A high-efficiency regulation system and method for plateau hypoxic environment damage

Abstract

The application discloses a kind of highland hypoxic environment damage high-efficiency regulation system and method, it is related to human hypoxic injury analysis, detection and regulation technical field, including data monitoring module, signal screening module, decision oxygen module and monitoring interaction module;With data monitoring module, real-time acquisition and highland hypoxic adaptability related physiological state;With signal screening module, based on test data, physiological data with high modeling value is obtained by optimization algorithm, and the discrete state space model of physiological state is constructed;With decision oxygen module, oxygen concentration decision is determined by predictive control algorithm, and oxygen supply regulation is realized;With monitoring interaction module, data storage, record and display are carried out, and warning and prediction dangerous situation are issued.Therefore, by using the above method, effective oxygen supply, blood oxygen dynamic monitoring and real-time alarm can be realized, and the health and safety of individuals located in high-altitude areas and other hypoxic environments can be ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of human hypoxia injury analysis, detection and regulation, and in particular to a high-efficiency regulation system and method for high-altitude hypoxia environmental injury. BACKGROUND

[0002] The harm of hypoxic environment to human body is multifaceted, especially in high-altitude areas and certain special places. Long-term exposure to hypoxic conditions can trigger a variety of physiological abnormalities, and in severe cases, even threaten life safety. The damage of hypoxia to the human body shows a complex physiological response process, including but not limited to decreased cardiopulmonary function, insufficient tissue oxygen supply, metabolic disorder, etc. These problems can cause the body to produce a series of physiological stress reactions, and over time, more serious chronic health problems such as high-altitude heart disease, chronic hypoxic encephalopathy, etc. Therefore, in view of the impact of hypoxic environment on human health, it is of great significance to establish an accurate injury model and carry out effective regulation to protect human health in hypoxic environment.

[0003] At present, the medical community has a certain degree of understanding of hypoxic injury, and has gradually established a corresponding theoretical framework. For example, through data-driven modeling methods, combined with biological signal monitoring technology, the physiological state of individuals in a hypoxic environment can be tracked in real time, such as blood oxygen saturation, heart rate, respiratory rate, and other important indicators. These data can be used to establish a dynamic model of hypoxic injury, assess the health risks individuals face, and intervene effectively through control strategies. Based on real-time monitoring data, combined with artificial intelligence technology, the oxygen supply and environmental conditions of individuals can be adjusted in real time to minimize the negative effects of hypoxia on the body, thereby reducing the risk of chronic diseases and improving physiological adaptability. In addition, the study of hypoxic injury models can also be applied to the health management of special populations such as pilots, high-altitude athletes, and residents in high-altitude areas, helping them better adapt to hypoxic environments and prevent diseases caused by hypoxia. Through accurate modeling and regulation, physiological adaptability in hypoxic environments can be greatly improved, ensuring the safety and health of individuals, and achieving broader social benefits.

[0004] However, existing hypoxic injury models are based on learning a large number of physiological signals, but in actual application, they cannot achieve ideal results. This is because the process noise generated by the complexity and uncertainty of the physiological system is difficult to control and analyze, and it also consumes a lot of resources. In addition, existing system modeling methods do not consider the value of data itself, resulting in an increase in data volume that cannot guarantee a direct improvement in modeling accuracy. Therefore, considering the power consumption and computational resource constraints of wearable devices, it is particularly important to design a lightweight and efficient injury modeling method.

[0005] On the other hand, in order to cope with the damage of high altitude hypoxia to the body, relevant research has proposed an effective method of regulating through an oxygen-rich environment, but due to the large individual difference of hypoxic injury, the precise regulation of low oxygen environment still faces challenges. In addition, the existing control regulation method is based on the open loop structure for oxygen delivery, for example, when the hypoxic response is relatively strong, the oxygen cylinder is used for active inhalation, or in the preset oxygen-rich mode, the low oxygen training device is used for high concentration oxygen supply. Although this method can achieve oxygen regulation to a certain extent, it lacks overall evaluation and prediction of future blood oxygen level trend, and it is difficult to maximize the intervention in the resource-limited plateau environment, and it is also difficult to ensure the optimality of blood oxygen control effect.

