A fully automatic cardiopulmonary resuscitation system and a cardiopulmonary resuscitation control method

Abstract

The embodiment of the present application provides a fully automatic cardiopulmonary resuscitation system and a cardiopulmonary resuscitation control method, which relates to the field of medical device technology. The cardiopulmonary resuscitation control module includes: a data acquisition submodule, which is used to acquire first data, a first control parameter, and an actual operating parameter; a parameter determination submodule, which is used to determine a first response parameter of a response parameter item based on the difference between the actual operating parameter and the first control parameter; a quality assessment submodule, which is used to assess the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter and the first data; a cardiopulmonary resuscitation control submodule, which is used to determine a control parameter corresponding to the actual resuscitation quality as a second control parameter, and send a control instruction to the cardiopulmonary resuscitation function component according to the second control parameter. The system provided by this embodiment can realize the integration and full automation of cardiopulmonary resuscitation.

Description

Technical Field

[0001] The present application relates to the field of medical device technology, and in particular to a fully automatic cardiopulmonary resuscitation system and a cardiopulmonary resuscitation control method. Background Art

[0002] Cardiopulmonary resuscitation is an emergency measure for patients with cardiac arrest. Cardiopulmonary resuscitation usually includes compression, ventilation and defibrillation. Cardiopulmonary resuscitation can help patients establish temporary blood perfusion and breathing, promote the recovery of mechanical activity of the heart, and eventually restore autonomous breathing and circulation. At present, how to achieve the integration and intelligence of cardiopulmonary resuscitation has become an urgent problem to be solved. Summary of the invention

[0003] The purpose of the embodiments of the present application is to provide a fully automatic cardiopulmonary resuscitation system and a cardiopulmonary resuscitation control method to achieve integrated and intelligent cardiopulmonary resuscitation. The specific technical solution is as follows:

[0004] In a first aspect, an embodiment of the present application provides a fully automatic cardiopulmonary resuscitation system, the system comprising a monitoring module, a cardiopulmonary resuscitation control module and a cardiopulmonary resuscitation function component, the cardiopulmonary resuscitation function component comprising a compression function component, a ventilation function component and a defibrillation function component:

[0005] The monitoring module is used to collect first data representing the patient's current physiological information, and to collect first control parameters and actual operating parameters during the current cardiopulmonary resuscitation execution process, wherein the first data includes the patient's ECG signal, chest impedance signal, and pulse oximetry signal;

[0006] The cardiopulmonary resuscitation control module comprises:

[0007] A data acquisition submodule, used to acquire the first data, the first control parameter and the actual operation parameter;

[0008] a parameter determination submodule, configured to determine a first response parameter of a response parameter item based on a difference between the actual operating parameter and the first control parameter, wherein the response parameter item represents a data parameter item of the patient's response to the current cardiopulmonary resuscitation;

[0009] a quality assessment submodule, configured to assess an actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter and the first data;

[0010] The cardiopulmonary resuscitation control submodule is used to determine a control parameter corresponding to the actual resuscitation quality as a second control parameter, and send a control instruction to the cardiopulmonary resuscitation function component according to the second control parameter, so that the cardiopulmonary resuscitation function component performs cardiopulmonary resuscitation on the patient according to the second control parameter.

[0011] In one embodiment of the present application, the above-mentioned quality assessment submodule includes:

[0012] A first association determination unit, configured to analyze a second response parameter of the response parameter item based on the first data, and determine a first degree of association between the first response parameter and the second response parameter;

[0013] a coefficient determination unit, configured to determine a target coefficient based on the first degree of association;

[0014] The quality evaluation unit is used to evaluate the actual resuscitation quality of the cardiopulmonary resuscitation currently performed on the patient based on the first response parameter, the second response parameter and the target coefficient.

[0015] In one embodiment of the present application, the cardiopulmonary resuscitation control module further includes a second association determination unit:

[0016] The second association determination unit is used to obtain second data representing environmental information of the patient's current environment before the coefficient determination unit, and analyze the third response parameter of the response parameter item based on the second data to determine a second degree of association between the third response parameter and the first response parameter;

[0017] The coefficient determination unit is specifically configured to determine a target coefficient based on the first degree of association and the second degree of association;

[0018] The quality assessment unit is specifically configured to assess the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter, the third response parameter and the target coefficient.

[0019] In one embodiment of the present application, the cardiopulmonary resuscitation control module further includes a third association determination unit:

[0020] The third correlation determination unit is used to obtain the third data of the patient's historical condition information before the coefficient determination unit, extract the fourth response parameter of the response parameter item in the third data, and determine the third correlation degree between the fourth response parameter and the first response parameter;

[0021] The coefficient determination unit is used to determine a target coefficient based on the first degree of association, the second degree of association, and the third degree of association.

