A respiratory assistance system with diaphragm pacemaker and neuroregulator linked

Abstract

The present invention relates to the field of medical device technology, and specifically discloses a respiratory assistance system in which a diaphragm pacemaker and a neuroregulator are linked, comprising: a respiratory dysfunction degree detection module for detecting the current respiratory dysfunction degree of a patient; a limit improvement degree evaluation module for evaluating the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the limit improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree; an assistance participation degree determination module for determining the degree of respiratory assistance participation of the diaphragm pacemaker and the neuroregulator on the patient; a respiratory assistance control module for setting control parameters of the diaphragm pacemaker and the neuroregulator respectively based on the degree of respiratory assistance participation of the diaphragm pacemaker and the neuroregulator on the patient's respiratory assistance degree; and for accurately linking and controlling the diaphragm pacemaker and the neuroregulator to assist the patient in improving his respiratory dysfunction.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and in particular to a respiratory assistance system in which a diaphragm pacemaker and a neuroregulator are linked. Background Art

[0002] A diaphragm pacemaker is a medical device that stimulates and enhances the contraction function of the diaphragm by providing electrical signals to the human body through an implant. It usually consists of a rechargeable battery, a pulse generator, an antenna, and implanted electrodes. These electrodes are designed to produce minimal resistance at specific locations to stimulate and sense the movement of the diaphragm, that is, the diaphragm pacemaker induces respiratory movement by electrically stimulating the diaphragm. The neuromodulator regulates the respiratory pattern by controlling the autonomic nervous system, especially the respiratory center. At present, both medical devices can improve patients' respiratory dysfunction. In actual treatment, medical staff appropriately choose any one of the treatment methods or use both treatment methods at the same time to improve patients' respiratory dysfunction based on the patient's clinical diagnosis results.

[0003] However, in actual treatment, the medical staff manually selects the degree of participation of the two treatment devices in the treatment of the patient's respiratory dysfunction. This decision-making process relies on manual experience and may not guarantee the efficiency of this combined respiratory assistance method in improving the treatment of respiratory dysfunction, and cannot maximize the therapeutic effect of this combined respiratory assistance method.

[0004] Therefore, the present invention proposes a respiratory assistance system in which a diaphragm pacemaker and a neuroregulator are linked. Summary of the invention

[0005] The present invention provides a respiratory assistance system in which a diaphragm pacemaker and a neuroregulator are linked together, which is used to accurately link and control the diaphragm pacemaker and the neuroregulator to assist the patient in improving his respiratory dysfunction based on the patient's current respiratory dysfunction level and the maximum improvement level of the diaphragm pacemaker and the neuroregulator to improve the patient's current respiratory dysfunction, thereby achieving more comprehensive and efficient respiratory assistance and maximizing the therapeutic effect of this combined respiratory assistance method.

[0006] The present invention provides a respiratory assistance system in which a diaphragm pacemaker and a neuroregulator are linked, comprising:

[0007] A respiratory dysfunction degree detection module is used to detect the patient's current respiratory dysfunction degree;

[0008] A limit improvement degree assessment module, used to assess the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the limit improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree based on the patient's current physiological parameters;

[0009] An assistance participation degree determination module, used to determine the degree of respiratory assistance participation of the diaphragm pacemaker and the degree of respiratory assistance participation of the neuroregulator on the patient based on the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the limit improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree;

[0010] The respiratory assistance control module is used to set the control parameters of the diaphragm pacemaker and the control parameters of the neuroregulator respectively based on the degree of participation of the diaphragm pacemaker in the patient's respiratory assistance and the degree of participation of the neuroregulator in the patient's respiratory assistance to obtain the respiratory assistance control result.

[0011] Preferably, the respiratory dysfunction degree detection module includes:

[0012] A response feedback information acquisition submodule is used to acquire all response parts of respiratory dysfunction and acquire current state information of all response parts of the patient as the patient's current respiratory dysfunction response feedback information;

[0013] The action characterization information acquisition submodule is used to acquire the action sites of all respiratory processes, and acquire the latest respiratory function characterization information of all the action sites of the patient's respiratory processes as the patient's current respiratory function action characterization information;

[0014] A respiratory function quantitative detection value acquisition submodule is used to acquire all respiratory function quantitative data sources and obtain the current detection values ​​of all respiratory function quantitative data sources of the patient;

[0015] The respiratory dysfunction degree assessment submodule is used to assess the patient's current respiratory dysfunction degree based on the patient's current respiratory dysfunction response feedback information and current respiratory function characterization information as well as the current detection values ​​of all respiratory function quantitative data sources.

[0016] Preferably, the respiratory dysfunction degree assessment submodule includes:

[0017] A first degree evaluation unit is used to extract specific indicator values ​​of all decision indicator classes belonging to the decision mechanism of respiratory dysfunction response feedback information-respiratory dysfunction degree from the patient's current respiratory dysfunction response feedback information as first indicator values, and determine the patient's first respiratory dysfunction degree based on all first indicator values ​​and the decision mechanism of respiratory dysfunction response feedback information-respiratory dysfunction degree;

[0018] A second degree evaluation unit is used to extract specific index values ​​of all decision index categories belonging to the decision mechanism of respiratory function characterization information-respiratory dysfunction degree from the patient's current respiratory function characterization information as second index values, and determine the patient's second respiratory dysfunction degree based on all second index values ​​and the decision mechanism of respiratory function characterization information-respiratory dysfunction degree;

[0019] A third degree evaluation unit, configured to determine a third respiratory dysfunction degree of the patient based on current detection values ​​of all respiratory function quantification data sources of the patient and a decision mechanism of respiratory function quantification detection value-respiratory dysfunction degree;

[0020] The respiratory dysfunction degree assessment unit is used to assess the patient's current respiratory dysfunction degree based on the patient's first respiratory dysfunction degree, second respiratory dysfunction degree, and third respiratory dysfunction degree.

[0021] Preferably, the respiratory dysfunction degree assessment unit comprises:

[0022] A first evaluation subunit is used for, when it is determined that the comprehensive similarity of the first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree of the patient is not less than the comprehensive similarity threshold, taking the average of the first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree of the patient as the current respiratory dysfunction degree of the patient;

[0023] The second evaluation subunit is used to calculate the similarity between the patient's first respiratory dysfunction level, second respiratory dysfunction level, and third respiratory dysfunction level when the comprehensive similarity of the patient's first respiratory dysfunction level, second respiratory dysfunction level, and third respiratory dysfunction level is less than the comprehensive similarity threshold, and take the average of the group of respiratory dysfunction levels with the greatest similarity as the patient's current respiratory dysfunction level.

