 arranged in the gas discharge branch 50, and the pressure sensor 950 can be arranged at the outlet end of the exhalation valve. The pressure sensor 950 can be the sealing pressure sensor of the exhalation valve.

[0060] The processing module 10 calculates, based on the at least two gas parameters, a first gas volume Vr1 flowing into the breathing circuit through the bellowsless gas driver 310 during the inhalation phase and a second gas volume Vr2 of the gas in the breathing circuit entering the bellowsless gas driver 310 during the exhalation phase. The more gas parameters are included, the easier it is to calculate the two gas volumes. The calculation methods can be various. For example, the processing module 10 inputs the at least two gas parameters into a pre-trained deep learning model to obtain the first gas volume Vr1 and the second gas volume Vr2 output by the deep learning model. The deep learning model can adopt a neural network. The at least two gas parameters serve as the input parameters of the neural network. The neural network can adopt a network structure with three to multiple (more than 3) layers. Through forward propagation, after the input gas parameters pass through the input layer, the hidden layer, and the output layer, the first gas volume Vr1 and the second gas volume Vr2 are obtained. Of course, the deep learning model can also obtain only the first gas volume Vr1 based on the at least two gas parameters, and the second gas volume Vr2 is obtained through the first method or the second method described above. The deep learning model can also obtain only the second gas volume Vr2 based on the at least two gas parameters, and the first gas volume Vr1 is obtained through the first method or the second method described above.

[0061] Step 2: The processing module 10 determines the state of the current driving gas according to the first gas volume Vr1 and the second gas volume Vr2. The state of the driving gas is usually divided into two types. One is that the driving gas enters the breathing circuit 40, and the other is that the driving gas does not enter the breathing circuit 40. Specifically, the processing module 10 determines whether the state of the current driving gas is that the driving gas enters the breathing circuit 40 according to the first gas volume Vr1 and the second gas volume Vr2. For example, the processing module 10 calculates the difference (Vr1 - Vr2) between the first gas volume Vr1 and the second gas volume Vr2, and compares the size of this difference with a preset threshold value Vo. When the difference is greater than the preset threshold value Vo (Vr1 - Vr2 > Vo), the processing module 10 determines that the state of the current driving gas is that the driving gas enters the breathing circuit 40. The preset threshold value Vo can be set as needed, and it is less than or equal to 0, usually less than 0. That is, when Vr1 - Vr2 > Vo, the fresh gas volume provided by the current fresh gas branch 60 is not enough to make up for the leakage volume of the breathing circuit 40 and the consumption of the patient, and the current breathing circuit 40 has gas mixing. Usually, the driving gas has an amount of |V r1 -V r2 -V0| enters the breathing circuit 40 through the volume reflector, reducing the anesthetic concentration or oxygen concentration at the patient end. The processing module 10 is also used to determine that the state of the current driving gas is that the driving gas does not enter the breathing circuit 40 when the difference is less than the preset threshold value (Vr1 - Vr2 < Vo). That is, when Vr1 - Vr2 < Vo, the fresh gas volume provided by the current fresh gas branch 60 is greater than the circuit leakage volume and the consumption of the patient, and the driving gas does not enter the breathing circuit 40. The gas volume discharged by the gas discharge branch 50 during the exhalation phase is the absolute value of the difference between this difference and the preset threshold value Vo. That is, in this state, there is an amount of |V r1 -V r2 -V0| of gas discharged to the atmosphere through the expiratory valve.

[0062] Step 3: The processing module 10 outputs the state of the current driving gas. For example, the processing module 10 can output the state of the current driving gas to an external device, or display the state of the current driving gas through the human-machine interaction device 80. At least when the state of the current driving gas is that the driving gas enters the breathing circuit 40, it is displayed on the display interface of the human-machine interaction device 80, thereby reminding the user to process it and reducing the risk of too low anesthetic concentration in the breathing circuit. Specifically, the state that the driving gas enters the breathing circuit 40 can be directly displayed, or the user can be prompted in the form of an alarm that the state of the current driving gas is that the driving gas enters the breathing circuit 40.