[0022] In one embodiment of the present application, the above-mentioned quality assessment submodule is specifically used to input the first response parameter and the first data into a pre-trained quality assessment model to obtain the parameters output by the quality assessment model as the actual resuscitation quality of cardiopulmonary resuscitation performed on the patient; wherein the quality assessment model is a model obtained by pre-training the initial neural network model and used to estimate the quality of cardiopulmonary resuscitation.

[0023] In a second aspect, an embodiment of the present application provides a cardiopulmonary resuscitation control method, the method comprising:

[0024] Collecting first data representing the patient's current physiological information, and collecting first control parameters and actual operating parameters during the current cardiopulmonary resuscitation execution process, wherein the first data includes the patient's ECG signal, chest impedance signal, and pulse oximetry signal;

[0025] Determine a first response parameter of a response parameter item based on a difference between the actual operating parameter and the first control parameter, wherein the response parameter item represents a data parameter item of the patient's response to the current cardiopulmonary resuscitation;

[0026] Based on the first response parameter and the first data, evaluating an actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient;

[0027] A control parameter corresponding to the actual resuscitation quality is determined as a second control parameter, and a control instruction is sent to the cardiopulmonary resuscitation function component according to the second control parameter, so that the cardiopulmonary resuscitation function component performs cardiopulmonary resuscitation on the patient according to the second control parameter.

[0028] In one embodiment of the present application, the evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter and the first data includes:

[0029] Based on the first data, analyzing a second response parameter of the response parameter item to determine a first correlation between the first response parameter and the second response parameter;

[0030] Based on the first correlation degree, determining a target coefficient;

[0031] An actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient is evaluated based on the first response parameter, the second response parameter, and the target coefficient.

[0032] In one embodiment of the present application, before determining the target coefficient based on the first correlation degree, the method further includes:

[0033] Acquire second data representing environmental information of the patient's current environment, analyze a third response parameter of the response parameter item based on the second data, and determine a second correlation between the third response parameter and the first response parameter;

[0034] The determining the target coefficient based on the first degree of association includes: determining the target coefficient based on the first degree of association and the second degree of association;

[0035] The evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter and the target coefficient includes: evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter, the third response parameter and the target coefficient.

[0036] In one embodiment of the present application, before determining the target coefficient based on the first correlation degree and the second correlation degree, the method further includes: acquiring third data of the patient's historical condition information, extracting a fourth response parameter of the response parameter item in the third data, and determining a third correlation degree between the fourth response parameter and the first response parameter;

[0037] The determining the target coefficient based on the first degree of association and the second degree of association includes: determining the target coefficient based on the first degree of association, the second degree of association and a third degree of association;

[0038] The evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently performed on the patient based on the first response parameter, the second response parameter, the third response parameter and the target coefficient includes: evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently performed on the patient based on the first response parameter, the second response parameter, the third response parameter, the fourth response parameter and the target coefficient.

[0039] In one embodiment of the present application, the evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter and the target coefficient includes:

[0040] The first response parameter and the first data are input into a pre-trained quality assessment model to obtain the parameters output by the quality assessment model as the actual resuscitation quality of cardiopulmonary resuscitation performed on the patient; wherein the quality assessment model is a model obtained by pre-training an initial neural network model and used to estimate the quality of cardiopulmonary resuscitation.

[0041] As can be seen from the above, using the system provided by the embodiment of the present application, the cardiopulmonary resuscitation system includes a monitoring module, a cardiopulmonary resuscitation control module and a cardiopulmonary resuscitation function component, and the cardiopulmonary resuscitation function component includes a compression function component, a ventilation function component and a defibrillation function component. The cardiopulmonary resuscitation control module evaluates the current cardiopulmonary resuscitation quality based on the data collected by the monitoring module, and re-determines the control parameters of the cardiopulmonary resuscitation based on the evaluated cardiopulmonary resuscitation quality, so that the cardiopulmonary resuscitation can be dynamically adjusted to adapt to the current cardiopulmonary resuscitation quality, thereby realizing the integration and intelligence of cardiopulmonary resuscitation.

[0042] In addition, in this embodiment, the quality of cardiopulmonary resuscitation is determined based on the first response parameter and the first data. Since the first response parameter represents the patient's response information to the current cardiopulmonary resuscitation, indicating the personalized dynamic information of the patient's response to the cardiopulmonary resuscitation, and the first data reflects the real-time dynamic information of the current patient's physiological parameters, the above two types of data can be used to comprehensively and accurately evaluate the quality of the cardiopulmonary resuscitation applied to the current patient. Then, the second control parameter determined based on the above cardiopulmonary resuscitation quality is more accurately adapted to the current actual cardiopulmonary resuscitation environment, thereby improving the accuracy of adaptive control.

[0043] Of course, implementing any product or method of the present application does not necessarily require achieving all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other embodiments can also be obtained based on these drawings.