[0024] Preferably, the limit improvement degree assessment module includes:

[0025] The first improvement degree assessment submodule is used to input the patient's current physiological parameters and the patient's current respiratory dysfunction degree into the pacemaker limit improvement degree assessment model to obtain the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree;

[0026] The second improvement degree assessment submodule is used to input the patient's current physiological parameters and the patient's current respiratory dysfunction degree into the neuroregulator limit improvement degree assessment model to obtain the neuroregulator's limit improvement degree on the patient's current respiratory dysfunction degree.

[0027] Preferably, the auxiliary participation level determination module includes:

[0028] A comparison table inference submodule is used to infer a comparison table of the limit improvement degree of the diaphragm pacemaker for the patient - the average improvement rate and a comparison table of the limit improvement degree of the neuromodulator for the patient - the average improvement rate;

[0029] A final improvement degree determination submodule, used to determine a final improvement degree of a group of diaphragm pacemakers on the patient's current respiratory dysfunction degree and a final improvement degree of a neuroregulator on the patient's current respiratory dysfunction degree that meet preset constraints;

[0030] The participation degree determination submodule is used to use the ratio of the final improvement degree of the diaphragm pacemaker to the patient's current respiratory dysfunction degree and the patient's current respiratory dysfunction degree as the diaphragm pacemaker's participation degree in the patient's respiratory assistance, and at the same time, use the ratio of the final improvement degree of the neuroregulator to the patient's current respiratory dysfunction degree and the patient's current respiratory dysfunction degree as the neuroregulator's participation degree in the patient's respiratory assistance.

[0031] Preferably, the comparison table inference submodule includes:

[0032] An instance acquisition unit, used for acquiring a large number of linked breathing assistance instances of diaphragm pacemakers and neuroregulators, and acquiring the breathing assistance action time and actual improvement degree of the diaphragm pacemaker and the breathing assistance action time and actual improvement degree of the neuroregulator in each linked breathing assistance instance;

[0033] An array construction unit, used for generating an assistive breathing array of each linked breathing assistance instance based on the respiratory assistive action time and actual improvement degree of the diaphragm pacemaker and the respiratory assistive action time and actual improvement degree of the neuroregulator in each linked breathing assistance instance;

[0034] A network structure building unit is used to calculate the similarity between the auxiliary breathing action arrays of the two-by-two linked breathing assistance instances, take the average value of all similarities involved in each auxiliary breathing action array as the centrality of each auxiliary breathing action array, and build an instance array network based on the similarity between the auxiliary breathing action array with the maximum centrality and the auxiliary breathing action array of the two-by-two linked breathing assistance instances;

[0035] The path crawling unit is used to crawl and screen all extended paths in the instance array network in sequence to obtain the optimal crawling path of the diaphragm pacemaker and the optimal crawling path of the neuroregulator, and determine the extreme improvement degree - average improvement rate comparison table of the diaphragm pacemaker for the patient based on the optimal crawling path of the diaphragm pacemaker. At the same time, determine the extreme improvement degree - average improvement rate comparison table of the neuroregulator for the patient based on the optimal crawling path of the neuroregulator.

[0036] Preferably, the final improvement degree determination submodule includes:

[0037] A first constraint unit is used to determine all possible value combinations of the improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree that meet the first constraint condition;

[0038] The second constraint unit is used to screen out a group of possible value combinations that meet the second constraint condition from all possible value combinations of the degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker and the degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator that meet the first constraint condition, as the final screened possible value combinations, and use the degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker and the degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator in the final screened possible value combinations as the final degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker and the final degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator that meet the constraint condition.

[0039] Preferably, the first constraint condition includes:

[0040] The sum of the improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree is equal to the patient's current respiratory dysfunction degree.

[0041] Preferably, the second constraint condition includes:

[0042] The sum of the average improvement rate corresponding to the degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker in the comparison table of the patient's limit improvement degree - average improvement rate and the average improvement rate corresponding to the degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator in the comparison table of the patient's limit improvement degree - average improvement rate is the largest.

[0043] The beneficial effects of the present invention compared to the prior art are as follows: based on the patient's current respiratory dysfunction level and the maximum improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction level and the maximum improvement degree of the neuroregulator on the patient's current respiratory dysfunction level, the diaphragm pacemaker and the neuroregulator are precisely linked and controlled to assist the patient in improving his respiratory dysfunction and achieve more comprehensive and efficient respiratory assistance.

[0044] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0045] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0047] Figure 1 Schematic diagram of the internal functional modules of the respiratory assistance system in which the diaphragm pacemaker and the neuroregulator are linked in an embodiment of the present invention;

[0048] Figure 2 Schematic diagram of internal functional submodules of a respiratory dysfunction degree detection module in an embodiment of the present invention;

[0049] Figure 3 Schematic diagram of internal functional submodules of the limit improvement degree evaluation module in an embodiment of the present invention;

[0050] Figure 4 Schematic diagram of internal functional submodules of the auxiliary participation degree determination module in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0052] Example 1

[0053] The present invention provides a respiratory assistance system in which a diaphragm pacemaker and a neuroregulator are linked. Figure 1 ,include:

[0054] A respiratory dysfunction degree detection module is used to detect the patient's current respiratory dysfunction degree;

[0055] A limit improvement degree assessment module, used to assess the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the limit improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree based on the patient's current physiological parameters;

[0056] An assistance participation degree determination module, used to determine the degree of respiratory assistance participation of the diaphragm pacemaker and the degree of respiratory assistance participation of the neuroregulator on the patient based on the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the limit improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree;

[0057] The respiratory assistance control module is used to set the control parameters of the diaphragm pacemaker and the control parameters of the neuroregulator respectively based on the degree of participation of the diaphragm pacemaker in the patient's respiratory assistance and the degree of participation of the neuroregulator in the patient's respiratory assistance to obtain the respiratory assistance control result.

[0058] In this embodiment, the diaphragm pacemaker is used to stimulate the diaphragm to achieve active breathing, while the neuroregulator is used to regulate the autonomic nervous system, including the regulation of the respiratory center. By linking these two devices, more comprehensive and efficient respiratory assistance can be achieved, which is especially suitable for patients with respiratory insufficiency or disorders.