[0063] When the current state of the driving gas is such that when the driving gas enters the breathing circuit 40, the processing module 10 can also calculate the recommended fresh gas volume of the fresh gas branch 60 based on the difference (Vr1 - Vr2) and the preset threshold Vo. The recommended fresh gas volume is the fresh gas volume that ensures that the driving gas does not enter the breathing circuit 40. Furthermore, the recommended fresh gas volume can be output, for example, by displaying the recommended fresh gas volume on the display interface of the human-machine interaction device 80. The user can set the fresh gas flow rate or velocity according to this recommended fresh gas volume, which can ensure that the driving gas does not enter the breathing circuit 40. Of course, the processing module 10 can also automatically adjust the fresh gas flow rate according to this recommended fresh gas volume. In this way, a solution after the driving gas enters the breathing circuit 40 is given automatically or semi-automatically, improving the work efficiency of the user and ensuring the safety of patient anesthesia.

[0064] Specifically, the processing module 10 can calculate the recommended fresh gas volume Vfgr according to the following formula:

[0065] Vfgr = |V r1 - V r2 - V0| + Vfgs;

[0066] Wherein, Vfgs is the fresh gas volume provided by the current fresh gas branch 60. It can be the set value of the flowmeter in the current fresh gas branch 60 or the detected value of the flowmeter in the current fresh gas branch 60. In short, it can reflect the flow rate of the fresh gas provided by the current fresh gas branch 60.

[0067] Reducing the driving gas flow rate can also prevent the driving gas from entering the breathing circuit. However, reducing the driving gas flow rate will reduce the ventilation volume, and the stability of the ventilation volume is more important. Therefore, the driving gas flow rate is usually not adjusted to prevent the driving gas from entering the breathing circuit.

[0068] Increasing the fresh gas flow rate can prevent the driving gas from entering the breathing circuit. That is to say, for the problems mentioned in the background art, if the fresh gas flow rate (flow) set by the anesthetic machine flowmeter always exceeds the amount required to supplement the circuit, then the driving gas will not enter the breathing circuit. However, this will result in the emission of excess anesthetic gas into the atmosphere, causing pollution in the operating room and wasting anesthetics. Therefore, the industry usually does not do this. In other words, the industry always hopes that the fresh gas flow rate can be just right. However, in actual application, this "just right" situation will inevitably change from sufficient to insufficient fresh gas due to various circumstances, resulting in the driving gas entering the breathing circuit and reducing the anesthetic concentration. Through the above technical solutions, the user can safely set a "just right" fresh gas flow rate. The present invention can automatically prompt the user whether the current driving gas has entered the breathing circuit. If so, the user can increase the fresh gas flow rate, which will neither cause waste of anesthetics nor affect the safety of the anesthesia process.

[0069] In order to prompt the user whether the current driving gas has entered the breathing circuit, the method adopted in the foregoing embodiment is to obtain the first gas volume Vr1 and the second gas volume Vr2, and then judge the state of the current driving gas. Of course, there are other methods that can also prompt the user of the risk of the driving gas entering the breathing circuit, which will be described below through several embodiments.

[0070] An anesthetic machine provided in an embodiment also includes as Figure 2 shown: a processing module 10, the driving gas branch 20 as described above, the breathing circuit 40 as described above, the gas discharge branch 50 as described above, the fresh gas branch 60 as described above, the man-machine interaction device 80 as described above, and a detection module. The main difference between this embodiment and some of the foregoing embodiments lies in the functions of the detection module and the processing module 10.

[0071] As Figure 8As shown, the detection module of this embodiment is used to detect at least two gas parameters. The at least two gas parameters include at least two of: the driving gas flow rate, the fresh gas flow rate, the inhalation flow rate in the breathing circuit, the exhalation flow rate in the breathing circuit, and the pressure when the gas discharge branch discharges gas. Similarly, the detection module may include at least two of: the driving gas sensor 940, the fresh gas sensor 960, the inhalation sensor 980, the exhalation sensor 970, and the pressure sensor 950. Among them, the driving gas sensor 940 is arranged in the driving gas branch 20 and is used to detect the flow rate of the driving gas. The fresh gas sensor 960 is arranged in the fresh gas branch 60 and is used to detect the flow rate of the fresh gas. The inhalation sensor 980 is arranged in the inhalation branch 410 and is used to detect the inhalation flow rate of the breathing circuit during the inhalation phase. The exhalation sensor 970 is arranged in the exhalation branch 420 and is used to detect the exhalation flow rate of the breathing circuit during the exhalation phase. The pressure sensor 950 is arranged in the gas discharge branch 50 and is used to detect the pressure when the gas discharge branch discharges gas. The specific setting positions and types of each sensor are mentioned in the foregoing embodiments and will not be elaborated here.

