An intelligent cardiopulmonary resuscitation system and a patient status assessment method

Abstract

The embodiment of the present application provides an intelligent cardiopulmonary resuscitation system and a patient status estimation method, which relates to the field of medical device technology. The above system includes a monitoring module, a patient status assessment module and a cardiopulmonary resuscitation functional component. The patient status assessment module includes: a first data acquisition submodule, which is used to acquire the target perfusion waveform and the actual operating parameters, and identify the signal feature points of the target perfusion waveform; a data identification submodule, which is used to identify the target circulation waveform that characterizes the patient's cardiac active circulation information in the target perfusion waveform based on the signal feature points and the actual operating parameters; a status assessment submodule, which is used to assess the patient's cardiac recovery status based on the target circulation waveform. The solution provided by this embodiment can realize the integration and intelligence of cardiopulmonary resuscitation.

Description

Technical Field

[0001] The present application relates to the field of medical device technology, and in particular to an intelligent cardiopulmonary resuscitation system and a patient status assessment method. Background Art

[0002] Cardiopulmonary resuscitation is an emergency measure for patients with cardiac arrest. It 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 spontaneous breathing and circulation. At present, how to achieve integrated and intelligent 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 an intelligent cardiopulmonary resuscitation system and a patient status assessment 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 an intelligent cardiopulmonary resuscitation system, the system comprising a monitoring module, a patient status assessment 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, wherein:

[0005] The monitoring module is used to collect the target perfusion waveform representing the current perfusion information of the patient's heart, and to collect the actual operating parameters during the current cardiopulmonary resuscitation execution;

[0006] The patient status assessment module comprises:

[0007] A first data acquisition submodule, used to acquire the target perfusion waveform and actual operating parameters, and identify signal feature points of the target perfusion waveform;

[0008] A data identification submodule, for identifying a target circulation waveform representing the patient's cardiac active circulation information in the target perfusion waveform based on the signal characteristic points and the actual operating parameters;

[0009] The state assessment submodule is used to assess the patient's cardiac recovery state based on the target cyclic waveform.

[0010] In one embodiment of the present application, the data identification submodule includes:

[0011] an alternative identification unit, configured to determine, based on the signal feature points, a sub-waveform of the target perfusion waveform that contains a signal peak value as an alternative cycle waveform;

[0012] The data identification unit is used to determine the cyclic waveform that does not match the actual operating parameters among the candidate cyclic waveforms as the target cyclic waveform that represents the patient's cardiac active circulation information.

[0013] In one embodiment of the present application, the target perfusion waveform includes: a pulse oximetry waveform and / or a chest impedance signal waveform.

[0014] In one embodiment of the present application, the candidate cyclic waveforms include a first candidate cyclic waveform of a pulse oximetry waveform and a second candidate cyclic waveform of a chest impedance signal waveform, and the data identification unit includes:

[0015] A first data identification subunit is used to determine a cyclic waveform that does not match the actual operating parameters in the first candidate cyclic waveform as the first cyclic waveform;

[0016] A second data identification subunit is used to determine a cyclic waveform that does not match the actual operating parameters in the second candidate cyclic waveform as the second cyclic waveform;

[0017] The third data identification subunit is used to determine a target cycle waveform based on the first cycle waveform and the second cycle waveform.

[0018] In one embodiment of the present application, the above-mentioned third data identification subunit is specifically used to extract the first parameter value of the preset waveform parameter item in the first cycle waveform, and extract the second parameter value of the preset waveform parameter item in the second cycle waveform. For each cycle waveform, the number of parameter values ​​that meet the preset numerical range corresponding to the preset waveform parameter item is counted, and the cycle waveform corresponding to the highest number is determined as the target cycle waveform.

[0019] In a second aspect, an embodiment of the present application provides a method for assessing a patient's condition, the method comprising:

[0020] Collecting a target perfusion waveform representing the current perfusion information of the patient's heart, collecting actual operating parameters during the current cardiopulmonary resuscitation execution process, and identifying signal feature points of the target perfusion waveform;

[0021] Based on the signal characteristic points and the actual operating parameters, identifying a target circulation waveform in the target perfusion waveform that represents the patient's cardiac active circulation information;

[0022] Based on the target cyclic waveform, the patient's cardiac recovery status is assessed.

[0023] In one embodiment of the present application, the identifying, based on the signal feature points and the actual operating parameters, a target circulation waveform representing the patient's cardiac active circulation information in the target perfusion waveform includes:

[0024] Based on the signal feature points, determining a sub-waveform of the target perfusion waveform that contains a signal peak as a candidate cyclic waveform;

[0025] A cyclic waveform among the candidate cyclic waveforms that does not match the actual operating parameters is determined as a target cyclic waveform that represents the patient's cardiac active circulation information.