[0059] In this embodiment, the current respiratory dysfunction level represents a numerical value of the severity of the respiratory dysfunction symptoms currently suffered by the patient, expressed as a percentage.

[0060] In this embodiment, the patient's current physiological parameters are parameters representing the patient's physiological signs, such as the patient's gender, age, blood pressure value, body temperature value, etc.

[0061] In this embodiment, the limit of improvement of the patient's current respiratory dysfunction by the diaphragm pacemaker means the maximum percentage of improvement of the patient's current respiratory dysfunction by the diaphragm pacemaker when the patient's respiratory dysfunction is treated and improved by the diaphragm pacemaker and the neuroregulator at the same time.

[0062] In this embodiment, the limit of improvement of the patient's current respiratory dysfunction by the neuroregulator represents the maximum percentage of improvement of the patient's current respiratory dysfunction by the neuroregulator when the patient's respiratory dysfunction is treated and improved by the diaphragm pacemaker and the neuroregulator at the same time.

[0063] In this embodiment, the degree of participation of the diaphragm pacemaker in assisting the patient's breathing is the ratio of the final degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker to the patient's current respiratory dysfunction degree.

[0064] In this embodiment, the degree of participation of the neuroregulator in assisting the patient's breathing is the ratio of the final degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator to the patient's current respiratory dysfunction degree.

[0065] In this embodiment, based on the degree of participation of the diaphragm pacemaker in assisting the patient's breathing and the degree of participation of the neuroregulator in assisting the patient's breathing, the control parameters of the diaphragm pacemaker and the control parameters of the neuroregulator are set respectively to obtain a respiratory assistance control result, including:

[0066] The preset maximum instantaneous improvement rate of the diaphragm pacemaker (i.e., the maximum improvement rate that the diaphragm pacemaker can achieve when improving respiratory dysfunction symptoms) and the preset maximum instantaneous improvement rate of the neuroregulator (i.e., the maximum improvement rate that the neuroregulator can achieve when improving respiratory dysfunction symptoms) are determined. When the ratio of the preset maximum instantaneous improvement rate of the diaphragm pacemaker to the preset maximum instantaneous improvement rate of the neuroregulator is greater than the ratio of the diaphragm pacemaker's participation in the patient's respiratory assistance to the neuroregulator's participation in the patient's respiratory assistance, the maximum controllable parameter of the neuropacer is used as the control parameter of the neuroregulator, and the quotient of the maximum controllable parameter of the diaphragm pacemaker and the ratio of the preset maximum instantaneous improvement rate of the diaphragm pacemaker to the preset maximum instantaneous improvement rate of the neuroregulator, and the product of the diaphragm pacemaker's participation in the patient's respiratory assistance to the neuroregulator's participation in the patient's respiratory assistance, are used as the control parameter of the diaphragm pacemaker.

[0067] In this embodiment, the control parameter of the diaphragm pacemaker is a control parameter that is proportional to the improvement effect of the diaphragm pacemaker on respiratory dysfunction, such as the magnitude of the voltage applied by the diaphragm pacemaker to the electrode.

[0068] In this embodiment, the control parameter of the regulator is a control parameter that is proportional to the magnitude of the improvement effect of the neuromodulator on the respiratory dysfunction, such as the magnitude of the effect exerted by the neuromodulator on the respiratory center.

[0069] The beneficial effects of the above technology are: based on the patient's current degree of respiratory dysfunction and the maximum improvement degree of the diaphragm pacemaker on the patient's current degree of respiratory dysfunction and the maximum improvement degree of the neuroregulator on the patient's current degree of respiratory dysfunction, the diaphragm pacemaker and the neuroregulator are precisely linked and controlled to assist the patient in improving his respiratory dysfunction, achieving more comprehensive and efficient respiratory assistance, so that this combined respiratory assistance method can achieve maximum therapeutic effectiveness.

[0070] Example 2

[0071] Based on Example 1, the respiratory dysfunction degree detection module refers to Figure 2 ,include:

[0072] A response feedback information acquisition submodule is used to acquire all response parts of respiratory dysfunction and acquire current state information of all response parts of the patient as the patient's current respiratory dysfunction response feedback information;

[0073] The action characterization information acquisition submodule is used to acquire the action sites of all respiratory processes, and acquire the latest respiratory function characterization information of all the action sites of the patient's respiratory processes as the patient's current respiratory function action characterization information;

[0074] A respiratory function quantitative detection value acquisition submodule is used to acquire all respiratory function quantitative data sources and obtain the current detection values ​​of all respiratory function quantitative data sources of the patient;

[0075] The respiratory dysfunction degree assessment submodule is used to assess the patient's current respiratory dysfunction degree based on the patient's current respiratory dysfunction response feedback information and current respiratory function characterization information as well as the current detection values ​​of all respiratory function quantitative data sources.

[0076] In this embodiment, all the response sites of respiratory dysfunction are the body parts or organs that may be affected by respiratory dysfunction, such as the gastroesophageal tract and airway. Respiratory dysfunction may cause gastroesophageal reflux or low airway pressure.

[0077] In this embodiment, the current status information of all the response parts is the status information indicating that the response parts are affected by respiratory dysfunction, such as the degree of gastroesophageal reflux or the intra-airway pressure value of the airway.

[0078] In this embodiment, all respiratory process action sites are body organs directly involved in the respiratory action, and some of their state information can reflect the patient's respiratory function, mainly the lungs and diaphragm.

[0079] In this embodiment, the latest respiratory function characterization information of all respiratory process action sites is the latest status information of the respiratory process action sites that can reflect the patient's respiratory function, such as lung function parameters: such as forced expiratory volume in one second (FEV1.0), forced expiratory volume in one second (FVC), etc., which can reflect the patient's lung capacity and gas exchange capacity; another example is the diaphragm thickening score and diaphragm mobility of the diaphragm.

[0080] In this embodiment, the respiratory function quantification data source is data items that can be directly detected and obtained and represent the patient's current respiratory function, such as deep expiratory volume, maximum air intake, etc.

[0081] In this embodiment, the current detection values ​​of all respiratory function quantification data sources are detection values ​​of all respiratory function quantification data sources obtained by the current detection.

[0082] The beneficial effect of the above technology is: by obtaining feedback information based on the patient's current respiratory disorder response and current respiratory function characterization information as well as the current detection values ​​of all respiratory function quantitative data sources, a comprehensive and accurate assessment of the patient's current respiratory dysfunction level can be achieved by integrating respiratory response, respiratory process, traditional respiratory function detection and other aspects.

