A dynamic compensation device for simulating high-altitude pressure and self-adapting to the first aid of injured persons

Abstract

The present invention relates to the field of pressure compensation control technology, and in particular to a simulated high-altitude pressure adaptive wounded first aid dynamic compensation device, the device comprising an airway, an airbag, an air pump, a sensor node group and an adaptive control module, the adaptive control module acquiring target first aid data through a data acquisition unit, the adaptive control module acquiring an environmental pressure prediction value through an environmental pressure prediction unit, the adaptive control module generating an airway airbag safety dynamic compensation interval through a pressure dynamic compensation unit, the adaptive control module generating a control instruction through a control instruction generation unit, and controlling the airbag pressure through a pressure control unit, the present invention generates an airway airbag safety dynamic compensation interval to perform real-time dynamic control of the airbag pressure, thereby improving the adaptability and use efficiency of the device.

Description

Technical Field

[0001] The present invention relates to the technical field of pressure compensation control, in particular to a dynamic compensation device for simulating high-altitude pressure self-adaptation for first aid of wounded persons. Background Art

[0002] In high-altitude environments, air pressure will change dramatically with the rapid increase or decrease in altitude. Traditional airway bags are difficult to maintain stable pressure under such rapid pressure changes, and most existing airway bag devices use fixed pressure setting thresholds or simple manual adjustment methods. They are unable to perceive the rapid changes in high-altitude pressure in real time and automatically make corresponding adjustments. Different target users have individual differences due to factors such as age, physical condition, and underlying diseases, and their tolerance range and requirements for airway bag pressure are also different. However, traditional airway management methods often use a unified airbag pressure standard, which does not fully consider that the individual physiological changes of the target users will also affect the optimal value of the airway bag pressure. Existing airbag devices are unable to monitor the physiological information of the injured in real time and adjust the airbag pressure accordingly.

[0003] Chinese patent application publication number CN117179843A discloses an automatic pressurized intelligent hemostatic device based on adaptive hemostatic pressure, including a display and main control unit, a force application and unloading unit, a sensor and power supply unit, a wearable unit, a base, and a top cover. It can be seen that this solution still has the problem of being unable to perceive the rapid changes in high-altitude pressure in real time and perform dynamic pressure compensation, and lacks the ability to regulate the airbag pressure according to the individual physiological differences of the target user, resulting in low adaptability and utilization efficiency of the device. Summary of the Invention

[0004] To this end, the present invention provides a dynamic compensation device for first aid of injured persons that simulates high-altitude pressure and is adaptive to the conditions, so as to overcome the problems in the prior art of being unable to perceive the rapid changes in high-altitude pressure in real time and perform dynamic pressure compensation, and lacking the ability to regulate the airbag pressure according to the physiological differences of the target user, resulting in low adaptability and utilization efficiency of the device.

[0005] To achieve the above-mentioned object, the present invention provides a simulated high-altitude pressure adaptive dynamic compensation device for first aid of injured persons, the device comprising an airway, an air bag, an air pump, a sensor node group, an adaptive control module and a sealing connector, wherein:

[0006] an airway connected to the air bag, the air pump and the sealing connection piece for supplying oxygen to the target user;

[0007] an air bag connected to the airway and used to seal the target user's laryngeal cavity;

[0008] an air pump connected to the sealing connector, the airway and the adaptive control module, and configured to deliver oxygen to the airway;

[0009] A sensor node group, which is connected to the adaptive control module and is used to collect target emergency data;

[0010] An adaptive control module, connected to the sensor node group and the air pump, is used to control the simulated high-altitude pressure adaptive target user emergency dynamic compensation device based on target emergency data. The control includes acquiring the target emergency data, acquiring the ambient pressure prediction value, performing error adjustment and error updating on the ambient pressure prediction value, generating an airway airbag safety dynamic compensation interval, optimizing the airway airbag safety dynamic compensation interval and the force optimization, acquiring the pressure trend, generating a control instruction, and controlling the airbag pressure according to the control instruction;

[0011] The sealing connector is connected to the air pump and the air passage and is used for connecting the air pump and the air passage.

[0012] Furthermore, the adaptive control module includes:

[0013] A data acquisition unit, used to acquire target first aid data;

[0014] an environmental pressure prediction unit, configured to obtain an environmental pressure prediction value based on target emergency data using an environmental pressure prediction value acquisition method, obtain an environmental pressure prediction value, perform error adjustment on the environmental pressure prediction value based on an average absolute error value, and perform error update on the error adjustment process based on a pressure change acceleration;

[0015] a pressure dynamic compensation unit, configured to generate an airway airbag safety dynamic compensation interval according to target emergency data using an airway airbag safety dynamic compensation interval generation method, optimize the airway airbag safety dynamic compensation interval according to the target emergency data, and optimize the intensity of the interval optimization process according to the pressure change acceleration;

[0016] a control instruction generation unit, configured to obtain a pressure trend based on an ambient pressure prediction value and an airway airbag safety dynamic compensation interval, and to generate a control instruction based on the pressure trend using a control instruction generation method;

[0017] The pressure control unit is used to control the airbag pressure according to the control instructions.

[0018] Furthermore, the environmental pressure prediction unit obtains the environmental pressure prediction value according to the target emergency data through an environmental pressure prediction value acquisition method, and the environmental pressure prediction value acquisition method includes:

[0019] Step A01, acquiring a historical environmental parameter set according to target emergency data;

[0020] Step A02: Divide the historical environmental parameter set into a 70% environmental training set and a 30% environmental validation set;

[0021] Step A03, initializing parameters of the spatiotemporal convolutional neural network model to obtain an initialized spatiotemporal convolutional neural network model;

[0022] Step A04: inputting the environment training set into the initialized spatiotemporal convolutional neural network model for model training to obtain a trained spatiotemporal convolutional neural network model;

[0023] Step A05: Based on the ambient temperature at time t1 , amount of substance n, gas volume and the ideal gas constant Predict environmental pressure at time t1 Calculate and set , get the predicted environmental pressure at time t1 ;

[0024] Step A06: Predict the environmental pressure based on time t1 , high altitude pressure at time t1 and time steps For the basic loss function Calculate and set ,in, is the order of the time steps;

[0025] Step A07, according to the number of time steps , predicted environmental pressure at time t1 , ambient temperature at time t1 , actual pressure value at time t-1 , ambient temperature at time t-1 Pressure-temperature loss function Calculate and set , and obtain the pressure-temperature loss function ;

[0026] Step A08, according to the time step , predicted environmental pressure at time t1 , ambient temperature at time t1 , coefficients of the gas state equation Loss function for the gas state equation Calculate and set , we get the gas state equation loss function ;

[0027] Step A09, according to the time step , predicted environmental pressure at time t1 , ambient temperature at time t1 , actual pressure value at time t-1 , ambient temperature at time t-1 , prediction step length and the pressure-temperature change coefficient Loss function for physical constraints on pressure change rate Calculate and set , 3 seconds ≤ Tw ≤ 4 seconds, and the pressure change rate physical constraint loss function is obtained ;

[0028] Step A10, based on the basic loss function , pressure-temperature loss function , gas state equation loss function , pressure change rate physical constraint loss function , pressure temperature coefficient α1, gas state coefficient α2 and pressure change rate coefficient α3 to calculate the total loss function Lt, set Lt= +α1× +α2× +α3× , get the total loss function Lt;

[0029] In step A11, the environmental verification set is input into the trained spatiotemporal convolutional neural network model, and the loss of the trained spatiotemporal convolutional neural network model is optimized according to the total loss function to obtain an environmental pressure prediction model.

[0030] Step A12: input the high altitude pressure into the environmental pressure prediction model to obtain the environmental pressure prediction value.

[0031] Furthermore, when the environmental pressure prediction unit performs error adjustment on the environmental pressure prediction model according to the average absolute error, the environmental pressure prediction unit adjusts the error according to the number of prediction samples. , actual pressure value and pressure prediction values Mean absolute error Calculate and set ,in, To predict the order of samples, get the average absolute error , the mean absolute error The average absolute error with the preset For comparison, set 0.25≤ ≤0.5, judge the compliance of the average absolute error value with the standard according to the comparison results, and make error adjustments to the pressure temperature coefficient α1, gas state coefficient α2 and pressure change rate coefficient α3 according to the judgment results, where:

[0032] when ≤ When , the environmental pressure prediction unit determines that the compliance of the average value of the absolute error is compliance, and does not perform error adjustment on the pressure temperature coefficient α1, the gas state coefficient α2, and the pressure change rate coefficient α3;

[0033] when > When the environmental pressure prediction unit determines that the absolute error average value is not up to standard, the error coefficient Adjust the pressure temperature coefficient α1, gas state coefficient α2 and pressure change rate coefficient α3 to set the error. , where e is the base of the natural logarithm, and the adjusted pressure-temperature coefficient α1`, the adjusted gas state coefficient α2`, and the adjusted pressure change rate coefficient α3` are obtained. Set α1`=α1×β, α2`=α2×β, α3`=α3×β, replace the pressure-temperature coefficient α1, gas state coefficient α2, and pressure change rate coefficient α3 with the adjusted pressure-temperature coefficient α1`, adjusted gas state coefficient α2`, and adjusted pressure change rate coefficient α3`, and recalculate the total loss function Lt.

[0034] Furthermore, when the environmental pressure prediction unit performs error update on the error adjustment process according to the pressure change acceleration, the environmental pressure prediction value , the environmental pressure predicted at the previous moment , predict environmental pressure at the next moment and prediction step length Acceleration of pressure change Calculate and set , and the pressure change acceleration is obtained , the pressure change acceleration Acceleration with preset pressure change Compare and set =10Pa / h 2 , judge the pressure change acceleration according to the comparison results, and calculate the preset absolute error average value according to the judgment results. Perform error update, where:

[0035] when ≤ When the ambient pressure prediction unit determines that the pressure change acceleration is normal, the preset absolute error average value is not set. Perform error update;

[0036] when > When the environmental pressure prediction unit determines that the pressure change acceleration is abnormal, the preset absolute error average value Perform error update according to the acceleration coefficient For the preset absolute error mean Perform error update and set , get the updated preset absolute error average `, set `= × , the preset absolute error average Replaced with the preset average absolute error after update `, and average the absolute error and the average absolute error of the preset value after update `Re-compare.