[0072] The processing module 10 inputs at least two gas parameters into a pre-trained deep learning model to obtain the result output by the deep learning model. The result output by the deep learning model includes: whether the current state of the driving gas is the result of the driving gas entering the breathing circuit. There is a function between at least two gas parameters and the state of the driving gas trained in the deep learning model, and inputting at least two gas parameters into the model can obtain the state of the driving gas. First training data can be prepared in advance. The first training data includes at least two of the above 5 gas parameters, and the state of the driving gas corresponding to these gas parameters. Using these first training data to train the deep learning model can obtain a model that can automatically distinguish the state of the driving gas. The processing module 10 outputs whether the current state of the driving gas is the result of the driving gas entering the breathing circuit, that is, outputs the current state of the driving gas, which is the same as the above step 3 and will not be elaborated here.

[0073] Of course, in some embodiments, the result output by the deep learning model may also be the third gas volume for driving the gas into the breathing circuit. If the third gas volume is 0 or negative, it indicates that no driving gas enters the breathing circuit. If the third gas volume is positive, it indicates that the driving gas enters the breathing circuit. Therefore, this method can also prompt the user about the current state of the driving gas. Moreover, when the driving gas enters the breathing circuit, the user can also know exactly how much gas volume enters the breathing circuit, which is convenient for the user to calculate how much the fresh gas flow rate needs to be increased. For example, increasing the current fresh gas flow rate by the third gas volume can make the driving gas in the breathing circuit become 0. There is a function between at least two gas parameters trained in the deep learning model and the third gas volume for driving the gas into the breathing circuit. By inputting at least two gas parameters into the model, the third gas volume for driving the gas into the breathing circuit can be obtained. Second training data can be prepared in advance. The second training data includes at least two of the above five gas parameters and the corresponding third gas volume under these gas parameters. By training the deep learning model with this second training data, a model capable of automatically calculating the third gas volume can be obtained. The processing module 10 outputs the third gas volume. For example, the third gas volume is displayed on the display interface of the human-machine interaction device. In this embodiment, the at least two gas parameters include at least two of the driving gas flow rate, the fresh gas flow rate, the inhalation flow rate in the breathing circuit, and the exhalation flow rate in the breathing circuit, that is, it does not include the pressure when the gas is discharged through the gas discharge branch. In this way, there is no need to set the pressure sensor 950, and Figure 8 the other four sensors are usually available in an anesthesia machine, so there is no need to modify the hardware of the anesthesia machine.

[0074] In still other embodiments, the result output by the deep learning model may also be the recommended fresh gas volume of the fresh gas branch. If the recommended fresh gas volume is not higher than the set value of the current fresh gas flow rate, it indicates that no driving gas enters the breathing circuit. If the recommended fresh gas volume is higher than the set value of the current fresh gas flow rate, it indicates that the driving gas enters the breathing circuit. Therefore, this method can also prompt the user of the current state of the driving gas. And when the driving gas enters the breathing circuit, the user can also know how to specifically modify the set value of the fresh gas flow rate, that is, use the recommended fresh gas volume as the new set value of the fresh gas flow rate, so that the anesthesia machine can return to the normal state, that is, the state where the driving gas does not enter the breathing circuit. There is a function between at least two gas parameters trained in the deep learning model and the recommended fresh gas volume of the fresh gas branch. Inputting at least two gas parameters into the model can obtain the recommended fresh gas volume of the fresh gas branch. Third training data can be prepared in advance. The third training data includes at least two of the above 5 gas parameters and the corresponding recommended fresh gas volume under these gas parameters. Training the deep learning model with this third training data can obtain a model that can automatically calculate the recommended fresh gas volume. The processing module 10 outputs the recommended fresh gas volume. For example, the recommended fresh gas volume is displayed on the display interface of the human-machine interaction device.