[0045] Figure 1 A schematic diagram of a cardiopulmonary resuscitation system structure provided in an embodiment of the present application;

[0046] Figure 2 A schematic diagram of the structure of a first fully automatic cardiopulmonary resuscitation system provided in an embodiment of the present application;

[0047] Figure 3 A schematic diagram of the structure of a second fully automatic cardiopulmonary resuscitation system provided in an embodiment of the present application;

[0048] Figure 4 A schematic diagram of the structure of a third fully automatic cardiopulmonary resuscitation system provided in an embodiment of the present application;

[0049] Figure 5 A schematic diagram of the structure of a fourth fully automatic cardiopulmonary resuscitation system provided in an embodiment of the present application;

[0050] Figure 6 A flowchart of a cardiopulmonary resuscitation control method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field based on the present application belong to the scope of protection of the present application.

[0052] Before describing the embodiments of the present application, the structure of the cardiopulmonary resuscitation system provided by the present application is briefly described first.

[0053] See also Figure 1 The cardiopulmonary resuscitation system includes a monitoring module, a cardiopulmonary resuscitation control module and a cardiopulmonary resuscitation function component, wherein the cardiopulmonary resuscitation function component includes a compression function component, a ventilation function component and a defibrillation function component, each function component is used to realize a corresponding function, such as the compression function component is used to realize the compression function.

[0054] The monitoring module is mainly used to collect, process and analyze data. The front end of the monitoring module can be coupled with a display interface to display the collected and analyzed data.

[0055] The cardiopulmonary resuscitation control module is mainly used to determine the control parameters of the cardiopulmonary resuscitation function component and send the control instructions containing the control parameters so that the cardiopulmonary resuscitation function component performs corresponding operations according to the control parameters.

[0056] Secondly, the application scenario of this application is briefly described. This application is applied to the process of cardiopulmonary resuscitation. In this scenario, the existing technology usually performs cardiopulmonary resuscitation on patients according to fixed control parameters, but the patient's heart performance is dynamically changing, and the fixed control parameters are inevitably difficult to match the current dynamically changing performance. Based on this, the system provided by this application can realize adaptive control of cardiopulmonary resuscitation, provide patients with better cardiopulmonary resuscitation first aid measures, and achieve high automation and intelligence.

[0057] The following is a detailed description of the embodiments of the present application.

[0058] See also Figure 2 , Figure 2 A schematic diagram of the structure of the first fully automatic cardiopulmonary resuscitation system provided in an embodiment of the present application.

[0059] The monitoring module 201 is used to collect first data representing the patient's current physiological information, and collect first control parameters and actual operating parameters during the current cardiopulmonary resuscitation execution process.

[0060] The above-mentioned first data is used to characterize the patient's current physiological information, and the first data may include ECG signals, chest impedance signals, pulse oximetry signals, etc.

[0061] The first control parameter represents the control information of the current cardiopulmonary resuscitation. The cardiopulmonary resuscitation function component currently performs the corresponding function according to the above-mentioned first control parameter. The first control parameter may include compression depth, compression frequency, compression duration, ventilation concentration, ventilation frequency, compression-ventilation frequency ratio, defibrillation waveform, defibrillation current, defibrillation voltage, etc.

[0062] The actual operating parameters represent the actual operating information during the execution of cardiopulmonary resuscitation, such as actual compression depth, actual compression duration, actual compression frequency; actual ventilation frequency, actual ventilation concentration, actual ventilation duration, actual defibrillation waveform, actual defibrillation current, actual defibrillation voltage, etc.

[0063] The above data and parameters can be collected through corresponding sensors. Various data sensors collect raw data in real time and send the raw data to the monitoring module. The monitoring module can pre-process the raw data, such as denoising and standardization, so as to collect the first data and actual operating parameters.

[0064] The cardiopulmonary resuscitation control module 202 includes:

[0065] The data acquisition submodule 2021 is used to acquire first data, first control parameters and actual operation parameters.

[0066] The first data acquisition submodule can send a data acquisition instruction to the monitoring module. The monitoring module responds to the instruction and sends the required data to the first data acquisition submodule. The first data acquisition submodule can thereby acquire the first data, the first control parameter and the actual operation parameter.

[0067] The parameter determination submodule 2022 is used to determine a first response parameter of the response parameter item based on the difference between the actual operating parameter and the first control parameter.

[0068] The above-mentioned response parameter items represent the data parameter items of the patient's response to the current cardiopulmonary resuscitation. Due to the influence of various complex factors, different patients will have different responses to cardiopulmonary resuscitation with the same control parameters, and the parameter data of the response parameter items are the data representing the above-mentioned response information. In one embodiment of the present application, the response parameter items may include vascular elasticity, vascular compliance, chest elasticity, chest compliance, etc.