[0083] Example 3

[0084] Based on Example 2, the respiratory dysfunction degree assessment submodule includes:

[0085] A first degree evaluation unit is used to extract specific indicator values ​​of all decision indicator classes belonging to the decision mechanism of respiratory dysfunction response feedback information-respiratory dysfunction degree from the patient's current respiratory dysfunction response feedback information as first indicator values, and determine the patient's first respiratory dysfunction degree based on all first indicator values ​​and the decision mechanism of respiratory dysfunction response feedback information-respiratory dysfunction degree;

[0086] A second degree evaluation unit is used to extract specific index values ​​of all decision index categories belonging to the decision mechanism of respiratory function characterization information-respiratory dysfunction degree from the patient's current respiratory function characterization information as second index values, and determine the patient's second respiratory dysfunction degree based on all second index values ​​and the decision mechanism of respiratory function characterization information-respiratory dysfunction degree;

[0087] A third degree evaluation unit, configured to determine a third respiratory dysfunction degree of the patient based on current detection values ​​of all respiratory function quantification data sources of the patient and a decision mechanism of respiratory function quantification detection value-respiratory dysfunction degree;

[0088] The respiratory dysfunction degree assessment unit is used to assess the patient's current respiratory dysfunction degree based on the patient's first respiratory dysfunction degree, second respiratory dysfunction degree, and third respiratory dysfunction degree.

[0089] In this embodiment, the respiratory dysfunction response feedback information-respiratory dysfunction degree decision mechanism represents a pre-set calculation mechanism for determining the respiratory dysfunction degree using the respiratory dysfunction response feedback information, for example:

[0090] When the intra-airway pressure value is less than the intra-airway pressure threshold value (i.e. 11 cmH2O), the ratio of the difference between the intra-airway pressure threshold value and the intra-airway pressure threshold value to the intra-airway pressure threshold value is taken as the degree of reduction of the intra-airway pressure.

[0091] The greater value of the decrease in intra-airway pressure and the gastroesophageal reflux degree is regarded as the first respiratory dysfunction degree;

[0092] When the intra-airway pressure value is greater than the intra-airway pressure threshold, the degree of gastroesophageal reflux is regarded as the first degree of respiratory dysfunction.

[0093] In this embodiment, the decision indicator class represents a data class that can be extracted from the respiratory dysfunction response feedback information or the respiratory function effect representation information and is used to determine the degree of respiratory dysfunction.

[0094] In this embodiment, the specific indicator value of the decision indicator class is the specific value of the decision indicator class extracted from the respiratory dysfunction response feedback information or the respiratory function effect representation information.

[0095] In this embodiment, based on all the first indicator values ​​and the respiratory dysfunction response feedback information-respiratory dysfunction degree decision mechanism, the first respiratory dysfunction degree of the patient is determined, that is:

[0096] All first indicator values ​​are substituted into the respiratory dysfunction response feedback information-respiratory dysfunction degree decision-making mechanism to obtain the patient's first respiratory dysfunction degree.

[0097] In this embodiment, the respiratory function characterization information-respiratory dysfunction degree decision mechanism represents a pre-set calculation mechanism for determining the respiratory dysfunction degree using the respiratory function characterization information, for example:

[0098] The average of the decline rate of the forced expiratory volume in one second (FEV1.0) and the decline rate of the forced expiratory volume in one second (FVC) was taken as the second degree of respiratory dysfunction of the patient.

[0099] In this embodiment, based on all the second index values ​​and the respiratory function characterization information-the decision mechanism of the respiratory dysfunction degree, the second respiratory dysfunction degree of the patient is determined, that is:

[0100] All second index values ​​are substituted into the respiratory function characterization information-respiratory dysfunction degree decision-making mechanism to obtain the patient's second respiratory dysfunction degree.

[0101] In this embodiment, the decision mechanism of respiratory function quantitative detection value-respiratory dysfunction degree represents a pre-set calculation mechanism for determining the respiratory dysfunction degree using respiratory dysfunction response feedback information, for example:

[0102] The average of the ratio of the difference between the standard deep expiratory volume and the deep expiratory volume to the standard deep expiratory volume and the average of the ratio of the difference between the maximum standard respiratory capacity and the maximum respiratory capacity to the maximum standard respiratory capacity was taken as the third degree of respiratory dysfunction of the patient.

[0103] In this embodiment, based on the current detection values ​​of all respiratory function quantification data sources of the patient and the decision mechanism of respiratory function quantification detection value-respiratory dysfunction degree, the third respiratory dysfunction degree of the patient is determined, that is:

[0104] The current detection values ​​of all respiratory function quantification data sources of the patient are substituted into the decision-making mechanism of respiratory function quantification detection value-respiratory dysfunction degree to obtain the patient's third respiratory dysfunction degree.

[0105] The beneficial effects of the above technology are: based on the respiratory dysfunction response feedback information-decision-making mechanism of the degree of respiratory dysfunction, the respiratory function characterization information-decision-making mechanism of the degree of respiratory dysfunction, and the respiratory function quantitative detection value-decision-making mechanism of the degree of respiratory dysfunction, a comprehensive and accurate assessment of the patient's current degree of respiratory dysfunction is achieved by integrating respiratory response, respiratory process, traditional respiratory function detection and other aspects.

[0106] Example 4

[0107] Based on Example 3, the respiratory dysfunction degree assessment unit includes:

[0108] A first evaluation subunit is used for, when it is determined that the comprehensive similarity of the first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree of the patient is not less than the comprehensive similarity threshold, taking the average of the first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree of the patient as the current respiratory dysfunction degree of the patient;

[0109] The second evaluation subunit is used to calculate the similarity between the patient's first respiratory dysfunction level, second respiratory dysfunction level, and third respiratory dysfunction level when the comprehensive similarity of the patient's first respiratory dysfunction level, second respiratory dysfunction level, and third respiratory dysfunction level is less than the comprehensive similarity threshold, and take the average of the group of respiratory dysfunction levels with the greatest similarity as the patient's current respiratory dysfunction level.

[0110] In this embodiment, the calculation method of the comprehensive similarity of the first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree of the patient is:

[0111] The average of the ratios of the first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree to the maximum values ​​of the first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree, respectively, is taken as the comprehensive similarity of the patient's first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree.