[0075] The above deep learning model can also adopt a neural network. The at least two gas parameters serve as the input parameters of the neural network. The neural network can adopt a network structure of three layers to multiple layers (more than 3). Using forward propagation, after the input gas parameters pass through the input layer, hidden layer, and output layer, the result is obtained and output.

[0076] In the foregoing embodiments, the state of the driving gas is determined either by the first gas volume and the second gas volume or by the deep learning model. The present invention also provides an embodiment in which the state of the driving gas is determined by the change trend of the anesthetic concentration and / or the change trend of the oxygen concentration. The difference from the foregoing embodiments also lies in the detection module and the processing module 10. Therefore, the functions of these two modules will be described in detail.

[0077] In this embodiment, the detection module is used to detect the anesthetic concentration or the oxygen concentration, specifically to detect the anesthetic concentration or the oxygen concentration in the gas discharge branch 50, the gas driving branch 30 without a bellows, or the breathing circuit 40. There are various specific implementation manners, and several examples will be given below for illustration.

[0078] As Figure 9 and 10 shown, the detection module includes a fourth sensor 981. The fourth sensor 981 is used to detect the anesthetic concentration or the oxygen concentration.

[0079] As Figure 9As shown, the fourth sensor 981 can be disposed in the gas discharge branch 50, for example, at the front end or the rear end of the expiratory valve.

[0080] As Figure 10 shown, the fourth sensor 981 can also be disposed in the bellows-free gas driving branch 30, for example, at the front end or the rear end of the bellows-free gas driver.

[0081] The detection module may also include a fifth sensor (not shown in the figure), and the fifth sensor is also used to detect the anesthetic concentration or the oxygen concentration. The fifth sensor is disposed in the breathing circuit 40, for example, in the inhalation branch or the exhalation branch.

[0082] The processing module 10 is configured to obtain the change trend of the anesthetic concentration or the oxygen concentration; for example, obtain the anesthetic concentration or the oxygen concentration detected by the detection module, and obtain the change trend of the anesthetic concentration or the oxygen concentration according to the anesthetic concentration or the oxygen concentration at different times; specifically, if the current anesthetic concentration or oxygen concentration is C[1], after n (n≥1) breathing cycles, the measured anesthetic concentration or oxygen concentration is C[n + 1], if C[n + 1] - C[1] < 0, or C[n + 1] = 0, it is considered that the anesthetic concentration decreases. Of course, the sampling moments of the anesthetic concentration or the oxygen concentration can be more than two, so as to better determine the change trend of the anesthetic concentration or the oxygen concentration.

[0083] When the change trend of the anesthetic concentration is a decrease in the anesthetic concentration, the processing module 10 can determine the state of the current driving gas as: the driving gas enters the breathing circuit; when the change trend of the oxygen concentration is an increase in the oxygen concentration, the processing module 10 can also determine the state of the current driving gas as: the driving gas enters the breathing circuit. In the gas discharge branch 50, the bellows-free gas driving branch 30 and the breathing circuit 40, a decrease in the anesthetic concentration means an increase in the oxygen concentration, and the two are actually two sides of the same coin. Correspondingly, when the change trend of the anesthetic concentration is an increase in the anesthetic concentration, the processing module 10 can determine the state of the current driving gas as: the driving gas does not enter the breathing circuit; when the change trend of the oxygen concentration is a decrease in the oxygen concentration, the processing module 10 can also determine the state of the current driving gas as: the driving gas does not enter the breathing circuit. Similarly, the processing module 10 can output the state of the current driving gas, which is the same as the above step 3, and will not be elaborated here.