[0037] Furthermore, the pressure dynamic compensation unit generates an airway airbag safety dynamic compensation interval according to the target emergency data by using an airway airbag safety dynamic compensation interval generation method, and the airway airbag safety dynamic compensation interval generation method includes:

[0038] Step B01: Acquire the generator and discriminator, and initialize the generator and discriminator to obtain the initial generator and initial discriminator;

[0039] Step B02: Input the blood oxygen, heart rate, respiratory rate, and tracheal diameter in the target emergency data as individual feature data into an initial generator to obtain an initial airway airbag safety dynamic compensation interval Px, wherein the initial airway airbag safety dynamic compensation interval Px includes an adult clinical restraint Px1 and a child clinical restraint Px2;

[0040] Step B03: Set the lower limit Pmin of the airway bag safety dynamic compensation interval and the upper limit Pmax1 of the airway bag safety dynamic compensation interval for adults as the adult clinical constraint Px1, and set the lower limit Pmin of the airway bag safety dynamic compensation interval and the upper limit Pmax2 of the airway bag safety dynamic compensation interval for children as the child clinical constraint Px2, and set Pmin≤Px1≤Pmax1, Pmin≤Px≤Pmax2, Pmax1=35cmH2O, Pmax2=25cmH2O, and Pmin=12cmH2O;

[0041] Step B04: inputting individual feature data, adult clinical restraints, child clinical restraints, and the actual airway bag safety dynamic compensation interval into an initial discriminator to obtain a final probability value Gp;

[0042] Step B05: Compare the final probability value Gp with the preset probability value Gp0, setting 80%≤Gp0≤100%, and determine whether the final probability value meets the standard based on the comparison result. Then, output the airway bag safety dynamic compensation interval based on the determination result, where:

[0043] When Gp<Gp0, the pressure dynamic compensation unit determines that the final probability value does not meet the standard. When the target user is an adult, the adult clinical restraint is output as the airway bag safety dynamic compensation interval; when the target user is a child, the child clinical restraint is output as the airway bag safety dynamic compensation interval;

[0044] When Gp≥Gp0, the pressure dynamic compensation unit determines that the final probability value meets the standard, and outputs the initial airway airbag safety dynamic compensation interval as the airway airbag safety dynamic compensation interval.

[0045] Furthermore, when the pressure dynamic compensation unit optimizes the airway bag safety dynamic compensation interval generation method based on the target emergency data, the heart rate variation frequency Fx in the target emergency data is compared with the preset heart rate variation frequency Fx0, and Fx=100 beats / minute is set. The heart rate variation frequency is judged based on the comparison result, and the adult clinical restraint Px1 and the child clinical restraint Px2 are interval-optimized based on the judgment result, wherein:

[0046] When Fx≥Fx0, the pressure dynamic compensation unit determines that the heart rate change frequency is normal, and does not perform interval optimization on the adult clinical restraint Px1 and the child clinical restraint Px2;

[0047] When Fx<Fx0, the pressure dynamic compensation unit determines that the heart rate change frequency is abnormal, and performs interval optimization on the adult clinical restraint Px1 and the child clinical restraint Px2. The interval optimization of the adult clinical restraint Px1 and the child clinical restraint Px2 is performed according to the variation coefficient ap, and ap=1.27-0.14×e -0.7×（Fx0-Fx） , where e is the base of the natural logarithm. The optimized adult clinical constraint Px1` and the optimized child clinical constraint Px2` are obtained. Px1`=Px1×ap is set. When Px1`>35cmH2O, Px1`=35cmH2O and Px2`=Px2×ap are set. When Px2`>25cmH2O, Px2`=25cmH2O are set. The adult clinical constraint Px1 is replaced with the optimized adult clinical constraint Px1`, and the child clinical constraint Px2 is replaced with the optimized child clinical constraint Px2`, and the final probability value Gp is ​​re-obtained.

[0048] Furthermore, when the pressure dynamic compensation unit performs interval optimization on the airway bag safety dynamic compensation interval generation method based on the target emergency data, the blood flow abnormality value Pb is calculated based on the blood perfusion volume PUs and the baseline value PUb in the target emergency data, and Pb=(PUb-PUs) / PUb×100% is set to obtain the blood flow abnormality value Pb. The blood flow abnormality value Pb is compared with the preset blood flow abnormality value Pb0, and the situation of the blood flow abnormality is judged based on the comparison result. Based on the judgment result, the adult clinical restraint Px1 and the child clinical restraint Px2 are subjected to secondary interval optimization, wherein:

[0049] When Pb≤Pb0, the pressure dynamic compensation unit determines that the abnormal blood flow value is not serious, and does not perform secondary interval optimization on the adult clinical constraint Px1 and the child clinical constraint Px2;

[0050] When Pb>Pb0, the pressure dynamic compensation unit determines that the blood flow abnormality is serious, and does not perform secondary interval optimization on the adult clinical constraint Px1 and the child clinical constraint Px2. Instead, the adult clinical constraint Px1 and the child clinical constraint Px2 are optimized secondary interval according to the contraction coefficient scx, and 0.4≤scx≤0.8 is set to obtain the secondary optimized adult clinical constraint Px1`` and the secondary optimized child clinical constraint Px2``. Px1``=Px1×scx is set. When Px1``<12cmH2O, Px1``=12cmH2O and Px2``=Px2×scx are set. When Px2``<12cmH2O, Px2``=12cmH2O are set. The adult clinical constraint Px1 is replaced with the secondary optimized adult clinical constraint Px1``, and the child clinical constraint Px2 is replaced with the secondary optimized child clinical constraint Px2``, and the final probability value Gp is ​​reacquired.

[0051] Furthermore, when the pressure dynamic compensation unit optimizes the interval optimization process according to the pressure change acceleration, the pressure change acceleration Compare with the preset pressure change acceleration Vj0 and set Vj0=10Pa / h 2 , judge the pressure change acceleration according to the comparison results, and optimize the contraction coefficient scx according to the judgment results, where:

[0052] when When ≤Vj0, the pressure dynamic compensation unit determines that the pressure change acceleration is normal and does not perform force optimization on the contraction coefficient scx;

[0053] when When Vj0 is higher, the pressure dynamic compensation unit determines that the pressure change acceleration is abnormal, and optimizes the contraction coefficient scx according to the force coefficient ld, setting ldy=1.57-0.23×e -0.38×（Vj-Vj0） , where e is the base of the natural logarithm, and the optimized shrinkage coefficient scx` is obtained. Set scx`=scx×ldy, replace the shrinkage coefficient scx with the optimized shrinkage coefficient scx`, and re-perform quadratic interval optimization on the adult clinical constraint Px1 and the child clinical constraint Px2 based on the optimized shrinkage coefficient scx`.

[0054] Furthermore, when the control instruction generation unit obtains the pressure trend according to the environmental pressure prediction value and the airway airbag safety dynamic compensation interval, when the target user is an adult, the pressure change acceleration is The predicted ambient pressure value P is compared with the second preset pressure change acceleration Vj01 and the adult clinical restraint, which includes the lower limit value Pmin of the airway airbag safety dynamic compensation interval and the upper limit value Pmax1 of the adult airway airbag safety dynamic compensation interval. Vj01 is set to 0, Pmin = 12 cmH2O, and Pmax1 = 35 cmH2O. The high-altitude pressure risk is judged based on the comparison results, and the pressure trend is output based on the judgment results, where:

[0055] when >Vj01 and P>Pmax1, the control instruction generation unit determines that the high altitude pressure risk situation is risky and outputs the risk as a pressure trend;

[0056] when >Vj01 and Pmin<P≤Pmax1, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0057] when >Vj01 and P≤Pmin, the control instruction generation unit determines that the high-altitude pressure risk situation is risky, controls the airway bag pressure according to the airway bag pressure control method, and outputs the risk as a pressure trend;

[0058] when ≤Vj01 and P>Pmax1, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0059] when ≤Vj01 and Pmin<P≤Pmax1, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0060] when ≤Vj01 and P≤Pmin, the control instruction generating unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0061] When the target user is a child, the pressure change acceleration The predicted ambient pressure value P is compared with the second preset pressure change acceleration Vj01 and the child clinical restraint, which includes the lower limit value Pmin of the airway airbag safety dynamic compensation interval and the upper limit value Pmax2 of the child airway airbag safety dynamic compensation interval. Vj01 is set to 0, Pmin = 12 cmH2O, and Pmax2 = 25 cmH2O. The high-altitude pressure risk is judged based on the comparison results, and the pressure trend is output based on the judgment results, where:

[0062] when >Vj01 and P>Pmax2, the control instruction generation unit determines that the high altitude pressure risk situation is risky and outputs the risk as a pressure trend;

[0063] when >Vj01 and Pmin<P≤Pmax2, the control instruction generation unit determines that the high-altitude pressure risk is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0064] when >Vj01 and P≤Pmin, the control instruction generation unit determines that the high-altitude pressure risk situation is risky, controls the airway bag pressure according to the airway bag pressure control method, and outputs the risk as a pressure trend;

[0065] when ≤Vj01 and P>Pmax2, the control instruction generation unit determines that the high altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0066] when ≤Vj01 and Pmin<P≤Pmax2, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0067] when ≤Vj01 and P≤Pmin, the control instruction generating unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0068] The control instruction generation unit generates a control instruction according to the pressure trend by using a control instruction generation method, and the control instruction generation method includes:

[0069] Step S01, when the target user is an adult, calculate the sudden pressure prediction safety difference ΔP1 and the sudden pressure drop prediction safety difference ΔP2 based on the ambient pressure prediction value P, the lower limit value Pmin of the airway airbag safety dynamic compensation interval, and the upper limit value Pmax1 of the adult airway airbag safety dynamic compensation interval, and set ΔP1=P-Pmax1 and ΔP2=Pmin-P to obtain the sudden pressure prediction safety difference ΔP1 and the sudden pressure drop prediction safety difference ΔP2;

[0070] When the target user is a child, the predicted safety difference ΔP1 for sudden pressure increase and the predicted safety difference ΔP2 for sudden pressure decrease are calculated based on the predicted ambient pressure value P, the lower limit Pmin of the airway airbag safety dynamic compensation interval, and the upper limit Pmax2 of the airway airbag safety dynamic compensation interval for children. ΔP1=P-Pmax2 and ΔP2=Pmin-P are set to obtain the predicted safety difference ΔP1 for sudden pressure increase and the predicted safety difference ΔP2 for sudden pressure decrease.