[0112] In this embodiment, the comprehensive similarity threshold is a preset value that the comprehensive similarity of the patient's first respiratory dysfunction level, second respiratory dysfunction level, and third respiratory dysfunction level cannot be less than when the average of the patient's first respiratory dysfunction level, second respiratory dysfunction level, and third respiratory dysfunction level is used as the patient's current respiratory dysfunction level.

[0113] In this embodiment, the similarity between the first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree of the patient is calculated, that is,

[0114] The ratio of the smaller value to the larger value of the two respiratory dysfunction degrees is regarded as the similarity between the corresponding two respiratory dysfunction degrees.

[0115] The beneficial effects of the above technology are: by calculating the comprehensive similarity of the patient's first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree and comparing them with the threshold, and further calculating the similarity between the patient's first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree, the numerical range of the patient's current respiratory dysfunction degree that is finally calculated is selected, thereby ensuring the accuracy of the patient's current respiratory dysfunction degree that is finally calculated.

[0116] Example 5

[0117] Based on Example 1, the limit improvement degree evaluation module refers to Figure 3 ,include:

[0118] The first improvement degree assessment submodule is used to input the patient's current physiological parameters and the patient's current respiratory dysfunction degree into the pacemaker limit improvement degree assessment model to obtain the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree;

[0119] The second improvement degree assessment submodule is used to input the patient's current physiological parameters and the patient's current respiratory dysfunction degree into the neuroregulator limit improvement degree assessment model to obtain the neuroregulator's limit improvement degree on the patient's current respiratory dysfunction degree.

[0120] In this embodiment, the pacemaker limit improvement degree assessment model is a model obtained by training with a large number of patients' current physiological parameters and the patients' current respiratory dysfunction degree and the corresponding diaphragm pacemaker's limit improvement degree on the patients' current respiratory dysfunction degree as training samples;

[0121] Among them, the current physiological parameters of the patients in the training samples, the initial respiratory dysfunction level of the patients, and the corresponding extreme improvement degree of the diaphragm pacemaker on the current respiratory dysfunction level of the patients are all extracted from the example of the artificially controlled diaphragm pacemaker improving the respiratory dysfunction symptoms of the patients, and the method for determining the initial respiratory dysfunction level of the patients in the training samples is the same as the method for determining the current respiratory dysfunction level of the patients in Example 1. In addition, the extreme improvement degree of the diaphragm pacemaker on the current respiratory dysfunction level of the patients is the difference between the initial respiratory dysfunction level of the patients and the respiratory dysfunction level finally achieved after the diaphragm pacemaker is continuously used to improve the respiratory dysfunction symptoms of the patients as recorded in the example.

[0122] In this embodiment, the neuroregulator limit improvement degree assessment model is a model obtained by training with a large number of patients' current physiological parameters and the patients' current respiratory dysfunction degree and the corresponding neuroregulator limit improvement degree of the patients' current respiratory dysfunction degree as training samples;

[0123] Among them, the current physiological parameters of the patients in the training samples, the initial respiratory dysfunction level of the patients, and the corresponding extreme improvement degree of the neuroregulator on the current respiratory dysfunction level of the patients are all extracted from the examples of the artificially controlled neuroregulator improving the respiratory dysfunction symptoms of the patients, and the method for determining the initial respiratory dysfunction level of the patients in the training samples is the same as the method for determining the current respiratory dysfunction level of the patients in Example 1. In addition, the extreme improvement degree of the neuroregulator on the current respiratory dysfunction level of the patients is the difference between the initial respiratory dysfunction level of the patients and the respiratory dysfunction level finally achieved after the neuroregulator is continuously improved in the patients as recorded in the examples.

[0124] The beneficial effects of the above technology are: based on the pacemaker limit improvement degree assessment model and the neuroregulator limit improvement degree assessment model, an artificial intelligence algorithm is used to accurately predict the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction and the limit improvement degree of the neuroregulator on the patient's current respiratory dysfunction.

[0125] Example 6

[0126] Based on Example 1, the auxiliary participation level determination module refers to Figure 4 ,include:

[0127] A comparison table inference submodule is used to infer a comparison table of the limit improvement degree of the diaphragm pacemaker for the patient - the average improvement rate and a comparison table of the limit improvement degree of the neuromodulator for the patient - the average improvement rate;

[0128] A final improvement degree determination submodule, used to determine a final improvement degree of a group of diaphragm pacemakers on the patient's current respiratory dysfunction degree and a final improvement degree of a neuroregulator on the patient's current respiratory dysfunction degree that meet preset constraints;

[0129] The participation degree determination submodule is used to use the ratio of the final improvement degree of the diaphragm pacemaker to the patient's current respiratory dysfunction degree and the patient's current respiratory dysfunction degree as the diaphragm pacemaker's participation degree in the patient's respiratory assistance, and at the same time, use the ratio of the final improvement degree of the neuroregulator to the patient's current respiratory dysfunction degree and the patient's current respiratory dysfunction degree as the neuroregulator's participation degree in the patient's respiratory assistance.

[0130] In this embodiment, the comparison table of the ultimate improvement degree of the diaphragm pacemaker for the patient and the average improvement rate includes the average improvement rate values ​​corresponding to different values ​​of the ultimate improvement degree of the diaphragm pacemaker for the patient.

[0131] In this embodiment, the comparison table of the extreme improvement degree of the neuroregulator for the patient and the average improvement rate includes the average improvement rate values ​​corresponding to different extreme improvement degrees of the neuroregulator for the patient.

[0132] In this embodiment, the average improvement rate is the ratio of the corresponding limit improvement degree to the time required for the improvement degree to reach the limit improvement degree when the diaphragm pacemaker or neuroregulator improves the patient's respiratory therapy.

[0133] The beneficial effect of the above technology is: to achieve reasonable determination of the degree of participation of the diaphragm pacemaker in the patient's respiratory assistance and the degree of participation of the neuroregulator in the patient's respiratory assistance.