[0084] Of course, in some other embodiments, the processing module 10 may have all the functions of the processing module in each of the above embodiments. That is, the processing module 10 can determine the state of the current driving gas through the first and second gas amounts, can also determine the state of the current driving gas through a deep learning model, and can also determine the state of the current driving gas through the change trend of the anesthetic or oxygen concentration. It can finally output the state of the current driving gas only when the states of the driving gas determined by these three methods are the same, or it can also finally output the state of the current driving gas only when the states of the driving gas determined by any two methods are the same.

[0085] This document has been described with reference to various exemplary embodiments. However, those skilled in the art will recognize that changes and modifications can be made to the exemplary embodiments without departing from the scope of this document. For example, the various operating steps and the components used to perform the operating steps can be implemented in different ways according to a particular application or any number of cost functions associated with the operation of the system (e.g., one or more steps can be deleted, modified, or incorporated into other steps).

[0086] In addition, as understood by those skilled in the art, the principles herein can be embodied in a computer program product on a computer-readable storage medium that is preloaded with computer-readable program code. Any tangible, non-transitory computer-readable storage medium can be used, including magnetic storage devices (hard disks, floppy disks, etc.), optical storage devices (CD-ROMs, DVDs, Blu-ray discs, etc.), flash memories, and / or the like. These computer program instructions can be loaded onto a general-purpose computer, a special-purpose computer, or other programmable data processing devices to form a machine, such that the instructions executed on the computer or other programmable data processing devices can generate a device for implementing the specified functions. These computer program instructions can also be stored in a computer-readable memory, which can direct the computer or other programmable data processing devices to operate in a specific manner, so that the instructions stored in the computer-readable memory can form a manufactured article, including a device for implementing the specified functions. The computer program instructions can also be loaded onto a computer or other programmable data processing devices, thereby performing a series of operating steps on the computer or other programmable devices to generate a computer-implemented process, such that the instructions executed on the computer or other programmable devices can provide steps for implementing the specified functions.

[0087] Although the principles herein have been shown in various embodiments, many modifications of structures, arrangements, proportions, elements, materials, and components that are particularly applicable to specific environments and operating requirements can be used without departing from the principles and scope of this disclosure. The above modifications and other changes or corrections will be included within the scope of this document.

[0088] The foregoing detailed description has been presented with reference to various embodiments. However, those skilled in the art will recognize that various modifications and changes can be made without departing from the scope of this disclosure. Accordingly, the contemplation of this disclosure is illustrative in nature and not restrictive, and all such modifications will be included within its scope. Similarly, the advantages, other advantages, and solutions to problems of the various embodiments have been described above. However, benefits, advantages, solutions to problems, and any elements that produce these, or that make them more explicit, should not be construed as critical, essential, or necessary. As used herein, the term "comprising" and any other variants thereof are non-exclusive inclusions, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but also other elements not expressly listed or inherent to the process, method, system, article, or apparatus. In addition, the term "coupled" and any other variants thereof as used herein refer to physical connection, electrical connection, magnetic connection, optical connection, communication connection, functional connection, and / or any other connection.

[0089] Those having skill in the art will recognize that many changes in the details of the above-described embodiments can be made without departing from the basic principles of the invention. Thus, the scope of the invention is to be determined by the following claims.

Claims

1. An anesthetic machine, characterized in that, Comprising: A bellows-free gas driving branch; A breathing circuit for connecting to a patient; A driving gas branch for supplying driving gas to the bellows-free gas driving branch; A fresh gas branch for supplying fresh gas to the breathing circuit; A gas discharge branch for discharging excess gas during the exhalation phase; The bellows-free gas driving branch includes a bellows-free gas driver, which is used to store driving gas during the inhalation phase and store the gas of the breathing circuit during the exhalation phase; The output end of the driving gas branch is connected to the input end of the gas discharge branch and one end of the bellows-free gas driving branch. The other end of the bellows-free gas driving branch is connected to the first end of the breathing circuit. The fresh gas branch is connected to the second end of the breathing circuit. The third end of the breathing circuit is used to connect to a patient; A processing module for: Obtaining a first gas volume flowing into the breathing circuit through the bellows-free gas driver during the inhalation phase and a second gas volume of the gas of the breathing circuit entering the bellows-free gas driver during the exhalation phase; and Determining whether the state of the current driving gas is that the driving gas enters the breathing circuit according to the first gas volume and the second gas volume.