[0069] Since the actual operating parameters represent the current actual operating information, that is, the actual operating information generated after cardiopulmonary resuscitation is applied to the patient, and the first control parameter can be understood as the target operating information of cardiopulmonary resuscitation, that is, the operating information that the current cardiopulmonary resuscitation is expected to achieve; then, the difference between the actual operating parameters and the first control parameters can reflect the patient's response information to the current cardiopulmonary resuscitation, that is, the first response parameter that can accurately characterize the response parameter item.

[0070] One implementation method for determining the first response parameter is to determine the parameter type having a parameter difference between the actual operating parameter and the first control parameter, determine the target type of the response parameter item corresponding to the above parameter type, and input the parameter difference into the parameter calculation model corresponding to the target type to obtain the parameter output by the parameter calculation model as the first response parameter.

[0071] For example: when it is determined that the parameter type with parameter difference is the compression depth type, the target type of the response parameter item corresponding to the above compression depth type is chest compliance, and a parameter calculation model of the target type of each response parameter item is set in advance. The parameter difference of the compression depth type is input into the above parameter calculation model to obtain the parameter output by the parameter calculation model as the first response parameter.

[0072] The quality assessment submodule 2023 is used to assess the actual resuscitation quality of the cardiopulmonary resuscitation performed on the patient based on the first response parameter and the first data.

[0073] The actual resuscitation quality is used to characterize the real-time resuscitation quality of the current cardiopulmonary resuscitation for the patient. Since the first response parameter characterizes the personalized information of the patient's response to cardiopulmonary resuscitation, and the first data reflects the real-time dynamic information of the current patient's physiological parameters, the above two types of data can be used to comprehensively and accurately determine the resuscitation quality of cardiopulmonary resuscitation.

[0074] In one implementation of determining the actual resuscitation quality, the first response parameter and the first data may be input into a pre-trained quality assessment model to obtain parameters output by the quality assessment model as the actual resuscitation quality of cardiopulmonary resuscitation performed on the patient.

[0075] The above-mentioned quality assessment model is a model obtained by pre-training the initial neural network model and is used to estimate the quality of cardiopulmonary resuscitation.

[0076] Other implementations for determining actual resuscitation quality can be found in the following Figure 3 The corresponding embodiments are not described in detail here.

[0077] The cardiopulmonary resuscitation control submodule 2024 is used to determine a control parameter corresponding to the actual resuscitation quality as a second control parameter, and send a control instruction to the cardiopulmonary resuscitation function component according to the second control parameter, so that the cardiopulmonary resuscitation function component performs cardiopulmonary resuscitation on the patient according to the second control parameter.

[0078] A first implementation method for determining the second control parameter is: presetting a correspondence between the resuscitation quality and the control parameter, and determining the control parameter corresponding to the actual resuscitation quality according to the correspondence as the second control parameter.

[0079] The second implementation method for determining the second control parameter is: according to the corresponding relationship, the control parameter corresponding to the actual replication quality is determined; if the parameter difference between the re-determined control parameter and the first control parameter is greater than a preset difference threshold, the re-determined control parameter is determined as the second control parameter; otherwise, the control parameter is not updated, that is, the first control parameter remains as the current control parameter.

[0080] As can be seen from the above, the cardiopulmonary resuscitation system provided by the present embodiment includes a monitoring module, a cardiopulmonary resuscitation control module and a cardiopulmonary resuscitation function component, and the cardiopulmonary resuscitation function component includes a compression function component, a ventilation function component and a defibrillation function component. The cardiopulmonary resuscitation control module evaluates the current cardiopulmonary resuscitation quality based on the data collected by the monitoring module, and re-determines the control parameters of the cardiopulmonary resuscitation based on the evaluated cardiopulmonary resuscitation quality, so that the cardiopulmonary resuscitation can be dynamically adjusted to adapt to the current cardiopulmonary resuscitation quality, thereby realizing the integration and intelligence of cardiopulmonary resuscitation.

[0081] In addition, in this embodiment, the quality of cardiopulmonary resuscitation is determined based on the first response parameter and the first data. Since the first response parameter represents the patient's response information to the current cardiopulmonary resuscitation, indicating the personalized dynamic information of the patient's response to the cardiopulmonary resuscitation, and the first data reflects the real-time dynamic information of the current patient's physiological parameters, the above two types of data can be used to comprehensively and accurately evaluate the quality of the cardiopulmonary resuscitation applied to the current patient. Then, the second control parameter determined based on the above cardiopulmonary resuscitation quality is more accurately adapted to the current actual cardiopulmonary resuscitation environment, thereby improving the accuracy of adaptive control.

[0082] In the aforementioned quality assessment submodule 2023, in addition to the implementation of the aforementioned implementation, the following 3023-3025 can also be used for implementation. Figure 3 , Figure 3 A schematic diagram of the structure of a second fully automatic cardiopulmonary resuscitation system provided in an embodiment of the present application, the system comprising:

[0083] The monitoring module 301 is used to collect first data representing the patient's current physiological information, and collect first control parameters and actual operating parameters during the current cardiopulmonary resuscitation execution process.