[0134] Example 7

[0135] Based on Example 6, the comparison table inference submodule includes:

[0136] An instance acquisition unit, used for acquiring a large number of linked breathing assistance instances of diaphragm pacemakers and neuroregulators, and acquiring the breathing assistance action time and actual improvement degree of the diaphragm pacemaker and the breathing assistance action time and actual improvement degree of the neuroregulator in each linked breathing assistance instance;

[0137] An array construction unit, used for generating an assistive breathing array of each linked breathing assistance instance based on the respiratory assistive action time and actual improvement degree of the diaphragm pacemaker and the respiratory assistive action time and actual improvement degree of the neuroregulator in each linked breathing assistance instance;

[0138] A network structure building unit is used to calculate the similarity between the auxiliary breathing action arrays of the two-by-two linked breathing assistance instances, take the average value of all similarities involved in each auxiliary breathing action array as the centrality of each auxiliary breathing action array, and build an instance array network based on the similarity between the auxiliary breathing action array with the maximum centrality and the auxiliary breathing action array of the two-by-two linked breathing assistance instances;

[0139] The path crawling unit is used to crawl and screen all extended paths in the instance array network in sequence to obtain the optimal crawling path of the diaphragm pacemaker and the optimal crawling path of the neuroregulator, and determine the extreme improvement degree - average improvement rate comparison table of the diaphragm pacemaker for the patient based on the optimal crawling path of the diaphragm pacemaker. At the same time, determine the extreme improvement degree - average improvement rate comparison table of the neuroregulator for the patient based on the optimal crawling path of the neuroregulator.

[0140] In this embodiment, the linked respiratory assistance example is an example that records relevant information and data during the process of a doctor using a diaphragm pacemaker and a neuroregulator to link together to treat and improve a patient's respiratory dysfunction, such as the respiratory assistance action time and actual degree of improvement of the diaphragm pacemaker and the respiratory assistance action time and actual degree of improvement of the neuroregulator.

[0141] In this embodiment, the respiratory assistance time is the length of time that the diaphragm pacemaker or neuroregulator acts on the patient's respiratory dysfunction during the entire treatment process.

[0142] In this embodiment, the actual degree of improvement is the final degree of improvement in the patient's respiratory dysfunction symptoms by the diaphragm pacemaker or neuroregulator recorded in the linked respiratory assistance example. This data is inferred based on the doctor's control parameters of the diaphragm pacemaker or neuroregulator recorded in the linked respiratory assistance example. The inference principle is obtained by performing big data analysis on a large number of examples of diaphragm pacemakers or neuroregulators improving patients' respiratory dysfunction symptoms using existing big data algorithms.

[0143] In this embodiment, the respiratory assistance array is formed by arranging the respiratory assistance time and actual improvement degree of the diaphragm pacemaker and the respiratory assistance time and actual improvement degree of the neuroregulator in a single linked respiratory assistance instance in sequence.

[0144] In this embodiment, calculating the similarity between the auxiliary breathing action arrays of the two-to-two linked breathing assistance instances includes:

[0145] The average of the ratios of the smaller value to the larger value in the values ​​of all positions in the auxiliary breathing action arrays of the two linked breathing assistance instances is regarded as the similarity between the auxiliary breathing action arrays of the two linked breathing assistance instances.

[0146] In this embodiment, the centrality of the auxiliary respiration array indicates the centrality of the auxiliary respiration array in the instance array grid.

[0147] In this embodiment, based on the similarity between the auxiliary breathing array of the maximum centrality and the auxiliary breathing array of the two-to-two linkage breathing auxiliary instances, an instance array network is constructed, including:

[0148] Determine all auxiliary respiration arrays whose similarity with the auxiliary respiration array with the maximum center is not less than a similarity threshold (a preset similarity threshold, for example, 0.75) as all surrounding arrays of the auxiliary respiration array with the maximum center, and regard all surrounding arrays of the auxiliary respiration array with the maximum center as all first-layer arrays, and respectively connect the auxiliary respiration array with the maximum center and all corresponding surrounding arrays with paths;

[0149] Among all the auxiliary breathing action arrays of all linked breathing assistance instances except the auxiliary breathing action array with the maximum centrality and all the first-layer arrays, all the auxiliary breathing action arrays whose similarity with each first-layer array is not less than the similarity threshold are screened out as all the surrounding arrays of each first-layer array, and all the surrounding arrays of all the first-layer arrays are regarded as the second-layer array, and each first-layer array and all the corresponding surrounding arrays are connected by paths respectively, and so on, until there is no auxiliary breathing action array whose similarity with the latest layer array is not less than the similarity threshold in the auxiliary breathing action arrays of all linked breathing assistance instances, then the network structure composed of all the auxiliary breathing action arrays connected by paths currently obtained is regarded as the instance array network.

[0150] In this embodiment, all the extended paths in the example array grid are sequentially crawled and screened to obtain the optimal crawling path of the diaphragm pacemaker and the optimal crawling path of the neuroregulator, and a comparison table of the limit improvement degree of the diaphragm pacemaker for the patient-average improvement rate is determined based on the optimal crawling path of the diaphragm pacemaker. At the same time, a comparison table of the limit improvement degree of the neuroregulator for the patient-average improvement rate is determined based on the optimal crawling path of the neuroregulator, including:

[0151] In the instance array network, multiple longest paths starting from the auxiliary breathing array with the maximum centrality and ending at the last layer array are determined, wherein the longest path is formed by connecting multiple auxiliary breathing arrays connected by multiple paths;

[0152] Determine the distribution uniformity of the actual improvement degree of the diaphragm pacemaker and the distribution uniformity of the actual improvement degree of the neuroregulator included in all the auxiliary breathing action arrays included in each longest path;

[0153] The longest path corresponding to the maximum distribution uniformity of the actual improvement degree of the diaphragm pacemaker is taken as the optimal crawling path of the diaphragm pacemaker;

[0154] Based on the respiratory assistance time and actual improvement degree of the diaphragm pacemaker included in all the respiratory assistance arrays included in the optimal crawling path, a comparison table of the limit improvement degree of the diaphragm pacemaker for the patient - average improvement rate is determined;

[0155] The longest path corresponding to the maximum distribution uniformity of the actual improvement degree of the neuromodulator is regarded as the optimal crawling path of the neuromodulator;

[0156] Based on the respiratory assistance time and actual improvement degree of the neuroregulators included in all the respiratory assistance arrays included in the optimal crawling path, a comparison table of the neuroregulator's limit improvement degree for the patient - average improvement rate is determined;

[0157] The calculation method of the distribution uniformity of the actual improvement degree of the diaphragm pacemaker and the actual improvement degree of the neuroregulator included in all auxiliary respiratory action arrays included in each longest path includes:

[0158] The difference between the maximum and minimum values ​​of the actual improvement degree of the diaphragm pacemaker (or neuroregulator) included in all the auxiliary breathing action arrays included in each longest path is regarded as the distribution uniformity of the actual improvement degree of the diaphragm pacemaker (or neuroregulator) included in all the auxiliary breathing action arrays included in each longest path;