[0006] Therefore, how to design an intelligent oxygen supply system based on predictive control technology from the particularity of the plateau environment is a problem worthy of further study. This not only helps to improve the accuracy of blood oxygen control, but also in a complex and dynamic plateau environment, through reasonable resource allocation and control strategy, it can realize more efficient health intervention and protect the life safety and health level of individuals. SUMMARY

[0007] The purpose of the present application is to provide an efficient regulation system and method for plateau hypoxic environmental damage, which can solve the problems of limited oxygen supply in high altitude areas, large oxygen supply equipment, and lack of blood oxygen level trend estimation.

[0008] To achieve the above purpose, the present application provides an efficient regulation method for plateau hypoxic environmental damage, comprising the following steps:

[0009] S1, using a portable wearable device, real-time physiological state related to plateau hypoxic adaptation ability is obtained by photoplethysmography method;

[0010] S2, a discrete state space model is constructed based on physiological indicators, and the state of the human body in different environments is preliminarily tested to obtain test data of the entire cycle, and an optimization algorithm is used to determine a screening vector to obtain physiological data with high modeling value;

[0011] S3, based on the real-time physiological state, the oxygen supply concentration decision is determined by a predictive control algorithm, and the oxygen storage device or oxygen enrichment technology is used for regulation;

[0012] S4, according to the real-time monitoring of physiological state, oxygen supply concentration and oxygen supply decision, the storage, recording and display are carried out through the monitoring interaction module, and the alarm is issued for abnormal situation, prompting manual intervention, checking equipment and troubleshooting.

[0013] Preferably, the screening vector is determined by an optimization algorithm, as follows:

[0014]

[0015] s.t.1 T z=Nf

[0016] wherein X t (z) and U t (z) are physiological state data matrix and control input oxygen concentration data matrix obtained under the screening vector z respectively, the minimum singular value of matrix , is a vector with all elements being 1.

[0017] Preferably, the optimization algorithm includes solving a suboptimal solution by using a heuristic optimization algorithm, and then screening the overall physiological data.

[0018] Preferably, the predictive control algorithm determines the oxygen concentration decision, including:

[0019] setting the optimization step as T f , and solving the oxygen optimization problem to determine the optimal control parameter, i.e. the oxygen concentration decision, as follows:

[0020]

[0021] s.t.x0=x ini

[0022]

[0023] x k ∈X,k∈{0,1,…,T f}

[0024] u k ∈U,k∈{0,1,…,T f -1

[0025] wherein ||x k -r|| Q =(x k -r) T Q(x k -r), r is the desired health physiological index level, x k is the state vector of the physiological index at time k, u k is the control input oxygen concentration vector at time k, x ini is the initial state vector of the human body at the beginning of the control, is the physiological state response corresponding to X t (z) and U t (z), and Q and R are weight matrices allocated to the deviation of the physiological state from the desired value and the oxygen concentration in the regulation process, X, U represent the generalized inverse matrix, and X, U are safety constraints of controllable input under corresponding physiological state.

[0026] A high-efficiency regulation system for high-altitude hypoxic environment damage, comprising:

[0027] A data monitoring module is configured to acquire physiological data related to high-altitude adaptation capability in real time through a monitoring device, and perform data transmission with the monitoring interaction module and the decision oxygen supply module.

[0028] A signal screening module is configured to acquire a series of physiological data with high modeling value, and use the data as basic data of the decision oxygen supply module.

[0029] The decision oxygen supply module is configured to efficiently model the human hypoxic damage mode, and generate oxygen supply concentration decisions by using real-time monitored physiological data, safety and resource constraints, and a predictive control algorithm.

[0030] The monitoring interaction module is configured to record, store and display the signal information acquired by the decision oxygen supply module and the data monitoring module, set control targets and parameters, and alarm abnormal physiological states, and prompt and predict dangerous situations.

[0031] Preferably, the monitoring interaction module is integrated into a mobile terminal, including a computer and a mobile phone.

[0032] Preferably, the monitoring interaction module communicates with the data monitoring module, the signal screening module and the decision oxygen supply module through wireless or wired communication technology.

[0033] Therefore, the high-efficiency regulation system and method for high-altitude hypoxic environment damage have the following technical effects:

[0034] (1) In the data monitoring module, physiological states of the human body in the plateau environment are measured, and multiple related physiological indicators including blood oxygen saturation, heart rate, blood pressure, etc. are integrated, which can be embedded in wearable devices such as wristbands, and will not interfere with normal life.

[0035] (2) The signal screening module can filter out signal sequences with high modeling value from a large amount of measurement data through a predictive control algorithm, reduce the memory occupied by basic data, reduce the calculation complexity of the predictive control algorithm, and improve the control performance of the decision oxygen supply module.