[0071] Step S02, initializing the PID control algorithm to obtain an initialized PID control algorithm;

[0072] Step S03, inputting the sudden pressure increase prediction safety difference ΔP1 and the sudden pressure decrease prediction safety difference ΔP2 into the initialized PID control algorithm to obtain a control instruction;

[0073] The pressure control unit controls the airbag pressure according to the control instruction.

[0074] Compared with the prior art, the beneficial effect of the present invention lies in that the present invention acquires target first aid data in real time through an adaptive control module, and generates an airway airbag safety dynamic compensation interval based on the target first aid data, so as to dynamically control the airbag pressure in real time, thereby improving the adaptability of the simulated high-altitude pressure adaptive target user first aid dynamic compensation device, wherein the adaptive control module acquires the target first aid data through a data acquisition unit, so as to acquire the physiological state and high-altitude pressure state of different target users in real time, thereby improving the accuracy of regulating the airbag pressure, and the adaptive control module also predicts environmental changes through an environmental pressure prediction unit, so as to adjust the intensity of regulation in time according to changes in the environment at future moments, Thereby improving the timeliness of regulating the airbag pressure, the adaptive regulation module also generates the airway airbag safety dynamic compensation interval through the pressure dynamic compensation unit, so as to reasonably dynamically compensate the airbag pressure according to the difference in the physiological state of the target user, thereby improving the adaptability of the simulated high-altitude pressure adaptive target user emergency dynamic compensation device, the adaptive regulation module also generates the control instruction through the control instruction generation unit, so as to regulate the airbag pressure in real time, the adaptive regulation module also controls the airbag pressure according to the control instruction through the pressure control unit, so as to adjust the airbag pressure in real time under risk conditions, thereby improving the adaptability and use efficiency of the simulated high-altitude pressure adaptive target user emergency dynamic compensation device. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 This is a schematic diagram of the structure of the dynamic compensation device for simulating high-altitude pressure self-adaptive first aid for injured persons in this embodiment;

[0076] Figure 2 Schematic diagram of the structure of the adaptive control module in this embodiment. DETAILED DESCRIPTION

[0077] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0078] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0079] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0080] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0081] See also Figure 1 As shown, it is a schematic diagram of the structure of the dynamic compensation device for simulating high-altitude pressure self-adaptive emergency treatment of injured persons in this embodiment, and the device includes:

[0082] An airway 1, which is connected to an air bag 2, an air pump 3 and a sealing connector 6, and is used to supply oxygen to a target user;

[0083] Airbag 2, connected to airway 1, for sealing the target user's laryngeal cavity;

[0084] An air pump 3 connected to the sealing connector 6, the airway 1 and the adaptive control module 5, for delivering oxygen to the airway 1;

[0085] A sensor node group 4, which is connected to the adaptive control module 5 and is used to collect target emergency data;

[0086] An adaptive control module 5, connected to the sensor node group 4 and the air pump 3, is used to control the simulated high-altitude pressure adaptive target user emergency dynamic compensation device according to the target emergency data. The control includes acquiring the target emergency data, acquiring the ambient pressure prediction value, performing error adjustment and error updating on the ambient pressure prediction value, generating an airway airbag safety dynamic compensation interval, optimizing the airway airbag safety dynamic compensation interval and the force optimization, acquiring the pressure trend, generating a control instruction, and controlling the airbag pressure according to the control instruction;

[0087] The sealing connector 6 is connected to the air pump 3 and the air channel 1 and is used to connect the air pump 3 and the air channel 1 .

[0088] Specifically, the sensor node group 4 includes a laser Doppler blood flow meter 401, an ultrasonic ranging sensor 402, a pressure sensor 403, a temperature sensor 404, a reflective photoelectric blood oxygen sensor 405 and a bioelectrical impedance sensor 406. The laser Doppler blood flow meter 401 is connected to the adaptive control module 5 for collecting the blood perfusion volume in the target emergency data. The ultrasonic ranging sensor 402 is connected to the adaptive control module 5 for collecting the tracheal diameter in the target emergency data. The pressure sensor 403 is connected to the adaptive control module 5 for collecting the high-altitude pressure in the target emergency data. The temperature sensor 404 is connected to the adaptive control module 5 for collecting the ambient temperature in the target emergency data. The reflective photoelectric blood oxygen sensor 405 is connected to the adaptive control module 5 for collecting the blood oxygen, heart rate and heart rate change frequency in the target emergency data. The bioelectrical impedance sensor 406 is connected to the adaptive control module 5 for collecting the respiratory rate in the target emergency data.

[0089] Specifically, the blood perfusion volume PUs refers to the amount of blood flowing through the body tissue per minute, the tracheal diameter refers to the cross-sectional diameter length of the target user's trachea, the high-altitude pressure refers to the pressure value of the high-altitude environment collected in real time, the ambient temperature refers to the real-time temperature of the environment in which the target user is located, the blood oxygen refers to the proportion of hemoglobin combined with oxygen in the target user's blood to the total hemoglobin, the heart rate refers to the number of beats of the target user's heart per minute, the heart rate change frequency refers to the degree of difference between successive heartbeats, and the respiratory rate refers to the number of breaths of the target user per minute. This implementation does not limit the target user, and relevant technical personnel in this field can freely choose according to actual needs, such as setting the target user to a wounded person.

[0090] Specifically, the simulated high-altitude pressure adaptive dynamic compensation device for first aid of the wounded is applied to high-altitude pressure first aid. The simulated high-altitude pressure adaptive dynamic compensation device for first aid of the wounded collects target first aid data and controls it according to the target first aid data so as to facilitate personalized matching for the target user, thereby improving the adaptability and dynamic compensation efficiency of the simulated high-altitude pressure adaptive dynamic compensation device for first aid of the wounded under high-altitude pressure. Among them, the simulated high-altitude pressure adaptive dynamic compensation device for first aid of the wounded acquires the target first aid data through a group of sensor nodes so as to accurately judge the individual differences of the target users, thereby improving the efficiency of dynamic compensation. The simulated high-altitude pressure adaptive dynamic compensation device for first aid of the wounded also dynamically controls the adaptive process through an adaptive control module, thereby improving the adaptability to different situations under high-altitude conditions.

[0091] See also Figure 2, which is a schematic diagram of the structure of the adaptive control module of this embodiment, the adaptive control module includes:

[0092] A data acquisition unit, used to acquire target first aid data;

[0093] an environmental pressure prediction unit, configured to obtain an environmental pressure prediction value based on the target emergency data using an environmental pressure prediction value acquisition method, obtain an environmental pressure prediction value, perform error adjustment on the environmental pressure prediction value based on an average absolute error value, and perform error update on the error adjustment process based on an acceleration of pressure change. The environmental pressure prediction unit is connected to the data acquisition unit;

[0094] a pressure dynamic compensation unit, configured to generate an airway airbag safety dynamic compensation interval according to target emergency data using an airway airbag safety dynamic compensation interval generation method, optimize the airway airbag safety dynamic compensation interval according to the target emergency data, and optimize the intensity of the interval optimization process according to the pressure change acceleration; the pressure dynamic compensation unit is connected to the ambient pressure prediction unit;

[0095] a control instruction generation unit, configured to obtain a pressure trend based on the ambient pressure prediction value and the airway airbag safety dynamic compensation interval, and to generate a control instruction based on the pressure trend using a control instruction generation method, the control instruction generation unit being connected to the pressure dynamic compensation unit;

[0096] The pressure control unit is used to control the airbag pressure according to the control instructions.

[0097] Specifically, the adaptive control module is applied to a simulated high-altitude pressure adaptive target user first aid dynamic compensation device. The adaptive control module acquires target first aid data in real time and generates an airway airbag safety dynamic compensation interval based on the target first aid data to perform real-time dynamic control of the airbag pressure, thereby improving the adaptability of the simulated high-altitude pressure adaptive target user first aid dynamic compensation device. The adaptive control module acquires target first aid data through a data acquisition unit so as to acquire the physiological state and high-altitude pressure state of different target users in real time, thereby improving the accuracy of regulating the airbag pressure. The adaptive control module also predicts environmental changes through an environmental pressure prediction unit so as to adjust the airbag pressure according to changes in the environment at future moments and The intensity of the regulation is adjusted in time, thereby improving the timeliness of regulating the airbag pressure. The adaptive regulation module also generates an airway airbag safety dynamic compensation interval through the pressure dynamic compensation unit, so as to reasonably dynamically compensate the airbag pressure according to the difference in the physiological state of the target user, thereby improving the adaptability of the simulated high-altitude pressure adaptive target user emergency dynamic compensation device. The adaptive regulation module also generates a control instruction through the control instruction generation unit, so as to regulate the airbag pressure in real time. The adaptive regulation module also controls the airbag pressure according to the control instruction through the pressure control unit, so as to adjust the airbag pressure in real time under risk conditions, thereby improving the adaptability and use efficiency of the simulated high-altitude pressure adaptive target user emergency dynamic compensation device.

[0098] Specifically, when the data acquisition unit acquires the target emergency data, the target emergency data includes high altitude pressure, ambient temperature, blood oxygen, heart rate, respiratory rate, tracheal diameter, heart rate change frequency and blood perfusion.

[0099] Specifically, the data acquisition unit acquires target first aid data so as to obtain the physiological status of different target users and the status of high-altitude pressure in real time, thereby improving the accuracy of regulating the airbag pressure.