[0159] Among them, based on the respiratory assistance time and actual improvement degree of the diaphragm pacemaker (or neuroregulator) included in all the assisted respiratory action arrays included in the optimal crawling path, a comparison table of the limit improvement degree of the diaphragm pacemaker (or neuroregulator) for the patient - the average improvement rate is determined, including:

[0160] The ratio of the actual improvement degree of the diaphragm pacemaker (or neuroregulator) included in all the assistive breathing action arrays included in the optimal crawling path to the corresponding assistive breathing action time is regarded as the average improvement rate corresponding to the limit improvement degree when the corresponding actual improvement degree is the limit improvement degree;

[0161] The average improvement rates corresponding to all actual improvement levels when the improvement levels are the limit improvement levels obtained from all assisted respiratory action arrays included in the optimal crawling path are used to generate a comparison table of the limit improvement level and average improvement rate of the diaphragm pacemaker (or neuroregulator) for the patient.

[0162] The beneficial effect of the above technology is: using the array generated based on the respiratory assistance action time and actual improvement degree of the diaphragm pacemaker and the respiratory assistance action time and actual improvement degree of the neuroregulator in each linked respiratory assistance instance, a network structure is constructed to facilitate the step-by-step screening of a large number of linked respiratory assistance instances, so as to screen out some respiratory assistance arrays to generate a comparison table of the diaphragm pacemaker's (or neuroregulator's) extreme improvement degree - average improvement rate for patients, ensuring that the generated comparison table of the diaphragm pacemaker's (or neuroregulator's) extreme improvement degree - average improvement rate for patients has a high data range coverage.

[0163] Example 8

[0164] Based on Example 6, the final improvement degree determination submodule includes:

[0165] A first constraint unit is used to determine all possible value combinations of the improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree that meet the first constraint condition;

[0166] The second constraint unit is used to screen out a group of possible value combinations that meet the second constraint condition from all possible value combinations of the degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker and the degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator that meet the first constraint condition, as the final screened possible value combinations, and use the degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker and the degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator in the final screened possible value combinations as the final degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker and the final degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator that meet the constraint condition.

[0167] In this embodiment, the possible value combination includes the possible value x1 of the degree of improvement of the patient's current respiratory dysfunction by the diaphragm pacemaker and the possible value x2 of the degree of improvement of the patient's current respiratory dysfunction by the neuroregulator, and the sum of x1 and x2 is equal to the patient's current respiratory dysfunction.

[0168] The beneficial effect of the above technology is: through two constraints, the final improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction and the final improvement degree of the neuroregulator on the patient's current respiratory dysfunction can be accurately determined.

[0169] Example 9

[0170] Based on Example 8, the first constraint condition includes:

[0171] The sum of the improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree is equal to the patient's current respiratory dysfunction degree.

[0172] The beneficial effects of the above technology are: to constrain the sum of the degree of improvement of the patient's current respiratory dysfunction by the diaphragm pacemaker and the degree of improvement of the patient's current respiratory dysfunction by the neuroregulator, thereby avoiding the mistake of over-treatment when the diaphragm pacemaker and the neuroregulator are ultimately used to jointly improve the patient's respiratory dysfunction lesions, and also avoiding the waste of medical resources.

[0173] Embodiment 10:

[0174] Based on Example 8, the second constraint condition includes:

[0175] The sum of the average improvement rate corresponding to the degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker in the comparison table of the patient's limit improvement degree - average improvement rate and the average improvement rate corresponding to the degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator in the comparison table of the patient's limit improvement degree - average improvement rate is the largest.

[0176] The beneficial effect of the above technology is: through this constraint condition, it can be guaranteed that the final improvement degree of the patient's current respiratory dysfunction degree by a set of diaphragm pacemakers and the final improvement degree of the patient's current respiratory dysfunction degree by a neuroregulator that meet the constraint conditions can be finally determined, and the control parameters of the diaphragm pacemaker and neuroregulator determined subsequently based on this can ensure that the two can work together as much as possible to exert maximum effectiveness in the process of improving the treatment of respiratory dysfunction.

[0177] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A respiratory assistance system in which a diaphragm pacemaker and a neuroregulator are linked, characterized in that: include: A respiratory dysfunction degree detection module is used to detect the patient's current respiratory dysfunction degree; A limit improvement degree assessment module, used to assess the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the limit improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree based on the patient's current physiological parameters; An assistance participation degree determination module, used to determine the degree of respiratory assistance participation of the diaphragm pacemaker and the degree of respiratory assistance participation of the neuroregulator on the patient based on the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the limit improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree; A respiratory assistance control module, used to set control parameters of the diaphragm pacemaker and control parameters of the neuroregulator respectively based on the degree of participation of the diaphragm pacemaker in the patient's respiratory assistance and the degree of participation of the neuroregulator in the patient's respiratory assistance, so as to obtain a respiratory assistance control result; Among them, the respiratory dysfunction degree detection module includes: A response feedback information acquisition submodule is used to acquire all response parts of respiratory dysfunction and acquire current state information of all response parts of the patient as the patient's current respiratory dysfunction response feedback information; The action characterization information acquisition submodule is used to acquire the action sites of all respiratory processes, and acquire the latest respiratory function characterization information of all the action sites of the patient's respiratory processes as the patient's current respiratory function action characterization information; A respiratory function quantitative detection value acquisition submodule is used to acquire all respiratory function quantitative data sources and obtain the current detection values ​​of all respiratory function quantitative data sources of the patient; The respiratory dysfunction degree assessment submodule is used to assess the patient's current respiratory dysfunction degree based on the patient's current respiratory dysfunction response feedback information and current respiratory function characterization information as well as the current detection values ​​of all respiratory function quantitative data sources.