[0036] (3) The decision oxygen supply module uses real-time physiological data and basic data acquired by the data screening module to achieve efficient modeling of the hypoxic damage mode and optimal oxygen uptake intelligent decision, avoids the modeling process of complex physiological models, fully considers the blood oxygen regulation performance in the whole time domain, and provides oxygen supply intervention strategies with maximum benefits on the basis of considering physiological limits, oxygen capacity and other additional constraints.

[0037] (4) Through the monitoring interaction module, the individual physiological database is built by enabling the communication connection between each sub-module, realizing the storage, utilization and sharing of a large amount of information, and realizing the health monitoring and alarm of the plateau residents.

[0038] The technical solutions of the present application are described in further detail below by means of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 It is a schematic diagram of an efficient regulation system for plateau hypoxic environment damage.

[0040] Figure 2 It is a flow chart of an efficient regulation method for plateau hypoxic environment damage. DETAILED DESCRIPTION

[0041] The present application can be explained in further detail by means of the following examples, the purpose of which is to protect all variations and improvements within the scope of the present application, and the present application is not limited to the following examples.

[0042] As shown in Figure 1 , the present application provides an efficient regulation system for plateau hypoxic environment damage, comprising:

[0043] The data monitoring module utilizes wearable physiological signal monitoring devices including wristbands, finger clips, etc. to monitor continuous physiological data related to plateau adaptation capacity, such as blood oxygen saturation, heart rate, etc.

[0044] The signal screening module, based on the data obtained by the data monitoring module, runs the corresponding data screening algorithm to obtain a series of physiological data with high modeling value as the basic data for the predictive control algorithm.

[0045] The decision oxygen supply module, based on the basic data screened out by the signal screening module, efficiently models the human hypoxic injury mode, runs the corresponding predictive control algorithm based on the real-time physiological monitoring data obtained by the data monitoring module and the safety and resource constraints, and provides oxygen using oxygen storage or oxygen collection technology such as oxygen tanks to realize oxygen concentration decision.

[0046] The monitoring interaction module is integrated into mobile terminals such as mobile phones and computers, and through wireless or wired communication technology, the monitored physiological signals, decision signals, and oxygen concentration signals are stored, recorded, and displayed, the control targets and parameters are set, and based on the real-time physiological state, an alarm is generated to prompt and predict dangerous situations.

[0047] As shown in Figure 2 , the present application provides an efficient regulation method for plateau hypoxic environment damage, comprising the following steps:

[0048] S1, using a bracelet, heart rate belt, crutch and other portable wearable devices to obtain continuous physiological data related to high altitude hypoxia adaptation ability, such as blood oxygen saturation, heart rate, etc.

[0049] Photoplethysmography (PPG) is a widely used physiological signal detection method that can non-invasively measure a variety of physiological parameters. Specifically, the detection device is embedded with an LED light source, and when data needs to be detected, the light source will be directed to the skin of the measured part, such as the fingertips, earlobes, nose, etc. Because the amount of light absorbed changes with the change of the material, the light is absorbed by each tissue to different degrees, and the reflected light is received by a photosensitive sensor and converted into an electrical signal. After analog-to-digital conversion, it is decomposed into a direct current component related to blood flow and an alternating current component related to pulsation. Among them, the alternating current component is mainly caused by the change of blood flow in the blood vessels and its components (such as hemoglobin, etc.) caused by the change of the amount of light absorption caused by the heart beat. By processing and calculating this alternating current signal, different physiological signals can be measured. Therefore, through PPG technology, blood oxygen saturation and heart rate can be measured as follows:

[0050] (1) Measurement of blood oxygen saturation: The content of hemoglobin carried by red blood cells is closely related to blood oxygen saturation and will affect the degree of light absorption by blood. By detecting the light intensity emitted after being absorbed by human tissues through PPG technology, using the difference in light absorption coefficient of oxygenated hemoglobin and reduced hemoglobin at different wavelengths, and combining the Beer-Lambert optical law, the blood oxygen content can be inferred, and the soft measurement of blood oxygen saturation can be completed.

[0051] (2) Measurement of heart rate: The change signal of the fluctuation of peripheral microvascular arterial blood volume presents periodic characteristics, and heart rate mainly corresponds to the period of the pulse wave. By performing time domain analysis and filtering on the PPG signal, the number of heartbeats per minute can be obtained according to the number of wave crests.