[0100] Specifically, the environmental pressure prediction unit obtains the environmental pressure prediction value according to the target emergency data through an environmental pressure prediction value acquisition method, and the environmental pressure prediction value acquisition method includes:

[0101] Step A01, acquiring a historical environmental parameter set according to target emergency data;

[0102] Step A02: Divide the historical environmental parameter set into a 70% environmental training set and a 30% environmental validation set;

[0103] Step A03, initializing parameters of the spatiotemporal convolutional neural network model to obtain an initialized spatiotemporal convolutional neural network model;

[0104] Step A04: inputting the environment training set into the initialized spatiotemporal convolutional neural network model for model training to obtain a trained spatiotemporal convolutional neural network model;

[0105] Step A05: Based on the ambient temperature at time t1 , amount of substance n, gas volume and the ideal gas constant Predict environmental pressure at time t1 Calculate and set , get the predicted environmental pressure at time t1 ;

[0106] Step A06: Predict the environmental pressure based on time t1 , high altitude pressure at time t1 and time steps For the basic loss function Calculate and set ,in, is the order of the time steps;

[0107] Step A07, according to the number of time steps , predicted environmental pressure at time t1 , ambient temperature at time t1 , actual pressure value at time t-1 , ambient temperature at time t-1 Pressure-temperature loss function Calculate and set , and obtain the pressure-temperature loss function ;

[0108] Step A08, according to the time step , predicted environmental pressure at time t1 , ambient temperature at time t1 , coefficients of the gas state equation Loss function for the gas state equation Calculate and set , we get the gas state equation loss function ;

[0109] Step A09, according to the time step , predicted environmental pressure at time t1 , ambient temperature at time t1 , actual pressure value at time t-1 , ambient temperature at time t-1 , prediction step length and the pressure-temperature change coefficient Loss function for physical constraints on pressure change rate Calculate and set , 3 seconds ≤ Tw ≤ 4 seconds, and the pressure change rate physical constraint loss function is obtained ;

[0110] Step A10, based on the basic loss function , pressure-temperature loss function , gas state equation loss function , pressure change rate physical constraint loss function , pressure temperature coefficient α1, gas state coefficient α2 and pressure change rate coefficient α3 to calculate the total loss function Lt, set Lt= +α1× +α2× +α3× , get the total loss function Lt;

[0111] In step A11, the environmental verification set is input into the trained spatiotemporal convolutional neural network model, and the loss of the trained spatiotemporal convolutional neural network model is optimized according to the total loss function to obtain an environmental pressure prediction model.

[0112] Step A12: input the high altitude pressure into the environmental pressure prediction model to obtain the environmental pressure prediction value.

[0113] Specifically, the historical environmental parameter set refers to the high-altitude pressure generated historically in the target emergency data and the pressure prediction value corresponding to the high-altitude pressure generated historically. The high-altitude pressure is used as the input data of the environmental pressure prediction model, and the pressure prediction value is used as the output data of the environmental pressure prediction model. The environmental training set refers to the data set for model training of the initialized spatiotemporal convolutional neural network model. The environmental verification set refers to the data set for loss optimization of the trained spatiotemporal convolutional neural network model. The spatiotemporal convolutional neural network model refers to the basic model architecture for constructing the environmental pressure prediction model. The parameter initialization refers to the process of setting the parameters of the spatiotemporal convolutional neural network model. This embodiment does not limit the specific method of parameter initialization. Relevant technical personnel in this field can freely choose according to actual needs, such as random setting. The model training refers to the process of training the initialized spatiotemporal convolutional neural network model according to the environmental training set. This embodiment does not limit the specific method of model training, and relevant technical personnel in this field can freely choose according to actual needs, such as software calculation, the ambient temperature at time t1 refers to the ambient temperature collected at time t1, and the time t1 refers to a pre-set specific time point, such as setting time t1 as the current time, the amount of substance refers to the number of gas molecules in the environment, this embodiment does not limit the specific method of obtaining the amount of substance n, and relevant technical personnel in this field can freely choose according to actual needs, such as setting the gas mass to m1, then n=m1 / M, M is the molar mass, this embodiment does not limit the specific method of obtaining the gas mass m1, and relevant technical personnel in this field can freely choose according to actual needs, such as weighing method, the gas volume refers to the preset value of the ambient gas volume, this embodiment does not limit the gas volume V, and relevant technical personnel in this field can freely choose according to actual needs, such as setting V=1 The ideal gas constant refers to a fixed constant value used to calculate the predicted ambient pressure at time t1. The number of time steps refers to the use of N consecutive time steps of historical high-altitude pressure for calculation when the ambient pressure prediction model inputs data. For example, if N=10 and data is collected once per second, the ambient pressure prediction model will read the historical high-altitude pressure of the past 10 seconds as input data. The actual pressure value at time t-1 refers to the high-altitude pressure collected at time t-1. The ambient temperature at time t-1 refers to the ambient temperature collected at time t-1. The time t-1 refers to the time point one time step before time t1. The gas state equation coefficient refers to a physical coefficient that reflects the quantitative relationship between the predicted ambient pressure at time t1 and the ambient temperature at time t1. The prediction step length Tw refers to the preset interval length between time steps. The pressure-temperature change rate coefficient refers to a constant coefficient that reflects the rate of change between the high-altitude pressure and the ambient temperature. The pressure-temperature coefficient α1 refers to a preset coefficient that reflects the degree of correlation between the pressure-temperature loss function and the total loss function. The gas state coefficient α2 refers to a preset coefficient that reflects the degree of correlation between the gas state equation loss function and the total loss function. The pressure change rate coefficient α3 refers to a preset coefficient that reflects the degree of correlation between the pressure change rate physical constraint loss function and the total loss function. This implementation does not limit the pressure-temperature coefficient, the gas state coefficient, and the pressure change rate coefficient. Relevant technical personnel in this field can freely choose according to actual needs, such as setting α1=0.6, α2=0.7, and α3=0.6. The loss optimization refers to the process of using the total loss function Lt to update the parameters of the trained spatiotemporal convolutional neural network to minimize the prediction error of the model on the environmental verification set. This embodiment does not limit the specific method of loss optimization. Relevant technical personnel in this field can freely choose according to actual needs, such as using software updates.

[0114] Specifically, the environmental pressure prediction unit constructs an environmental pressure prediction model to make real-time predictions of the high-altitude pressure at future moments, so as to facilitate subsequent dynamic compensation according to the high-altitude pressure at future moments.

[0115] Specifically, when the environmental pressure prediction unit performs error adjustment on the environmental pressure prediction model according to the average absolute error, the error is adjusted according to the number of prediction samples. , actual pressure value and pressure prediction values Mean absolute error Calculate and set ,in, To predict the order of samples, get the average absolute error , the mean absolute error The average absolute error with the preset For comparison, set 0.25≤ ≤0.5, judge the compliance of the absolute error average value according to the comparison results, and make error adjustments to the pressure temperature coefficient α1, gas state coefficient α2 and pressure change rate coefficient α3 according to the judgment results, where:

[0116] when ≤ When , the environmental pressure prediction unit determines that the compliance of the average value of the absolute error is compliance, and does not perform error adjustment on the pressure temperature coefficient α1, the gas state coefficient α2, and the pressure change rate coefficient α3;

[0117] when > When the environmental pressure prediction unit determines that the absolute error average value is not up to standard, the error coefficient Adjust the pressure temperature coefficient α1, gas state coefficient α2 and pressure change rate coefficient α3 to set the error. , where e is the base of the natural logarithm, and the adjusted pressure-temperature coefficient α1`, the adjusted gas state coefficient α2`, and the adjusted pressure change rate coefficient α3` are obtained. Set α1`=α1×β, α2`=α2×β, α3`=α3×β, replace the pressure-temperature coefficient α1, gas state coefficient α2, and pressure change rate coefficient α3 with the adjusted pressure-temperature coefficient α1`, adjusted gas state coefficient α2`, and adjusted pressure change rate coefficient α3`, and recalculate the total loss function Lt.

[0118] Specifically, the predicted sample refers to the pressure prediction value output by the environmental pressure prediction model according to the time step number and the prediction step length, the predicted sample number refers to the total number of pressure prediction values ​​output by the environmental pressure prediction model according to the time step number and the prediction step length, the actual pressure value refers to the actual high-altitude pressure corresponding to the tt-th pressure prediction value in the predicted sample number, this embodiment does not limit the specific method of obtaining the actual pressure value, and relevant technical personnel in this field can freely choose according to actual needs, such as obtaining the actual pressure value through an airbag pressure monitor, the pressure prediction value refers to the tt-th pressure prediction value in the predicted sample number, tt is the order of the pressure prediction values ​​in the predicted sample number, the preset absolute error average value refers to the preset value for judging the compliance of the absolute error average value, the compliance of the absolute error average value refers to the degree of compliance of the absolute error average value judged based on the absolute error average value and the preset absolute error average value, the absolute error average value includes the compliance of the absolute error average value as being up to standard and the compliance of the absolute error average value as being not up to standard.

[0119] Specifically, the ambient pressure prediction unit calculates the average absolute error to measure the degree of error between the pressure prediction value output by the ambient pressure prediction model and the actual high-altitude pressure, thereby evaluating the accuracy of the ambient pressure prediction model. The ambient pressure prediction unit also judges whether the average absolute error meets the standard. In this embodiment, 0.25≤MAE0≤0.5 is set to avoid frequent triggering of adjustments due to small pressure fluctuations, such as when MAE0<0.2, thereby reducing misjudgment and maintaining the stability of error adjustment. At the same time, it avoids large pressure fluctuations, such as when MAE0>0.5, which fails to capture pressure changes and results in insufficient sensitivity in judging whether the average absolute error meets the standard, thereby ensuring that the non-compliance of the average absolute error is promptly and reasonably identified. When the average absolute error does not meet the standard, as the average absolute error increases, the pressure temperature coefficient, gas state coefficient and pressure change rate coefficient are increased according to the error coefficient. The change trend of the pressure temperature coefficient, gas state coefficient and pressure change rate coefficient is nonlinear with the average absolute error. In the initial stage when the average absolute error does not meet the standard, the pressure temperature coefficient, gas state coefficient and pressure change rate coefficient are quickly increased to quickly adjust the error. In the later stage, the adjustment rate tends to be flat. The error coefficient is set to match the change trend, so as to reasonably increase the correlation between the pressure temperature loss function, the gas state equation loss function and the pressure change rate physical constraint loss function and the total loss function, further converge the environmental pressure prediction model, and thus improve the accuracy of the environmental pressure prediction model.