2. The anesthesia machine according to claim 1, characterized in that, The processing module determines whether the state of the current driving gas is that the driving gas enters the breathing circuit according to the first gas volume and the second gas volume, including: Calculating the difference between the first gas volume and the second gas volume, and comparing the size of the difference with a preset threshold; when the difference is greater than the preset threshold, determining that the state of the current driving gas is that the driving gas enters the breathing circuit.

3. The anesthesia machine according to claim 2, characterized in that, The processing module is further used for: when the difference is less than the preset threshold, determining that the state of the current driving gas is that the driving gas does not enter the breathing circuit.

4. The anesthesia machine according to any one of claims 1 to 3, characterized in that, The anesthetic machine further includes a detection module, and the detection module includes a first sensor and a second sensor; the first sensor is arranged in the driving gas branch, and the second sensor is arranged in the gas discharge branch; during the inhalation phase, the first gas volume is obtained by subtracting the flow rate detected by the second sensor from the flow rate detected by the first sensor; the flow rate detected by the second sensor during the exhalation phase is the second gas volume.

5. The anesthesia machine according to any one of claims 1 to 3, characterized in that The anesthetic machine further includes a detection module, and the detection module includes a third sensor; the third sensor is arranged in the bellows-free gas driving branch; The flow rate detected by the third sensor during the inhalation phase is the first gas volume, and the flow rate detected by the third sensor during the exhalation phase is the second gas volume.

6. The anesthesia machine according to claim 4, characterized in that, The driving gas branch includes a driving gas interface; the gas discharge branch includes an exhalation valve; the first sensor is located at the rear end of the driving gas interface; the second sensor is located at the front end or the rear end of the exhalation valve.

7. The anesthesia machine according to claim 5, characterized in that, The third sensor is located at the front end or the rear end of the bellows-free gas driver.

8. The anesthesia machine according to claim 2, characterized in that, The preset threshold is less than or equal to 0.

9. The anesthesia machine according to claim 3, characterized in that, When the state of the current driving gas is that the driving gas does not enter the breathing circuit, the gas volume discharged by the gas discharge branch during the exhalation phase is the absolute value of the difference between the difference and the preset threshold.

10. The anesthesia machine according to claim 2, characterized in that, The processing module is further used for: When the current state of the driving gas is that when the driving gas enters the breathing circuit, the recommended fresh gas volume of the fresh gas branch is calculated according to the difference value and the preset threshold value, and the recommended fresh gas volume is the fresh gas volume that ensures that the driving gas does not enter the breathing circuit; Output the recommended fresh gas volume or adjust the flow rate of the fresh gas according to the recommended fresh gas volume.

11. The anesthesia machine according to any one of claims 1 to 3, characterized in that, The anesthetic machine further includes a detection module for detecting at least two gas parameters, and the at least two gas parameters include at least two of: driving gas flow rate, fresh gas flow rate, inspiratory flow rate in the breathing circuit, expiratory flow rate in the breathing circuit, and pressure when the gas in the gas discharge branch discharges gas; The processing module obtains the first gas volume flowing into the breathing circuit through the bellowsless gas driver during the inhalation phase and the second gas volume of the gas in the breathing circuit entering the bellowsless gas driver during the exhalation phase, including: According to the at least two gas parameters, calculate the first gas volume flowing into the breathing circuit through the bellowsless gas driver during the inhalation phase and the second gas volume of the gas in the breathing circuit entering the bellowsless gas driver during the exhalation phase.

12. The anesthesia machine according to claim 1, characterized in that, The anesthetic machine further includes a detection module for detecting at least two gas parameters, and the at least two gas parameters include at least two of: driving gas flow rate, fresh gas flow rate, inspiratory flow rate in the breathing circuit, expiratory flow rate in the breathing circuit, and pressure when the gas in the gas discharge branch discharges gas; The processing module obtains the first gas volume flowing into the breathing circuit through the bellowsless gas driver during the inhalation phase and the second gas volume of the gas in the breathing circuit entering the bellowsless gas driver during the exhalation phase; and determines whether the current state of the driving gas is that the driving gas enters the breathing circuit according to the first gas volume and the second gas volume, including: Input the at least two gas parameters into a pre-trained deep learning model to obtain the result output by the deep learning model: whether the current state of the driving gas is that the driving gas enters the breathing circuit.