[0084] The first data includes the patient's ECG signal, chest impedance signal, and pulse oximetry signal.

[0085] The cardiopulmonary resuscitation control module 302 includes:

[0086] The data acquisition submodule 3021 is used to acquire first data, first control parameters and actual operation parameters.

[0087] The parameter determination submodule 3022 is used to determine a first response parameter of the response parameter item based on the difference between the actual operating parameter and the first control parameter.

[0088] The above-mentioned response parameter items represent data parameter items of the patient's response to the current cardiopulmonary resuscitation.

[0089] The above 301, 3021-3022 are the same as the aforementioned 201, 2021-2022, and will not be repeated here.

[0090] The first association determination unit 3023 is configured to analyze the second response parameter of the response parameter item based on the first data, and determine a first association degree between the first response parameter and the second response parameter.

[0091] The difference between the second response parameter and the first response parameter is that the data sources are different. The first response parameter is determined based on the control information of cardiopulmonary resuscitation, and the second response parameter is determined based on the first data, that is, the patient's physiological information. Therefore, although both are parameter values ​​of the response parameter item, the specific values ​​are different due to different data sources.

[0092] An implementation method of analyzing the second response parameter is: extracting data features of the first data, and determining the second response parameter based on a corresponding relationship between the data features and the response parameter.

[0093] One implementation of determining the first correlation degree is: using any correlation analysis algorithm in the prior art to analyze the correlation between the first response parameter and the second response parameter as the first correlation degree.

[0094] The coefficient determination unit 3024 is used to determine the target coefficient based on the first correlation degree.

[0095] One implementation method of determining the target coefficient is: normalizing the first correlation degree and determining the value obtained by the processing as the target coefficient.

[0096] Other implementations for determining the target coefficient may refer to the subsequent embodiments and will not be described in detail here.

[0097] The quality assessment submodule 3025 is used to assess the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter and the target coefficient.

[0098] Since the first response parameter reflects the patient response information from the perspective of cardiopulmonary resuscitation control, and the second response parameter reflects the patient response information from the perspective of patient physiological information, the actual resuscitation quality of the current cardiopulmonary resuscitation can be evaluated more comprehensively and accurately from the above two different perspectives, thereby further improving the accuracy of subsequent cardiopulmonary resuscitation adaptive control.

[0099] One implementation method for evaluating the actual resuscitation quality is: based on the target coefficient, determine the weights corresponding to the first response parameter and the second response parameter respectively, fuse the first response parameter and the second response parameter according to the corresponding weights, and determine the resuscitation quality corresponding to the fused response data as the actual resuscitation quality of the current cardiopulmonary resuscitation.

[0100] The implementation method of determining the weights corresponding to the two response parameters is as follows: taking the target coefficient as the weight of the first response parameter, and taking the absolute value of the difference between the target coefficient and 1 as the weight of the second response parameter.

[0101] The cardiopulmonary resuscitation control submodule 3026 is used to determine a control parameter corresponding to the actual resuscitation quality as a second control parameter, and send a control instruction to the cardiopulmonary resuscitation function component according to the second control parameter, so that the cardiopulmonary resuscitation function component performs cardiopulmonary resuscitation on the patient according to the second control parameter.

[0102] The parameter adjustment submodule 3026 is the same as the aforementioned 2024 and will not be described again here.

[0103] In the aforementioned Figure 3 Based on the corresponding embodiment, the cardiopulmonary resuscitation control module further includes a second association determination unit. Based on this, see Figure 4 , Figure 4 The third fully automatic cardiopulmonary resuscitation system provided in the embodiment of the present application is a schematic diagram of the structure of the system, the system comprising:

[0104] The monitoring module 401 is used to collect first data representing the patient's current physiological information, and collect first control parameters and actual operating parameters during the current cardiopulmonary resuscitation execution process.

[0105] The first data includes the patient's ECG signal, chest impedance signal, and pulse oximetry signal.

[0106] The cardiopulmonary resuscitation control module 402 includes:

[0107] The data acquisition submodule 4021 is used to acquire first data, first control parameters and actual operation parameters.

[0108] The parameter determination submodule 4022 is used to determine a first response parameter of the response parameter item based on the difference between the actual operating parameter and the first control parameter.

[0109] The above-mentioned response parameter items represent data parameter items of the patient's response to the current cardiopulmonary resuscitation.

[0110] The first association determination unit 4023 is configured to analyze the second response parameter of the response parameter item based on the first data, and determine a first association degree between the first response parameter and the second response parameter.

[0111] The second correlation determination unit 4024 is used to obtain second data representing environmental information of the patient's current environment, analyze the third response parameter of the response parameter item based on the second data, and determine a second correlation degree between the third response parameter and the first response parameter.

[0112] The second data is used to characterize the environmental information of the patient's current environment, such as the type, thickness, softness, ambient temperature, humidity, etc. of the surface on which the patient lies. The second data can be obtained through manual input by the user, such as the user can input relevant data through the user interface; or can be collected by corresponding sensors.