[0120] Specifically, when the environmental pressure prediction unit performs error update on the error adjustment process according to the pressure change acceleration, the environmental pressure prediction value , the environmental pressure predicted at the previous moment , predict environmental pressure at the next moment and prediction step length Acceleration of pressure change Calculate and set , and the pressure change acceleration is obtained , the pressure change acceleration Acceleration with preset pressure change Compare and set =10Pa / h 2 , judge the pressure change acceleration according to the comparison results, and calculate the preset absolute error average value according to the judgment results. Perform error update, where:

[0121] when ≤ When the ambient pressure prediction unit determines that the pressure change acceleration is normal, the preset absolute error average value is not set. Perform error update;

[0122] when > When the environmental pressure prediction unit determines that the pressure change acceleration is abnormal, the preset absolute error average value Perform error update according to the acceleration coefficient For the preset absolute error mean Perform error update and set , get the updated preset absolute error average `, set `= × , the preset absolute error average Replaced with the updated preset absolute error average `, and average the absolute error and the average absolute error of the preset value after update `Re-compare.

[0123] Specifically, the predicted environmental pressure at the previous moment refers to the previous environmental pressure prediction value predicted by the environmental pressure prediction model, and the predicted environmental pressure P2 at the next moment refers to the next environmental pressure prediction value predicted by the environmental pressure prediction model. The time point when the environmental pressure prediction model outputs the environmental pressure prediction value is set to n, then the predicted environmental pressure at the previous moment is the environmental pressure prediction value output by the environmental pressure prediction model at the moment n-Tw, and the predicted environmental pressure P2 at the next moment is the environmental pressure prediction value output by the environmental pressure prediction model at the moment n+Tw. The preset pressure change acceleration refers to a preset value for judging the situation of pressure change acceleration. The situation of pressure change acceleration refers to the degree of compliance of pressure change acceleration judged based on the pressure change acceleration and the preset pressure change acceleration. The situation of pressure change acceleration includes the situation of pressure change acceleration being normal and the situation of pressure change acceleration being abnormal.

[0124] Specifically, the environmental pressure prediction unit calculates the acceleration of pressure change to measure the normality of the rate of change of the pressure prediction value output by the environmental pressure prediction model over time, thereby improving the evaluation accuracy of the environmental pressure prediction model. The environmental pressure prediction unit also judges the situation of the pressure change acceleration. In this embodiment, Vj0=10Pa / h is set. 2 , avoid small fluctuations in acceleration due to pressure changes, such as Vj0<10Pa / h 2When the pressure change acceleration is abnormal, the preset absolute error average value is reduced according to the acceleration coefficient. The preset absolute error average value and the change trend of the pressure change acceleration are nonlinear. In the early stage of the abnormal pressure change acceleration, the preset absolute error average value is quickly reduced to quickly update the preset absolute error average value. In the later update trend, the acceleration coefficient is set to match the change trend, so as to reasonably avoid the pressure change acceleration changing too fast and affect the accuracy of the environmental pressure prediction model, thereby improving the accuracy of the environmental pressure prediction model.

[0125] Specifically, the pressure dynamic compensation unit generates an airway airbag safety dynamic compensation interval according to the target emergency data using an airway airbag safety dynamic compensation interval generation method, and the airway airbag safety dynamic compensation interval generation method includes:

[0126] Step B01: Acquire the generator and discriminator, and initialize the generator and discriminator to obtain the initial generator and initial discriminator;

[0127] Step B02: Input the blood oxygen, heart rate, respiratory rate, and tracheal diameter in the target emergency data as individual feature data into an initial generator to obtain an initial airway airbag safety dynamic compensation interval Px, wherein the initial airway airbag safety dynamic compensation interval Px includes an adult clinical restraint Px1 and a child clinical restraint Px2;

[0128] Step B03: Set the lower limit Pmin of the airway bag safety dynamic compensation interval and the upper limit Pmax1 of the airway bag safety dynamic compensation interval for adults as the adult clinical constraint Px1, and set the lower limit Pmin of the airway bag safety dynamic compensation interval and the upper limit Pmax2 of the airway bag safety dynamic compensation interval for children as the child clinical constraint Px2, and set Pmin≤Px1≤Pmax1, Pmin≤Px≤Pmax2, Pmax1=35cmH2O, Pmax2=25cmH2O, and Pmin=12cmH2O;

[0129] Step B04: inputting individual feature data, adult clinical restraints, child clinical restraints, and the actual airway bag safety dynamic compensation interval into an initial discriminator to obtain a final probability value Gp;

[0130] Step B05: Compare the final probability value Gp with the preset probability value Gp0, setting 80%≤Gp0≤100%, and determine whether the final probability value meets the standard based on the comparison result. Then, output the airway bag safety dynamic compensation interval based on the determination result, where:

[0131] When Gp<Gp0, the pressure dynamic compensation unit determines that the final probability value does not meet the standard. When the target user is an adult, the adult clinical restraint is output as the airway bag safety dynamic compensation interval; when the target user is a child, the child clinical restraint is output as the airway bag safety dynamic compensation interval;

[0132] When Gp≥Gp0, the pressure dynamic compensation unit determines that the final probability value meets the standard, and outputs the initial airway airbag safety dynamic compensation interval as the airway airbag safety dynamic compensation interval.

[0133] Specifically, the generator refers to a model architecture that generates an initial airway airbag safety dynamic compensation interval based on individual feature data, and the discriminator refers to a model architecture that discriminates between the initial airway airbag safety dynamic compensation interval and the real airway airbag safety dynamic compensation interval. This embodiment does not limit the specific acquisition method of the generator and the discriminator. Relevant technical personnel in this field can freely choose according to actual needs, such as obtaining a pre-trained model of a deep learning framework through the network to construct the generator and the discriminator. The discrimination initialization refers to the process of setting parameters for the generator and the discriminator. This embodiment does not limit the discrimination initialization. Relevant technical personnel in this field can freely choose according to actual needs, such as software setting. The initial airway airbag safety dynamic compensation interval refers to the airbag pressure value range under the airway safety conditions generated by the initial generator. The adult clinical restraint refers to the initial airway airbag safety dynamic compensation interval applicable to adults. The pediatric clinical restraint refers to the initial airway airbag safety dynamic compensation interval applicable to children. This embodiment does not limit the division method between adults and children. Relevant technical personnel in this field The target user age can be freely selected based on actual needs. For example, if bv is set as the target user age, when bv is greater than 18 years old, the target user is determined to be an adult, and when bv is ≤18 years old, the target user is determined to be a child. The lower limit of the airway bag safety dynamic compensation interval refers to the lowest limit of adult clinical restraints and child clinical restraints. The upper limit of the adult airway bag safety dynamic compensation interval refers to the highest limit of adult clinical restraints. The upper limit of the child airway bag safety dynamic compensation interval refers to the highest limit of child clinical restraints. The actual airway bag safety dynamic compensation interval refers to the actual verified airway bag pressure safety interval. This embodiment does not limit the specific method for obtaining the actual airway bag safety dynamic compensation interval. Relevant technicians in this field can freely select it according to actual needs, such as clinical statistics. The preset probability value refers to a preset value for judging whether the final probability value meets the standard. The compliance status of the final probability value refers to the degree of compliance of the final probability value determined based on the final probability value and the preset probability value. The compliance status of the final probability value includes the following: the final probability value meets the standard and the final probability value meets the standard.

[0134] Specifically, the pressure dynamic compensation unit obtains the airway airbag safety dynamic compensation interval according to the individual characteristics of the target user through a generator. In this embodiment, the preset probability value is set to 80%≤Gp0≤100% to avoid slight fluctuations in the final probability value. For example, when Gp0 is less than 80%, the judgment process is frequently triggered to ensure the judgment sensitivity while reducing misjudgment. Age constraints are set for the airway airbag safety dynamic compensation interval according to adults and children, so as to accurately match the airway airbag safety dynamic compensation interval according to target users of different ages, thereby improving the efficiency of pressure dynamic compensation.

[0135] Specifically, when the pressure dynamic compensation unit optimizes the airway bag safety dynamic compensation interval generation method based on the target emergency data, the heart rate change frequency Fx in the target emergency data is compared with the preset heart rate change frequency Fx0, and Fx=100 beats / minute is set. The heart rate change frequency is judged based on the comparison result, and the adult clinical restraint Px1 and the child clinical restraint Px2 are interval optimized based on the judgment result, wherein:

[0136] When Fx≥Fx0, the pressure dynamic compensation unit determines that the heart rate change frequency is normal, and does not perform interval optimization on the adult clinical restraint Px1 and the child clinical restraint Px2;

[0137] When Fx<Fx0, the pressure dynamic compensation unit determines that the heart rate change frequency is abnormal, and performs interval optimization on the adult clinical restraint Px1 and the child clinical restraint Px2. The interval optimization of the adult clinical restraint Px1 and the child clinical restraint Px2 is performed according to the variation coefficient ap, and ap=1.27-0.14×e -0.7×（Fx0-Fx） , where e is the base of the natural logarithm. The optimized adult clinical constraint Px1` and the optimized child clinical constraint Px2` are obtained. Px1`=Px1×ap is set. When Px1`>35cmH2O, Px1`=35cmH2O and Px2`=Px2×ap are set. When Px2`>25cmH2O, Px2`=25cmH2O are set. The adult clinical constraint Px1 is replaced with the optimized adult clinical constraint Px1`, and the child clinical constraint Px2 is replaced with the optimized child clinical constraint Px2`, and the final probability value Gp is ​​re-obtained.

[0138] Specifically, the preset heart rate change frequency refers to a preset value for judging the situation of the heart rate change frequency, and the situation of the heart rate change frequency refers to the normal degree of the heart rate change frequency, and the situation of the heart rate change frequency includes the situation of the heart rate change frequency being normal and the situation of the heart rate change frequency being abnormal.

[0139] Specifically, the pressure dynamic compensation unit judges the situation of the heart rate change frequency. In this embodiment, Fx is set to 100 times / minute to avoid frequent optimization triggering when the heart rate change frequency fluctuates too little, such as when Fx is less than 100 times / minute, resulting in unstable interval optimization. At the same time, it avoids the situation where it is difficult to accurately capture the heart rate change frequency when the heart rate change frequency fluctuates greatly. When the heart rate change frequency is abnormal, the upper limit value of the airway airbag safety dynamic compensation interval is expanded by the change coefficient. The upper limit value of the airway airbag safety dynamic compensation interval is nonlinear with the change trend of the heart rate change frequency. In the early stage of the abnormal heart rate change frequency, the upper limit value of the airway airbag safety dynamic compensation interval needs to be quickly expanded to quickly optimize the interval. In the later stage, the abnormal rate of heart rate change frequency tends to be gentle. The change coefficient is set to match the change trend so as to reasonably increase the target user's breathing volume and avoid the airway airbag safety dynamic compensation interval affecting the target user's breathing when the heart rate decays, thereby improving the accuracy and efficiency of dynamic compensation.