13. The anesthesia machine according to any one of claims 1 to 3, characterized in that, The anesthetic machine further includes a detection module for detecting at least two gas parameters, and the at least two gas parameters include at least two of: driving gas flow rate, fresh gas flow rate, inspiratory flow rate in the breathing circuit, expiratory flow rate in the breathing circuit, and pressure when the gas in the gas discharge branch discharges gas; The processing module is further configured to: input the at least two gas parameters into a pre-trained deep learning model to obtain the result output by the deep learning model; The result output by the deep learning model is the third gas volume of the driving gas entering the breathing circuit or the recommended fresh gas volume of the fresh gas branch.

14. The anesthesia machine according to any one of claims 11 to 13, characterized in that, The detection module includes at least two of a driving gas sensor, a fresh gas sensor, an inhalation sensor, an exhalation sensor, and a pressure sensor; wherein, the driving gas sensor is arranged in the driving gas branch for detecting the flow rate of the driving gas; the fresh gas sensor is arranged in the fresh gas branch for detecting the flow rate of the fresh gas; the inhalation sensor is arranged in the breathing circuit for detecting the inhalation flow rate of the breathing circuit during the inhalation phase; the exhalation sensor is arranged in the breathing circuit for detecting the exhalation flow rate of the breathing circuit during the exhalation phase; the pressure sensor is arranged in the gas discharge branch for detecting the pressure when the gas is discharged from the gas discharge branch.

15. The anesthesia machine according to any one of claims 1 to 3, characterized in that, The processing module is further configured to obtain the change trend of anesthetic concentration or the change trend of oxygen concentration; and when the change trend of anesthetic concentration is a decrease in anesthetic concentration, determine that the state of the current driving gas is: the driving gas enters the breathing circuit; or, when the change trend of oxygen concentration is an increase in oxygen concentration, determine that the state of the current driving gas is: the driving gas enters the breathing circuit.

16. The anesthesia machine according to claim 15, characterized in that, The processing module is further configured to: When the change trend of anesthetic concentration is an increase in anesthetic concentration, determine that the state of the current driving gas is: the driving gas does not enter the breathing circuit; or, when the change trend of oxygen concentration is a decrease in oxygen concentration, determine that the state of the current driving gas is: the driving gas does not enter the breathing circuit.

17. The anesthesia machine according to claim 15 or 16, characterized in that, The anesthesia machine further includes a detection module, and the detection module includes a fourth sensor; The fourth sensor is arranged in the gas discharge branch for detecting anesthetic concentration or oxygen concentration; or, The fourth sensor is arranged in the gas driving branch without a bellows for detecting anesthetic concentration or oxygen concentration.

18. The anesthesia machine according to claim 15 or 16, characterized in that, The anesthesia machine further includes a detection module, and the detection module includes a fifth sensor; the fifth sensor is arranged in the breathing circuit for detecting anesthetic concentration or oxygen concentration.

19. The anesthesia machine according to any one of claims 1 to 18, characterized in that, The processing module is further configured to: output the state of the current driving gas.

20. A method for identifying the state of the driving gas of an anesthesia machine, characterized in that, The anesthesia machine includes: a breathing circuit for connecting to a patient, a driving gas branch for providing driving gas for the gas driving branch without a bellows, and a gas driving branch without a bellows having a gas driver without a bellows; the gas driver without a bellows is configured to store driving gas during the inhalation phase and store the gas of the breathing circuit during the exhalation phase; the method includes: Obtaining a first gas volume flowing from the gas driver without a bellows into the breathing circuit during the inhalation phase and a second gas volume of the gas of the breathing circuit entering the gas driver without a bellows during the exhalation phase; Determining whether the state of the current driving gas is: the driving gas enters the breathing circuit according to the first gas volume and the second gas volume; If so, output the state of the current driving gas.

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