[0113] Similarly, since the data sources of the third response parameter and the first response parameter are different, although both are parameter values ​​of the response parameter item, their specific values ​​are different.

[0114] An implementation of analyzing the third response parameter is: extracting data features of the second data, and determining the third response parameter based on a corresponding relationship between the data features and the response parameters.

[0115] The coefficient determination unit 4025 is specifically configured to determine a target coefficient based on the first degree of association and the second degree of association.

[0116] One implementation method for determining the target coefficient is: normalizing the first correlation degree, normalizing the second correlation degree, and calculating the mean of the two processed data as the target coefficient.

[0117] The quality assessment submodule 4026 is used to assess the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter, the third response parameter and the target coefficient.

[0118] Since the first response parameter reflects the patient response information from the perspective of cardiopulmonary resuscitation control, the second response parameter reflects the patient response information from the perspective of patient physiological information, and the third response parameter reflects the patient response information from the perspective of current environmental information, the actual resuscitation quality of the current cardiopulmonary resuscitation can be evaluated more comprehensively and accurately from the above three different perspectives, thereby further improving the accuracy of subsequent cardiopulmonary resuscitation adaptive control.

[0119] One implementation method for evaluating the actual resuscitation quality is: based on the target coefficient, determine the weights corresponding to the first response parameter, the second response parameter, and the third response parameter, respectively; according to the corresponding weights, fuse the first response parameter, the second response parameter, and the third response parameter; determine the resuscitation quality corresponding to the fused response data as the actual resuscitation quality of the current cardiopulmonary resuscitation.

[0120] The implementation method for determining the weights corresponding to the three response parameters is: taking the target coefficient as the weight of the first response parameter, and taking the absolute value of the difference between the target coefficient and 1 as the weights of the second response parameter and the third response parameter.

[0121] The cardiopulmonary resuscitation control submodule 4027 is used to determine a control parameter corresponding to the actual resuscitation quality as a second control parameter, and send a control instruction to the cardiopulmonary resuscitation function component according to the second control parameter, so that the cardiopulmonary resuscitation function component performs cardiopulmonary resuscitation on the patient according to the second control parameter.

[0122] In the aforementioned Figure 4 Based on the corresponding embodiment, the cardiopulmonary resuscitation control module further includes a third association determination unit. Based on this, see Figure 5 , Figure 5 The fourth fully automatic cardiopulmonary resuscitation system provided in the embodiment of the present application is a schematic diagram of the structure of the system, the system comprising:

[0123] The monitoring module 501 is used to collect first data representing the patient's current physiological information, and collect first control parameters and actual operating parameters during the current cardiopulmonary resuscitation execution process.

[0124] The first data includes the patient's ECG signal, chest impedance signal, and pulse oximetry signal.

[0125] The cardiopulmonary resuscitation control module 502 includes:

[0126] The data acquisition submodule 5021 is used to acquire first data, first control parameters and actual operation parameters.

[0127] The parameter determination submodule 5022 is used to determine a first response parameter of the response parameter item based on the difference between the actual operating parameter and the first control parameter.

[0128] The above-mentioned response parameter items represent data parameter items of the patient's response to the current cardiopulmonary resuscitation.

[0129] The first association determination unit 5023 is configured to analyze the second response parameter of the response parameter item based on the first data, and determine a first degree of association between the first response parameter and the second response parameter.

[0130] The second correlation determination unit 5024 is used to obtain second data representing environmental information of the patient's current environment, analyze the third response parameter of the response parameter item based on the second data, and determine a second correlation degree between the third response parameter and the first response parameter.

[0131] The third correlation determination unit 5025 is used to obtain third data of the patient's historical condition information, extract the fourth response parameter of the response parameter item in the third data, and determine a third correlation degree between the fourth response parameter and the first response parameter.

[0132] The third data is used to characterize the patient's historical medical condition information, such as previous cardiovascular conditions, family genetic diseases, etc. The third data can be read from the case database with authorization, or can be manually input by the user and obtained by the monitoring module.

[0133] Similarly, since the fourth response parameter and the first response parameter have different data sources, although both are parameter values ​​of the response parameter item, their specific values ​​are different.

[0134] An implementation of analyzing the fourth response parameter is: extracting data features of the third data, and determining the fourth response parameter based on a corresponding relationship between the data features and the response parameters.

[0135] The coefficient determination unit 5026 is specifically configured to determine a target coefficient based on the first degree of association, the second degree of association, and the third degree of association.

[0136] One implementation method for determining the target coefficient is: normalizing the first correlation degree, the second correlation degree, and the third correlation degree respectively, and calculating the average of the three processed data as the target coefficient.

[0137] The quality assessment submodule 5027 is used to assess the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter, the third response parameter, the fourth response parameter and the target coefficient.