[0052] S2, for the physiological model, a discrete state space model is used in this embodiment, as follows:

[0053] x k+1 =Ax k +Bu k +w k ;

[0054] In the formula, x k is a state vector composed of measured physiological indicators such as blood oxygen saturation, heart rate signal of the human body at time k, u k is the control input oxygen concentration at time k, and w k is the process noise at time k.

[0055] Considering the difference between individuals, the basic data corresponding to the physiological system model needs to be tested for different individuals and different times, so before the actual adjustment process starts, a simple test needs to be carried out on the human body for different environments. According to the actual situation, the test step is set to N t , the basic signal length is N f , where N f ≤N t , the initial state vector of the human body is , the oxygen concentration sequence is , and the corresponding human physiological state sequence is The data obtained in the entire test period is recorded in the following matrix form where X t , U t respectively represent the physiological state matrix and the oxygen concentration matrix, represent the physiological state response matrix corresponding to X t , U t .

[0056] At the same time, a 0 / 1 vector, i.e. a screening vector z, is set:

[0057]

[0058] In the formula, z i ∈{0,1}, where there is only one element of N f with value 1. z i =1 represents that the data group is selected into the basic data, and vice versa. Set X t (z), U t (z), respectively represent the data matrix screened out under the screening vector z. For example, set to 1, then

[0059] The screening vector is realized by solving the following 0 / 1 optimization problem:

[0060]

[0061] s.t.1 T z=N f

[0062] In the formula, is recorded as the minimum singular value of the matrix , and all elements are 1.

[0063] ​Considering that the traversal method may take a long time to calculate when the data volume is large, it is difficult to implement, and the greedy algorithm or particle swarm algorithm and other heuristic optimization algorithms can be preferred to solve the suboptimal solution in an approximate manner, filter all data, and pass the basic data to the subsequent oxygen allocation module, so that it uses a small amount of data to model the human body hypoxia damage mode to complete the oxygen supply decision, and realizes effective oxygen concentration regulation.

[0064] S3, according to the physiological state indicated by the data monitoring module, running the corresponding oxygen supply control algorithm, using the oxygen storage device or oxygen enrichment technology, combined with the oxygen allocation equipment such as the breathing mask, realizing the oxygen allocation decision set by the algorithm, as follows:

[0065] The optimization step is set to T f The optimal control parameter of each step can be obtained by solving the following optimization problem:

[0066]

[0067] s.t.x0=x ini

[0068]

[0069] x k ∈N,k∈{0,1,…,T f}

[0070] u k ∈U,k∈{0,1,…,T f -1}

[0071] In the formula r is the expected health physiological index level, x ini is the initial state vector of the human body at the beginning of the regulation; ||x k -r|| Q , ||u k || R (x k -r) T Q(x k -r) and Where Q, R are the weight matrices allocated to the physiological state deviation from the expected value and the oxygen concentration during the adjustment process; represents the generalized inverse matrix; X, U are the safety constraints of the controllable input of the physiological state.

[0072] After optimization, the optimal input sequence is recorded as The input sequence represents the optimal choice of future oxygen allocation decision at the current time, but because the algorithm is updated online, the input at the future time will be determined by the new optimal input sequence calculated at the future time. Therefore, the current oxygen allocation decision is And the rest of the parameters are not utilized. The gas mixture ratio can be selected to make decisions on the plains By writing control algorithms in the micro control unit, the gas pipeline conduction state is manipulated to achieve proportional regulation of oxygen-rich gas. For the high-altitude environment with thin oxygen, molecular sieve oxygen generation technology can be used to provide oxygen. Zeolite molecular sieve is used as the adsorbent, and pressure swing adsorption technology is used. In the pressure increasing stage, air is adsorbed as raw material, and then the pressure is reduced to separate oxygen and nitrogen. Medical high-purity oxygen is obtained through pressure cycling. Then it is stored by the oxygen storage device, and combined with the oxygen supply device to make decisions

[0073] S4, using the monitoring and interaction module integrated in mobile terminals such as mobile phones and computers, the physiological signals, decision signals, and oxygen concentration signals monitored are stored, recorded, and displayed through wired or wireless communication technology, the expected state setting function is provided, and the alarm is generated based on the real-time physiological state to prompt and predict dangerous situations.