[0140] Specifically, when the pressure dynamic compensation unit optimizes the airway bag safety dynamic compensation interval generation method according to the target emergency data, the blood flow abnormality value Pb is calculated according to the blood perfusion volume PUs and the baseline value PUb in the target emergency data, and Pb=(PUb-PUs) / PUb×100% is set to obtain the blood flow abnormality value Pb. The blood flow abnormality value Pb is compared with the preset blood flow abnormality value Pb0, and Pb0 is set to ≤15%. The situation of the blood flow abnormality is judged according to the comparison result, and the adult clinical restraint Px1 and the child clinical restraint Px2 are secondary interval optimized according to the judgment result, wherein:

[0141] When Pb≤Pb0, the pressure dynamic compensation unit determines that the abnormal blood flow value is not serious, and does not perform secondary interval optimization on the adult clinical constraint Px1 and the child clinical constraint Px2;

[0142] When Pb>Pb0, the pressure dynamic compensation unit determines that the blood flow abnormality is serious, and does not perform secondary interval optimization on the adult clinical constraint Px1 and the child clinical constraint Px2. Instead, the adult clinical constraint Px1 and the child clinical constraint Px2 are optimized secondary interval according to the contraction coefficient scx, and 0.4≤scx≤0.8 is set to obtain the secondary optimized adult clinical constraint Px1`` and the secondary optimized child clinical constraint Px2``. Px1``=Px1×scx is set. When Px1``<12cmH2O, Px1``=12cmH2O and Px2``=Px2×scx are set. When Px2``<12cmH2O, Px2``=12cmH2O are set. The adult clinical constraint Px1 is replaced with the secondary optimized adult clinical constraint Px1``, and the child clinical constraint Px2 is replaced with the secondary optimized child clinical constraint Px2``, and the final probability value Gp is ​​reacquired.

[0143] Specifically, the baseline value refers to the basic reference value of blood perfusion, which is used to measure the degree of abnormality of blood perfusion. This embodiment does not limit the specific method of obtaining the baseline value. Relevant technical personnel in this field can freely choose according to actual needs, such as expert evaluation. The preset blood flow abnormality value refers to a preset value for judging the situation of the blood flow abnormality value. The situation of the blood flow abnormality value refers to the severity of the abnormal situation reflected by the blood flow abnormality value. The situation of the blood flow abnormality value includes the situation of the blood flow abnormality value being not serious and the situation of the blood flow abnormality value being serious.

[0144] Specifically, the pressure dynamic compensation unit judges the situation of the blood flow abnormality value. In this embodiment, Pb0≤15% is set to avoid the situation where the blood flow abnormality value fluctuates greatly and the serious situation of the blood flow abnormality value cannot be accurately captured, resulting in inaccurate optimization results. When the abnormal situation reflected by the blood flow abnormality value is serious, the lower limit of the airway airbag safety dynamic compensation interval is contracted according to the contraction coefficient. The lower limit of the airway airbag safety dynamic compensation interval is nonlinear with the change trend of the blood flow abnormality value. In the early stage of the serious blood flow abnormality value, the lower limit of the airway airbag safety dynamic compensation interval needs to be quickly reduced to quickly optimize. In the later stage, the change state of the blood flow abnormality value tends to be gentle, and the contraction coefficient is set to match the change trend, so as to reasonably avoid the inaccuracy of the airway airbag safety dynamic compensation interval caused by abnormal blood perfusion, thereby improving the efficiency of pressure dynamic compensation.

[0145] Specifically, when the pressure dynamic compensation unit optimizes the interval optimization process according to the pressure change acceleration, the pressure change acceleration Compare with the preset pressure change acceleration Vj0 and set Vj0=10Pa / h 2, judge the pressure change acceleration according to the comparison results, and optimize the contraction coefficient scx according to the judgment results, where:

[0146] when When ≤Vj0, the pressure dynamic compensation unit determines that the pressure change acceleration is normal and does not perform force optimization on the contraction coefficient scx;

[0147] when When Vj0 is higher, the pressure dynamic compensation unit determines that the pressure change acceleration is abnormal, and optimizes the contraction coefficient scx according to the force coefficient ld, setting ldy=1.57-0.23×e -0.38×（Vj-Vj0） , where e is the base of the natural logarithm, and the optimized shrinkage coefficient scx` is obtained. Set scx`=scx×ldy, replace the shrinkage coefficient scx with the optimized shrinkage coefficient scx`, and re-perform quadratic interval optimization on the adult clinical constraint Px1 and the child clinical constraint Px2 based on the optimized shrinkage coefficient scx`.

[0148] Specifically, the pressure dynamic compensation unit determines the acceleration of pressure change. In this embodiment, Vj0 is set to 10Pa / h. 2 , avoid frequent force optimization caused by small fluctuations in pressure change acceleration, thereby reducing misjudgment, and avoid large fluctuations in pressure change acceleration, which makes it difficult to accurately capture abnormal pressure change acceleration. When the pressure change acceleration is abnormal, the contraction coefficient scx is increased according to the force coefficient. The change trend of the contraction coefficient and the pressure change acceleration is nonlinear. In the early stage of the pressure change acceleration, the contraction coefficient needs to be quickly increased and the force optimization needs to be performed in time. In the later stage, the pressure change acceleration trend tends to be flat. The force coefficient is set to match the change trend, so as to reasonably avoid excessive pressure changes and insufficient contraction force in the airway bag safety dynamic compensation range when the blood flow abnormality is serious, thereby improving the efficiency of pressure dynamic compensation.

[0149] Specifically, when the control instruction generation unit obtains the pressure trend according to the ambient pressure prediction value and the airway airbag safety dynamic compensation interval, when the target user is an adult, the pressure change acceleration is calculated. The predicted ambient pressure value P is compared with the second preset pressure change acceleration Vj01 and the adult clinical restraint, which includes the lower limit value Pmin of the airway airbag safety dynamic compensation interval and the upper limit value Pmax1 of the adult airway airbag safety dynamic compensation interval. Vj01 is set to 0, Pmin = 12 cmH2O, and Pmax1 = 35 cmH2O. The high-altitude pressure risk is judged based on the comparison results, and the pressure trend is output based on the judgment results, where:

[0150] when >Vj01 and P>Pmax1, the control instruction generation unit determines that the high altitude pressure risk situation is risky and outputs the risk as a pressure trend;

[0151] when >Vj01 and Pmin<P≤Pmax1, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0152] when >Vj01 and P≤Pmin, the control instruction generation unit determines that the high-altitude pressure risk situation is risky, controls the airway bag pressure according to the airway bag pressure control method, and outputs the risk as a pressure trend;

[0153] when ≤Vj01 and P>Pmax1, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0154] when ≤Vj01 and Pmin<P≤Pmax1, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0155] when ≤Vj01 and P≤Pmin, the control instruction generating unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0156] When the target user is a child, the pressure change acceleration The predicted ambient pressure value P is compared with the second preset pressure change acceleration Vj01 and the child clinical restraint, which includes the lower limit value Pmin of the airway airbag safety dynamic compensation interval and the upper limit value Pmax2 of the child airway airbag safety dynamic compensation interval. Vj01 is set to 0, Pmin = 12 cmH2O, and Pmax2 = 25 cmH2O. The high-altitude pressure risk is judged based on the comparison results, and the pressure trend is output based on the judgment results, where:

[0157] when >Vj01 and P>Pmax2, the control instruction generation unit determines that the high altitude pressure risk situation is risky and outputs the risk as a pressure trend;

[0158] when >Vj01 and Pmin<P≤Pmax2, the control instruction generation unit determines that the high-altitude pressure risk is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0159] when >Vj01 and P≤Pmin, the control instruction generation unit determines that the high-altitude pressure risk situation is risky, controls the airway bag pressure according to the airway bag pressure control method, and outputs the risk as a pressure trend;

[0160] when ≤Vj01 and P>Pmax2, the control instruction generation unit determines that the high altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0161] when ≤Vj01 and Pmin<P≤Pmax2, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend;

[0162] when ≤Vj01 and P≤Pmin, the control instruction generating unit determines that the high altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend.

[0163] Specifically, the second preset pressure change acceleration refers to a preset value for limiting the pressure change acceleration when judging the high-altitude pressure risk situation. The high-altitude pressure risk situation refers to the risk level of sudden increase and decrease in high-altitude pressure. The high-altitude pressure risk situation includes the high-altitude pressure risk situation being risky and the high-altitude pressure risk situation being non-risky.

[0164] Specifically, the control instruction generation unit obtains the pressure trend according to the age of the target user. In this embodiment, Vj01=0 is set to limit the minimum value of the pressure change acceleration when judging the high-altitude pressure risk situation, accurately capture the changes in the pressure change acceleration and the ambient pressure prediction value, and timely judge the presence or absence of high-altitude pressure risk to facilitate subsequent regulation of the airbag pressure.

[0165] Specifically, the control instruction generation unit generates a control instruction according to the pressure trend through a control instruction generation method, and the control instruction generation method includes:

[0166] Step S01, when the target user is an adult, calculate the sudden pressure prediction safety difference ΔP1 and the sudden pressure drop prediction safety difference ΔP2 based on the ambient pressure prediction value P, the lower limit value Pmin of the airway airbag safety dynamic compensation interval, and the upper limit value Pmax1 of the adult airway airbag safety dynamic compensation interval, and set ΔP1=P-Pmax1 and ΔP2=Pmin-P to obtain the sudden pressure prediction safety difference ΔP1 and the sudden pressure drop prediction safety difference ΔP2;

[0167] When the target user is a child, the predicted safety difference ΔP1 for sudden pressure increase and the predicted safety difference ΔP2 for sudden pressure decrease are calculated based on the predicted ambient pressure value P, the lower limit Pmin of the airway airbag safety dynamic compensation interval, and the upper limit Pmax2 of the airway airbag safety dynamic compensation interval for children. ΔP1=P-Pmax2 and ΔP2=Pmin-P are set to obtain the predicted safety difference ΔP1 for sudden pressure increase and the predicted safety difference ΔP2 for sudden pressure decrease.