[0138] Since the first response parameter reflects the patient response information from the perspective of cardiopulmonary resuscitation control, the second response parameter reflects the patient response information from the perspective of patient physiological information, the third response parameter reflects the patient response information from the perspective of current environmental information, and the fourth response parameter reflects the patient response information from the perspective of patient historical medical condition information, then the actual resuscitation quality of the current cardiopulmonary resuscitation can be evaluated more comprehensively and accurately from the above four different perspectives, thereby further improving the accuracy of subsequent cardiopulmonary resuscitation adaptive control.

[0139] One implementation method for evaluating the actual resuscitation quality is: based on the target coefficient, determine the weights corresponding to the first response parameter, the second response parameter, the third response parameter, and the fourth response parameter, respectively; according to the corresponding weights, fuse the first response parameter, the second response parameter, and the third response parameter; determine the resuscitation quality corresponding to the fused response data as the actual resuscitation quality of the current cardiopulmonary resuscitation.

[0140] The implementation method for determining the weights corresponding to the four response parameters is: taking the target coefficient as the weight of the first response parameter, and taking the absolute value of the difference between the target coefficient and 1 as the weights of the second response parameter, the third response parameter, and the fourth response parameter.

[0141] The cardiopulmonary resuscitation control submodule 5028 is used to determine a control parameter corresponding to the actual resuscitation quality as a second control parameter, and send a control instruction to the cardiopulmonary resuscitation function component according to the second control parameter, so that the cardiopulmonary resuscitation function component performs cardiopulmonary resuscitation on the patient according to the second control parameter.

[0142] See also Figure 6 , Figure 6 A schematic diagram of a cardiopulmonary resuscitation control method provided in an embodiment of the present application, the method comprising:

[0143] Step S601: collecting first data representing the patient's current physiological information, and collecting first control parameters and actual operating parameters during the current cardiopulmonary resuscitation execution process, wherein the first data includes the patient's ECG signal, chest impedance signal, and pulse oximetry signal;

[0144] Step S602: determining a first response parameter of a response parameter item based on a difference between the actual operating parameter and the first control parameter, wherein the response parameter item represents a data parameter item of the patient's response to the current cardiopulmonary resuscitation;

[0145] Step S603: evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter and the first data;

[0146] Step S604: Determine a control parameter corresponding to the actual resuscitation quality as a second control parameter, and send a control instruction to the cardiopulmonary resuscitation function component according to the second control parameter, so that the cardiopulmonary resuscitation function component performs cardiopulmonary resuscitation on the patient according to the second control parameter.

[0147] In one embodiment of the present application, the evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter and the first data includes:

[0148] Based on the first data, analyzing a second response parameter of the response parameter item to determine a first correlation between the first response parameter and the second response parameter;

[0149] Based on the first correlation degree, determining a target coefficient;

[0150] An actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient is evaluated based on the first response parameter, the second response parameter, and the target coefficient.

[0151] In one embodiment of the present application, before determining the target coefficient based on the first correlation degree, the method further includes:

[0152] Acquire second data representing environmental information of the patient's current environment, analyze a third response parameter of the response parameter item based on the second data, and determine a second correlation between the third response parameter and the first response parameter;

[0153] The determining the target coefficient based on the first degree of association includes: determining the target coefficient based on the first degree of association and the second degree of association;

[0154] The evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter and the target coefficient includes: evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter, the third response parameter and the target coefficient.

[0155] In one embodiment of the present application, before determining the target coefficient based on the first correlation degree and the second correlation degree, the method further includes: acquiring third data of the patient's historical condition information, extracting a fourth response parameter of the response parameter item in the third data, and determining a third correlation degree between the fourth response parameter and the first response parameter;

[0156] The determining the target coefficient based on the first degree of association and the second degree of association includes: determining the target coefficient based on the first degree of association, the second degree of association and a third degree of association;

[0157] The evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently performed on the patient based on the first response parameter, the second response parameter, the third response parameter and the target coefficient includes: evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently performed on the patient based on the first response parameter, the second response parameter, the third response parameter, the fourth response parameter and the target coefficient.

[0158] In one embodiment of the present application, the evaluating the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter and the target coefficient includes:

[0159] The first response parameter and the first data are input into a pre-trained quality assessment model to obtain the parameters output by the quality assessment model as the actual resuscitation quality of cardiopulmonary resuscitation performed on the patient; wherein the quality assessment model is a model obtained by pre-training an initial neural network model and used to estimate the quality of cardiopulmonary resuscitation.