[0074] Considering the mobility of the use scenario and the main requirement of small-range communication, Bluetooth technology can be used to achieve near-field data transmission and exchange, including real-time physiological data transmission by the data monitoring module, oxygen supply decision and oxygen concentration transmission by the decision oxygen supply module. In addition, in order to facilitate the viewing of human and oxygen supply system data, the monitoring and interaction module needs to have a display and interaction interface to dynamically monitor and display the current vital sign parameters, provide an interface to set the expected control interval, and generate an alarm to remind manual intervention when the human body or oxygen supply system is abnormal. The alarm needs to: prompt the physiological signal exceeding the safety threshold; prompt the violation of the internal preset safety constraints of the controller during the operation of the processing system; and prompt the connection abnormality or sudden interruption of the main processing equipment. When the alarm occurs, the closed-loop system should be closed in time, the safe oxygen supply amount is provided manually, the equipment is checked, and the problem is investigated.

[0075] Therefore, the present application adopts the above-mentioned efficient regulation system and method for high-altitude hypoxic environment damage, which has the integrated functions of continuous monitoring, dynamic evaluation, and closed-loop intervention, can realize effective oxygen supply, dynamic blood oxygen monitoring, and real-time alarm, and guarantees the health and safety of individuals in hypoxic environments such as high-altitude areas.

[0076] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application and not to limit them. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or equivalently replace the technical solutions of the present application, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present application.

Claims

1. A high-efficiency regulation system for high-altitude hypoxic environment damage, characterized in that, Comprise: Data monitoring module for real-time acquisition of physiological data related to highland adaptation ability by monitoring equipment, and data transmission with monitoring interaction module and decision oxygen supply module, specifically: using portable wearable equipment, real-time acquisition of physiological state related to highland hypoxia adaptation ability by photoplethysmography, manual configuration of oxygen supply concentration, preliminary test of physiological state change of human body under different oxygen supply concentration, and obtaining of "physiological state-oxygen supply concentration" test data in the whole cycle; Signal screening module for obtaining a series of physiological data with high modeling value and using it as basic data of decision oxygen supply module, specifically: determining screening vector by optimization algorithm, and then obtaining physiological data with high modeling value, and then constructing state space model for physiological state; Determine the screening vector by optimization algorithm, as follows: wherein , are the physiological state data matrix and the control input oxygen supply concentration data matrix, respectively, obtained under the screening vector , denoted by the matrix the smallest singular value of the matrix is a vector with elements equal to 1, is the test step size, is the base signal length; Decision oxygen supply module for efficient modeling of human hypoxia injury mode, and using real-time monitored physiological data, safety and resource constraints to generate oxygen supply concentration decision by predictive control algorithm, specifically: based on real-time acquired physiological state, determining oxygen supply concentration decision by predictive control algorithm, and using oxygen storage equipment or oxygen enrichment technology for regulation and control; Monitoring interaction module for recording, storing and displaying signal information obtained by decision oxygen supply module and data monitoring module, and setting control target and parameters, alarming abnormal state of physiological state, prompting and predicting dangerous situation, specifically: according to real-time monitored physiological state, oxygen supply concentration and oxygen supply decision, storing, recording and displaying through monitoring interaction module, and issuing alarm for abnormal situation, prompting manual intervention, checking equipment and troubleshooting.

2. The system of claim 1, wherein the system is configured to: In the signal screening module, the optimization algorithm includes solving suboptimal solution by using heuristic optimization algorithm, and then screening the overall physiological data.

3. The system of claim 1, wherein the system is configured to: In the decision oxygen supply module, the oxygen supply concentration decision is determined by the predictive control algorithm, including: The optimization step size is set as And the optimal control parameters, i.e. the oxygen allocation decision, are determined by solving the oxygen allocation optimization problem as follows: wherein , , ; is the level of the desired healthy physiological indicator, is the state vector of the physiological indicator at time t, is the control input oxygen concentration vector at time t, is the initial state vector of the human body at the beginning of the regulation, is the physiological state response corresponding to , , are the weight matrices respectively assigned to the deviation of the physiological state from the desired value and to the oxygen concentration during the regulation process, represents the generalized inverse matrix, , are the safety constraints on the controllable input for the corresponding physiological state.​ 4. The system of claim 1, wherein the system is configured to: The monitoring interaction module is integrated into a mobile terminal, including a computer and a mobile phone.

5. The system of claim 1, wherein the system is configured to regulate the hypoxic environment by adjusting the oxygen concentration in the chamber to a level between 10% and 20%. The monitoring interaction module, data monitoring module, signal screening module and decision oxygen supply module are connected by wireless or wired communication technology.

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