2. The respiratory assistance system of the diaphragm pacemaker and the neuroregulator linked together according to claim 1, characterized in that: The respiratory dysfunction assessment submodule includes: A first degree evaluation unit is used to extract specific indicator values ​​of all decision indicator classes belonging to the decision mechanism of respiratory dysfunction response feedback information-respiratory dysfunction degree from the patient's current respiratory dysfunction response feedback information as first indicator values, and determine the patient's first respiratory dysfunction degree based on all first indicator values ​​and the decision mechanism of respiratory dysfunction response feedback information-respiratory dysfunction degree; A second degree evaluation unit is used to extract specific index values ​​of all decision index categories belonging to the decision mechanism of respiratory function characterization information-respiratory dysfunction degree from the patient's current respiratory function characterization information as second index values, and determine the patient's second respiratory dysfunction degree based on all second index values ​​and the decision mechanism of respiratory function characterization information-respiratory dysfunction degree; A third degree evaluation unit, configured to determine a third respiratory dysfunction degree of the patient based on current detection values ​​of all respiratory function quantification data sources of the patient and a decision mechanism of respiratory function quantification detection value-respiratory dysfunction degree; The respiratory dysfunction degree assessment unit is used to assess the patient's current respiratory dysfunction degree based on the patient's first respiratory dysfunction degree, second respiratory dysfunction degree, and third respiratory dysfunction degree.

3. The respiratory assistance system in which the diaphragm pacemaker and the neuroregulator are linked according to claim 2, characterized in that: Respiratory dysfunction assessment unit, including: A first evaluation subunit is used for, when it is determined that the comprehensive similarity of the first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree of the patient is not less than the comprehensive similarity threshold, taking the average of the first respiratory dysfunction degree, the second respiratory dysfunction degree, and the third respiratory dysfunction degree of the patient as the current respiratory dysfunction degree of the patient; The second evaluation subunit is used to calculate the similarity between the patient's first respiratory dysfunction level, second respiratory dysfunction level, and third respiratory dysfunction level when the comprehensive similarity of the patient's first respiratory dysfunction level, second respiratory dysfunction level, and third respiratory dysfunction level is less than the comprehensive similarity threshold, and take the average of the group of respiratory dysfunction levels with the greatest similarity as the patient's current respiratory dysfunction level.

4. The respiratory assistance system of the diaphragm pacemaker and the neuroregulator linkage according to claim 1, characterized in that: The module for assessing the degree of improvement includes: The first improvement degree assessment submodule is used to input the patient's current physiological parameters and the patient's current respiratory dysfunction degree into the pacemaker limit improvement degree assessment model to obtain the limit improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree; The second improvement degree assessment submodule is used to input the patient's current physiological parameters and the patient's current respiratory dysfunction degree into the neuroregulator limit improvement degree assessment model to obtain the neuroregulator's limit improvement degree on the patient's current respiratory dysfunction degree.

5. The respiratory assistance system of the diaphragm pacemaker and the neuroregulator linked together according to claim 1, characterized in that: A module to assist in determining the level of participation, including: A comparison table inference submodule is used to infer a comparison table of the limit improvement degree of the diaphragm pacemaker for the patient - the average improvement rate and a comparison table of the limit improvement degree of the neuromodulator for the patient - the average improvement rate; A final improvement degree determination submodule, used to determine a final improvement degree of a group of diaphragm pacemakers on the patient's current respiratory dysfunction degree and a final improvement degree of a neuroregulator on the patient's current respiratory dysfunction degree that meet preset constraints; The participation degree determination submodule is used to use the ratio of the final improvement degree of the diaphragm pacemaker to the patient's current respiratory dysfunction degree and the patient's current respiratory dysfunction degree as the diaphragm pacemaker's participation degree in the patient's respiratory assistance, and at the same time, use the ratio of the final improvement degree of the neuroregulator to the patient's current respiratory dysfunction degree and the patient's current respiratory dysfunction degree as the neuroregulator's participation degree in the patient's respiratory assistance.

6. The respiratory assistance system of the diaphragm pacemaker and the neuroregulator linked together according to claim 5, characterized in that: The comparison table inference submodule includes: An instance acquisition unit, used for acquiring a large number of linked breathing assistance instances of diaphragm pacemakers and neuroregulators, and acquiring the breathing assistance action time and actual improvement degree of the diaphragm pacemaker and the breathing assistance action time and actual improvement degree of the neuroregulator in each linked breathing assistance instance; An array construction unit, used for generating an assistive breathing array of each linked breathing assistance instance based on the respiratory assistive action time and actual improvement degree of the diaphragm pacemaker and the respiratory assistive action time and actual improvement degree of the neuroregulator in each linked breathing assistance instance; A network structure building unit is used to calculate the similarity between the auxiliary breathing action arrays of the two-by-two linked breathing assistance instances, take the average value of all similarities involved in each auxiliary breathing action array as the centrality of each auxiliary breathing action array, and build an instance array network based on the similarity between the auxiliary breathing action array with the maximum centrality and the auxiliary breathing action array of the two-by-two linked breathing assistance instances; The path crawling unit is used to crawl and screen all extended paths in the instance array network in sequence to obtain the optimal crawling path of the diaphragm pacemaker and the optimal crawling path of the neuroregulator, and determine the extreme improvement degree - average improvement rate comparison table of the diaphragm pacemaker for the patient based on the optimal crawling path of the diaphragm pacemaker. At the same time, determine the extreme improvement degree - average improvement rate comparison table of the neuroregulator for the patient based on the optimal crawling path of the neuroregulator.

7. The respiratory assistance system in which the diaphragm pacemaker and the neuroregulator are linked according to claim 5, characterized in that: The final improvement level is determined by the submodules, including: A first constraint unit is used to determine all possible value combinations of the improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree that meet the first constraint condition; The second constraint unit is used to screen out a group of possible value combinations that meet the second constraint condition from all possible value combinations of the degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker and the degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator that meet the first constraint condition, as the final screened possible value combinations, and use the degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker and the degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator in the final screened possible value combinations as the final degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker and the final degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator that meet the constraint condition.

8. The respiratory assistance system in which the diaphragm pacemaker and the neuroregulator are linked according to claim 7, characterized in that: The first constraint condition includes: The sum of the improvement degree of the diaphragm pacemaker on the patient's current respiratory dysfunction degree and the improvement degree of the neuroregulator on the patient's current respiratory dysfunction degree is equal to the patient's current respiratory dysfunction degree.

9. The respiratory assistance system of the diaphragm pacemaker and the neuroregulator linked together according to claim 7, characterized in that: The second constraint condition includes: The sum of the average improvement rate corresponding to the degree of improvement of the patient's current respiratory dysfunction degree by the diaphragm pacemaker in the comparison table of the patient's limit improvement degree - average improvement rate and the average improvement rate corresponding to the degree of improvement of the patient's current respiratory dysfunction degree by the neuroregulator in the comparison table of the patient's limit improvement degree - average improvement rate is the largest.

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