[0168] Step S02, initializing the PID control algorithm to obtain an initialized PID control algorithm;

[0169] In step S03 , the predicted safety difference of sudden pressure increase ΔP1 and the predicted safety difference of sudden pressure decrease ΔP2 are input into the initialized PID control algorithm to obtain a control instruction.

[0170] Specifically, the PID control algorithm refers to an algorithm for regulating the airbag pressure, and the algorithm initialization refers to the process of setting the parameters in the PID control algorithm. This embodiment does not limit the specific method of algorithm initialization. Relevant technical personnel in this field can freely choose according to actual needs, such as software settings. The control instruction refers to the instruction for regulating the airbag pressure obtained according to the initialized PID control algorithm. For example, when the control amount is positive and the control amount is 1.2, the airbag pressure will be reduced by 1.2 cmH2O as a control instruction output. When the control amount is negative and the control amount is 1.2, the airbag pressure will be increased by 1.2 cmH2O as a control instruction output. The airbag pressure refers to the pressure value inside the airway airbag.

[0171] Specifically, the control instruction generation unit generates control instructions so as to control the airbag pressure according to the control instructions when there is a risk of sudden increase or decrease in high-altitude pressure, thereby improving the environmental adaptability of dynamic pressure compensation.

[0172] Specifically, the pressure control unit controls the airbag pressure according to the control instruction.

[0173] It is understandable that this embodiment does not limit the specific method of controlling the airbag pressure according to the control instruction. Relevant technical personnel in this field can freely choose according to actual needs, such as inputting the control instruction into the pressure regulating valve to control the airbag pressure.

[0174] Specifically, the pressure control unit controls the airbag pressure through control instructions, so as to adjust the airbag pressure in real time according to the environmental conditions, thereby improving the control efficiency and environmental adaptability of the simulated high-altitude pressure adaptive wounded first aid dynamic compensation device.

[0175] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A dynamic compensation device for simulated high-altitude pressure self-adaptation of wounded first aid, characterized in that: The device comprises an airway (1), an air bag (2), an air pump (3), a sensor node group (4), an adaptive control module (5) and a sealing connection (6), wherein: An airway (1) connected to an air bag (2), an air pump (3) and a sealing connector (6) for supplying oxygen to a target user; an air bag (2) connected to the airway (1) for sealing the target user's laryngeal cavity; an air pump (3) connected to the sealing connector (6), the airway (1) and the adaptive control module (5) for delivering oxygen to the airway (1); A sensor node group (4), connected to the adaptive control module (5), is used to collect target emergency data; An adaptive control module (5) is connected to the sensor node group (4) and the air pump (3) and is used to control the simulated high-altitude pressure adaptive target user emergency dynamic compensation device according to target emergency data, wherein the control includes acquiring the target emergency data, acquiring the environmental pressure prediction value, performing error adjustment and error update on the environmental pressure prediction value, generating an airway airbag safety dynamic compensation interval, performing interval optimization and force optimization on the airway airbag safety dynamic compensation interval, acquiring the pressure trend and generating a control instruction, and controlling the airbag pressure according to the control instruction; A sealing connector (6) is connected to the air pump (3) and the air channel (1) and is used to connect the air pump (3) and the air channel (1).

2. The simulated high-altitude pressure adaptive wounded first aid dynamic compensation device according to claim 1 is characterized in that: The adaptive control module includes: A data acquisition unit, used to acquire target first aid data; an environmental pressure prediction unit, configured to obtain an environmental pressure prediction value based on target emergency data using an environmental pressure prediction value acquisition method, obtain an environmental pressure prediction value, perform error adjustment on the environmental pressure prediction value based on an average absolute error value, and perform error update on the error adjustment process based on a pressure change acceleration; a pressure dynamic compensation unit, configured to generate an airway airbag safety dynamic compensation interval according to target emergency data using an airway airbag safety dynamic compensation interval generation method, optimize the airway airbag safety dynamic compensation interval according to the target emergency data, and optimize the intensity of the interval optimization process according to the pressure change acceleration; a control instruction generation unit, configured to obtain a pressure trend based on an ambient pressure prediction value and an airway airbag safety dynamic compensation interval, and to generate a control instruction based on the pressure trend using a control instruction generation method; The pressure control unit is used to control the airbag pressure according to the control instructions.

3. The simulated high-altitude pressure adaptive wounded first aid dynamic compensation device according to claim 2 is characterized in that: The environmental pressure prediction unit obtains the environmental pressure prediction value according to the target first aid data through an environmental pressure prediction value acquisition method, and the environmental pressure prediction value acquisition method includes: Step A01, acquiring a historical environmental parameter set according to target emergency data; Step A02: Divide the historical environmental parameter set into a 70% environmental training set and a 30% environmental validation set; Step A03, initializing parameters of the spatiotemporal convolutional neural network model to obtain an initialized spatiotemporal convolutional neural network model; Step A04: inputting the environment training set into the initialized spatiotemporal convolutional neural network model for model training to obtain a trained spatiotemporal convolutional neural network model; Step A05: Based on the ambient temperature at time t1 , amount of substance n, gas volume and the ideal gas constant Predict environmental pressure at time t1 Calculate and set , get the predicted environmental pressure at time t1 ; Step A06: Predict the environmental pressure based on time t1 , high altitude pressure at time t1 and time steps For the basic loss function Calculate and set ,in, is the order of the time steps; Step A07, according to the number of time steps , predicted environmental pressure at time t1 , ambient temperature at time t1 , actual pressure value at time t-1 , ambient temperature at time t-1 Pressure-temperature loss function Calculate and set , and obtain the pressure-temperature loss function ; Step A08, according to the time step , predicted environmental pressure at time t1 , ambient temperature at time t1 , the coefficients of the gas state equation Loss function for the gas state equation Calculate and set , and obtain the gas state equation loss function ; Step A09, according to the time step , predicted environmental pressure at time t1 , ambient temperature at time t1 , actual pressure value at time t-1 , ambient temperature at time t-1 , prediction step length and the pressure-temperature change coefficient Loss function for physical constraints on pressure change rate Calculate and set , 3 seconds ≤ Tw ≤ 4 seconds, and the pressure change rate physical constraint loss function is obtained ; Step A10, based on the basic loss function , pressure-temperature loss function , gas state equation loss function , pressure change rate physical constraint loss function , pressure temperature coefficient α1, gas state coefficient α2 and pressure change rate coefficient α3 to calculate the total loss function Lt, set Lt= +α1× +α2× +α3× , get the total loss function Lt; Step A11: input the environmental verification set into the trained spatiotemporal convolutional neural network model, and optimize the loss of the trained spatiotemporal convolutional neural network model according to the total loss function to obtain an environmental pressure prediction model; Step A12: input the high altitude pressure into the environmental pressure prediction model to obtain the environmental pressure prediction value.

4. The simulated high-altitude pressure adaptive wounded first aid dynamic compensation device according to claim 3 is characterized in that: When the environmental pressure prediction unit performs error adjustment on the environmental pressure prediction model according to the average absolute error, the error is adjusted according to the number of prediction samples. , actual pressure value and pressure prediction values Mean absolute error Calculate and set ,in, To predict the order of samples, get the average absolute error , the mean absolute error The average absolute error with the preset For comparison, set 0.25≤ ≤0.5, judge the compliance of the average absolute error value with the standard according to the comparison results, and make error adjustments to the pressure temperature coefficient α1, gas state coefficient α2 and pressure change rate coefficient α3 according to the judgment results, where: when ≤ When , the environmental pressure prediction unit determines that the compliance of the average value of the absolute error is compliance, and does not perform error adjustment on the pressure temperature coefficient α1, the gas state coefficient α2, and the pressure change rate coefficient α3; when > When the environmental pressure prediction unit determines that the absolute error average value is not up to standard, the error coefficient Adjust the pressure temperature coefficient α1, gas state coefficient α2 and pressure change rate coefficient α3 to set the error. , where e is the base of the natural logarithm, and the adjusted pressure-temperature coefficient α1`, the adjusted gas state coefficient α2`, and the adjusted pressure change rate coefficient α3` are obtained. Set α1`=α1×β, α2`=α2×β, α3`=α3×β, replace the pressure-temperature coefficient α1, gas state coefficient α2, and pressure change rate coefficient α3 with the adjusted pressure-temperature coefficient α1`, adjusted gas state coefficient α2`, and adjusted pressure change rate coefficient α3`, and recalculate the total loss function Lt.

5. The simulated high-altitude pressure adaptive wounded first aid dynamic compensation device according to claim 4 is characterized in that: When the environmental pressure prediction unit performs error update on the error adjustment process according to the pressure change acceleration, the environmental pressure prediction value , the environmental pressure predicted at the previous moment , predict environmental pressure at the next moment and prediction step length Acceleration of pressure change Calculate and set , and the pressure change acceleration is obtained , the pressure change acceleration Acceleration with preset pressure change Compare and set =10Pa / h 2 , judge the pressure change acceleration according to the comparison results, and calculate the preset absolute error average value according to the judgment results. Perform error update, where: when ≤ When the ambient pressure prediction unit determines that the pressure change acceleration is normal, the preset absolute error average value is not set. Perform error update; when > When the environmental pressure prediction unit determines that the pressure change acceleration is abnormal, the preset absolute error average value Perform error update according to the acceleration coefficient For the preset absolute error mean Perform error update and set , get the updated preset absolute error average `, set `= × , the preset absolute error average Replaced with the preset average absolute error after update `, and average the absolute error and the average absolute error of the preset value after update `Re-compare.