[0160] As can be seen from the above, the cardiopulmonary resuscitation system provided by the present embodiment includes a monitoring module, a cardiopulmonary resuscitation control module and a cardiopulmonary resuscitation function component, and the cardiopulmonary resuscitation function component includes a compression function component, a ventilation function component and a defibrillation function component. The cardiopulmonary resuscitation control module evaluates the current cardiopulmonary resuscitation quality based on the data collected by the monitoring module, and re-determines the control parameters of the cardiopulmonary resuscitation based on the evaluated cardiopulmonary resuscitation quality, so that the cardiopulmonary resuscitation can be dynamically adjusted to adapt to the current cardiopulmonary resuscitation quality, thereby realizing the integration and intelligence of cardiopulmonary resuscitation.

[0161] In addition, in this embodiment, the quality of cardiopulmonary resuscitation is determined based on the first response parameter and the first data. Since the first response parameter represents the patient's response information to the current cardiopulmonary resuscitation, indicating the personalized dynamic information of the patient's response to the cardiopulmonary resuscitation, and the first data reflects the real-time dynamic information of the current patient's physiological parameters, the above two types of data can be used to comprehensively and accurately evaluate the quality of the cardiopulmonary resuscitation applied to the current patient. Then, the second control parameter determined based on the above cardiopulmonary resuscitation quality is more accurately adapted to the current actual cardiopulmonary resuscitation environment, thereby improving the accuracy of adaptive control.

[0162] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive Solid State Disk (SSD)), etc.

[0163] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0164] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the method embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0165] The above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application are included in the protection scope of the present application.

Claims

1. A fully automatic cardiopulmonary resuscitation system, characterized in that: The system includes a monitoring module, a cardiopulmonary resuscitation control module and a cardiopulmonary resuscitation function component, wherein the cardiopulmonary resuscitation function component includes a compression function component, a ventilation function component and a defibrillation function component: The monitoring module is used to collect first data representing the patient's current physiological information, and collect first control parameters and actual operating parameters during the current cardiopulmonary resuscitation execution process, wherein the first data includes the patient's ECG signal, chest impedance signal and pulse oximetry signal; The cardiopulmonary resuscitation control module comprises: A data acquisition submodule, used to acquire the first data, the first control parameter and the actual operation parameter; a parameter determination submodule, configured to determine a first response parameter of a response parameter item based on a difference between the actual operating parameter and the first control parameter, wherein the response parameter item represents a data parameter item of the patient's response to the current cardiopulmonary resuscitation, and the response parameter item includes vascular elasticity, vascular compliance, chest elasticity, and chest compliance; The parameter determination submodule is specifically used to determine the parameter type having a parameter difference between the actual operating parameter and the first control parameter, determine the target type of the response parameter item corresponding to the above parameter type, and input the parameter difference into the parameter calculation model corresponding to the target type to obtain the parameter output by the parameter calculation model as the first response parameter; a quality assessment submodule, configured to assess an actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter and the first data; The cardiopulmonary resuscitation control submodule is used to determine a control parameter corresponding to the actual resuscitation quality as a second control parameter, and send a control instruction to the cardiopulmonary resuscitation function component according to the second control parameter, so that the cardiopulmonary resuscitation function component performs cardiopulmonary resuscitation on the patient according to the second control parameter.

2. The system according to claim 1, characterized in that The quality assessment submodule comprises: A first association determination unit, configured to analyze a second response parameter of the response parameter item based on the first data, and determine a first degree of association between the first response parameter and the second response parameter; a coefficient determination unit, configured to determine a target coefficient based on the first degree of association; The quality evaluation unit is used to evaluate the actual resuscitation quality of the cardiopulmonary resuscitation currently performed on the patient based on the first response parameter, the second response parameter and the target coefficient.

3. The system according to claim 2, characterized in that The cardiopulmonary resuscitation control module further includes a second association determination unit: The second association determination unit is used to obtain second data representing environmental information of the patient's current environment before the coefficient determination unit, and analyze the third response parameter of the response parameter item based on the second data to determine a second degree of association between the third response parameter and the first response parameter; The coefficient determination unit is specifically configured to determine a target coefficient based on the first degree of association and the second degree of association; The quality assessment unit is specifically configured to assess the actual resuscitation quality of the cardiopulmonary resuscitation currently being performed on the patient based on the first response parameter, the second response parameter, the third response parameter and the target coefficient.

4. The system according to claim 3, characterized in that The cardiopulmonary resuscitation control module further includes a third association determination unit: The third correlation determination unit is used to obtain the third data of the patient's historical condition information before the coefficient determination unit, extract the fourth response parameter of the response parameter item in the third data, and determine the third correlation degree between the fourth response parameter and the first response parameter; The coefficient determination unit is used to determine a target coefficient based on the first degree of association, the second degree of association, and the third degree of association.

5. The system according to claim 1, characterized in that The quality assessment submodule is specifically used to input the first response parameter and the first data into a pre-trained quality assessment model to obtain the parameters output by the quality assessment model as the actual resuscitation quality of cardiopulmonary resuscitation performed on the patient; wherein the quality assessment model is a model obtained by pre-training the initial neural network model and used to estimate the quality of cardiopulmonary resuscitation.

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