6. The simulated high-altitude pressure adaptive wounded first aid dynamic compensation device according to claim 5 is characterized in that: The pressure dynamic compensation unit generates an airway airbag safety dynamic compensation interval according to the target emergency data using an airway airbag safety dynamic compensation interval generation method, wherein the airway airbag safety dynamic compensation interval generation method includes: Step B01: Acquire the generator and discriminator, and initialize the generator and discriminator to obtain the initial generator and initial discriminator; Step B02: Input the blood oxygen, heart rate, respiratory rate, and tracheal diameter in the target emergency data as individual feature data into an initial generator to obtain an initial airway airbag safety dynamic compensation interval Px, wherein the initial airway airbag safety dynamic compensation interval Px includes an adult clinical restraint Px1 and a child clinical restraint Px2; Step B03: Set the lower limit Pmin of the airway bag safety dynamic compensation interval and the upper limit Pmax1 of the airway bag safety dynamic compensation interval for adults as the adult clinical constraint Px1, and set the lower limit Pmin of the airway bag safety dynamic compensation interval and the upper limit Pmax2 of the airway bag safety dynamic compensation interval for children as the child clinical constraint Px2, and set Pmin≤Px1≤Pmax1, Pmin≤Px≤Pmax2, Pmax1=35cmH2O, Pmax2=25cmH2O, and Pmin=12cmH2O; Step B04: inputting individual feature data, adult clinical restraints, child clinical restraints, and the actual airway bag safety dynamic compensation interval into an initial discriminator to obtain a final probability value Gp; Step B05: Compare the final probability value Gp with the preset probability value Gp0, setting 80%≤Gp0≤100%, and determine whether the final probability value meets the standard based on the comparison result. Then, output the airway bag safety dynamic compensation interval based on the determination result, where: When Gp<Gp0, the pressure dynamic compensation unit determines that the final probability value does not meet the standard. When the target user is an adult, the adult clinical restraint is output as the airway bag safety dynamic compensation interval; when the target user is a child, the child clinical restraint is output as the airway bag safety dynamic compensation interval; When Gp≥Gp0, the pressure dynamic compensation unit determines that the final probability value meets the standard, and outputs the initial airway airbag safety dynamic compensation interval as the airway airbag safety dynamic compensation interval.

7. The simulated high-altitude pressure adaptive wounded first aid dynamic compensation device according to claim 6 is characterized in that: When the pressure dynamic compensation unit optimizes the airway bag safety dynamic compensation interval generation method based on the target emergency data, the heart rate variation frequency Fx in the target emergency data is compared with the preset heart rate variation frequency Fx0, and Fx is set to 100 beats / minute. The heart rate variation frequency is judged based on the comparison result, and the adult clinical restraint Px1 and the child clinical restraint Px2 are interval-optimized based on the judgment result, wherein: When Fx≥Fx0, the pressure dynamic compensation unit determines that the heart rate change frequency is normal, and does not perform interval optimization on the adult clinical restraint Px1 and the child clinical restraint Px2; When Fx<Fx0, the pressure dynamic compensation unit determines that the heart rate change frequency is abnormal, and performs interval optimization on the adult clinical restraint Px1 and the child clinical restraint Px2. The interval optimization of the adult clinical restraint Px1 and the child clinical restraint Px2 is performed according to the variation coefficient ap, and ap=1.27-0.14×e -0.7×（Fx0-Fx） , where e is the base of the natural logarithm. The optimized adult clinical constraint Px1` and the optimized child clinical constraint Px2` are obtained. Px1`=Px1×ap is set. When Px1`>35cmH2O, Px1`=35cmH2O and Px2`=Px2×ap are set. When Px2`>25cmH2O, Px2`=25cmH2O are set. The adult clinical constraint Px1 is replaced with the optimized adult clinical constraint Px1`, and the child clinical constraint Px2 is replaced with the optimized child clinical constraint Px2`, and the final probability value Gp is ​​re-obtained.

8. The simulated high-altitude pressure adaptive wounded first aid dynamic compensation device according to claim 7 is characterized in that: When the pressure dynamic compensation unit performs interval optimization on the airway bag safety dynamic compensation interval generation method based on the target emergency data, the blood flow abnormality value Pb is calculated based on the blood perfusion volume PUs and the baseline value PUb in the target emergency data, and Pb is set to (PUb-PUs) / PUb×100% to obtain the blood flow abnormality value Pb. The blood flow abnormality value Pb is compared with the preset blood flow abnormality value Pb0, and the situation of the blood flow abnormality is judged based on the comparison result. Based on the judgment result, the adult clinical restraint Px1 and the child clinical restraint Px2 are secondary interval optimized, wherein: When Pb≤Pb0, the pressure dynamic compensation unit determines that the abnormal blood flow value is not serious, and does not perform secondary interval optimization on the adult clinical constraint Px1 and the child clinical constraint Px2; When Pb>Pb0, the pressure dynamic compensation unit determines that the blood flow abnormality is serious, and does not perform secondary interval optimization on the adult clinical constraint Px1 and the child clinical constraint Px2. Instead, the adult clinical constraint Px1 and the child clinical constraint Px2 are optimized secondary interval according to the contraction coefficient scx, and 0.4≤scx≤0.8 is set to obtain the secondary optimized adult clinical constraint Px1`` and the secondary optimized child clinical constraint Px2``. Px1``=Px1×scx is set. When Px1``<12cmH2O, Px1``=12cmH2O and Px2``=Px2×scx are set. When Px2``<12cmH2O, Px2``=12cmH2O are set. The adult clinical constraint Px1 is replaced with the secondary optimized adult clinical constraint Px1``, and the child clinical constraint Px2 is replaced with the secondary optimized child clinical constraint Px2``, and the final probability value Gp is ​​reacquired.

9. The simulated high-altitude pressure adaptive wounded first aid dynamic compensation device according to claim 8, characterized in that: When the pressure dynamic compensation unit optimizes the interval optimization process according to the pressure change acceleration, the pressure change acceleration Acceleration with preset pressure change Compare and set =10Pa / h 2 , judge the pressure change acceleration according to the comparison results, and optimize the contraction coefficient scx according to the judgment results, where: when ≤ When , the pressure dynamic compensation unit determines that the pressure change acceleration is normal and does not perform force optimization on the contraction coefficient scx; when > When the pressure dynamic compensation unit determines that the pressure change acceleration is abnormal, the contraction coefficient scx is optimized according to the force coefficient ld, and ldy=1.57-0.23×e -0.38×（Vj-Vj0） , where e is the base of the natural logarithm, and the optimized shrinkage coefficient scx` is obtained. Set scx`=scx×ldy, replace the shrinkage coefficient scx with the optimized shrinkage coefficient scx`, and re-perform quadratic interval optimization on the adult clinical constraint Px1 and the child clinical constraint Px2 based on the optimized shrinkage coefficient scx`.

10. The simulated high-altitude pressure adaptive wounded first aid dynamic compensation device according to claim 9, characterized in that: When the control instruction generating unit obtains the pressure trend according to the ambient pressure prediction value and the airway airbag safety dynamic compensation interval, when the target user is an adult, the pressure change acceleration is calculated. The predicted ambient pressure value P is compared with the second preset pressure change acceleration Vj01 and the adult clinical restraint, which includes the lower limit value Pmin of the airway airbag safety dynamic compensation interval and the upper limit value Pmax1 of the adult airway airbag safety dynamic compensation interval. Vj01 is set to 0, Pmin = 12 cmH2O, and Pmax1 = 35 cmH2O. The high-altitude pressure risk is judged based on the comparison results, and the pressure trend is output based on the judgment results, where: when >Vj01 and P>Pmax1, the control instruction generation unit determines that the high altitude pressure risk situation is risky and outputs the risk as a pressure trend; when >Vj01 and Pmin<P≤Pmax1, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend; when >Vj01 and P≤Pmin, the control instruction generation unit determines that the high-altitude pressure risk situation is risky, controls the airway bag pressure according to the airway bag pressure control method, and outputs the risk as a pressure trend; when ≤Vj01 and P>Pmax1, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend; when ≤Vj01 and Pmin<P≤Pmax1, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend; when ≤Vj01 and P≤Pmin, the control instruction generating unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend; When the target user is a child, the pressure change acceleration The predicted ambient pressure value P is compared with the second preset pressure change acceleration Vj01 and the child clinical restraint, which includes the lower limit value Pmin of the airway airbag safety dynamic compensation interval and the upper limit value Pmax2 of the child airway airbag safety dynamic compensation interval. Vj01 is set to 0, Pmin = 12 cmH2O, and Pmax2 = 25 cmH2O. The high-altitude pressure risk is judged based on the comparison results, and the pressure trend is output based on the judgment results, where: when >Vj01 and P>Pmax2, the control instruction generation unit determines that the high altitude pressure risk situation is risky and outputs the risk as a pressure trend; when >Vj01 and Pmin<P≤Pmax2, the control instruction generation unit determines that the high-altitude pressure risk is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend; when >Vj01 and P≤Pmin, the control instruction generation unit determines that the high-altitude pressure risk situation is risky, controls the airway bag pressure according to the airway bag pressure control method, and outputs the risk as a pressure trend; when ≤Vj01 and P>Pmax2, the control instruction generation unit determines that the high altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend; when ≤Vj01 and Pmin<P≤Pmax2, the control instruction generation unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend; when ≤Vj01 and P≤Pmin, the control instruction generating unit determines that the high-altitude pressure risk situation is no risk, does not control the airway bag pressure according to the airway bag pressure control method, and outputs no risk as the pressure trend; The control instruction generation unit generates a control instruction according to the pressure trend by using a control instruction generation method, and the control instruction generation method includes: Step S01, when the target user is an adult, calculate the sudden pressure prediction safety difference ΔP1 and the sudden pressure prediction safety difference ΔP2 based on the ambient pressure prediction value P, the lower limit value Pmin of the airway airbag safety dynamic compensation interval, and the upper limit value Pmax1 of the adult airway airbag safety dynamic compensation interval, and set ΔP1=P-Pmax1 and ΔP2=Pmin-P to obtain the sudden pressure prediction safety difference ΔP1 and the sudden pressure prediction safety difference ΔP2; When the target user is a child, the predicted safety difference ΔP1 for sudden pressure increase and the predicted safety difference ΔP2 for sudden pressure decrease are calculated based on the predicted ambient pressure value P, the lower limit Pmin of the airway airbag safety dynamic compensation interval, and the upper limit Pmax2 of the airway airbag safety dynamic compensation interval for children. ΔP1=P-Pmax2 and ΔP2=Pmin-P are set to obtain the predicted safety difference ΔP1 for sudden pressure increase and the predicted safety difference ΔP2 for sudden pressure decrease. Step S02, initializing the PID control algorithm to obtain an initialized PID control algorithm; Step S03, inputting the sudden pressure increase prediction safety difference ΔP1 and the sudden pressure decrease prediction safety difference ΔP2 into the initialized PID control algorithm to obtain a control instruction; The pressure control unit controls the airbag pressure according to the control instruction.

Images