[0026] In one embodiment of the present application, the target perfusion waveform includes: a pulse oximetry waveform and / or a chest impedance signal waveform.

[0027] In one embodiment of the present application, the candidate cyclic waveforms include a first candidate cyclic waveform of a pulse oximetry waveform and a second candidate cyclic waveform of a chest impedance signal waveform;

[0028] The step of determining a cyclic waveform that does not match the actual operating parameters among the candidate cyclic waveforms as a target cyclic waveform that represents the patient's cardiac active circulation information includes:

[0029] Determine a cyclic waveform that does not match the actual operating parameters in the first candidate cyclic waveform as the first cyclic waveform;

[0030] Determine a cyclic waveform that does not match the actual operating parameters in the second candidate cyclic waveform as the second cyclic waveform;

[0031] A target cyclic waveform is determined based on the first cyclic waveform and the second cyclic waveform.

[0032] In one embodiment of the present application, the above-mentioned determining the target cycle waveform based on the first cycle waveform and the second cycle waveform includes:

[0033] Extracting a first parameter value of a preset waveform parameter item in the first cyclic waveform, and extracting a second parameter value of a preset waveform parameter item in the second cyclic waveform;

[0034] For each cyclic waveform, the number of parameter values ​​that meet the preset numerical range corresponding to the preset waveform parameter item is counted, and the cyclic waveform corresponding to the highest number is determined as the target cyclic waveform.

[0035] The cardiopulmonary resuscitation system provided by the embodiment of the present application is applied, and the cardiopulmonary resuscitation system includes a monitoring module, a patient status assessment 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 patient status assessment module assesses the patient's cardiac recovery status based on the data collected by the monitoring module, thereby realizing the integration and intelligence of cardiopulmonary resuscitation.

[0036] Moreover, in this embodiment, the signal feature points of the target perfusion waveform reflect the perfusion information of the patient's current heart, that is, the overall perfusion situation of the patient's current heart; the actual operating parameters are the real-time operating parameters of cardiopulmonary resuscitation, and cardiopulmonary resuscitation, as an auxiliary means, directly affects the perfusion situation of the patient's heart. Therefore, the actual operating parameters reflect the perfusion situation of the patient's heart from the perspective of cardiopulmonary resuscitation. Under the condition of cardiopulmonary resuscitation assistance, the overall perfusion situation of the heart is affected by the patient's own cardiac function and cardiopulmonary resuscitation assistance. Therefore, based on the signal feature points of the target perfusion waveform and the actual operating parameters, the perfusion information of the patient's heart caused by the patient's own cardiac function can be accurately determined, making the identified target circulation waveform close to the current real situation. And the patient's heart recovery state is directly related to the patient's own cardiac function, so that the accuracy of the evaluated patient's heart recovery state is high, realizing high-precision and intelligent patient state evaluation.

[0037] Of course, it is not necessary for any product or method implementing the present application to achieve all the above-mentioned advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application, and those of ordinary skill in the art can also obtain other embodiments based on these drawings.

[0039] Figure 1 It is a schematic structural diagram of a cardiopulmonary resuscitation system provided by an embodiment of the present application;

[0040] Figure 2 It is a structural diagram of the first intelligent cardiopulmonary resuscitation system provided by an embodiment of the present application;

[0041] Figure 3a It is a structural diagram of the second intelligent cardiopulmonary resuscitation system provided by an embodiment of the present application;

[0042] Figure 3b It is a schematic diagram of a target perfusion waveform provided by an embodiment of the present application;

[0043] Figure 4 It is a structural diagram of the third intelligent cardiopulmonary resuscitation system provided by an embodiment of the present application;

[0044] Figure 5 It is a schematic flowchart of a patient state evaluation method provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] 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.

[0046] Before describing the embodiments of the present application, the structure of the cardiopulmonary resuscitation system provided by the present application is briefly described first.

[0047] See also Figure 1 The cardiopulmonary resuscitation system includes a monitoring module, a patient status assessment 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 implement a corresponding function, such as the compression function component is used to press the patient's chest.

[0048] 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.

[0049] The patient status assessment module is mainly used to assess the patient's current status, such as cardiac recovery status,

[0050] 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 requires medical staff to manually judge the patient's status based on experience, but this method is too dependent on the medical experience of medical staff, and the timeliness and accuracy are difficult to guarantee. Based on this, the system provided by this application can realize the intelligent evaluation of the patient's status, so as to provide patients with better cardiopulmonary resuscitation emergency measures, and achieve high automation and intelligence.

[0051] The following is a detailed description of the embodiments of the present application.

[0052] See also Figure 2 , Figure 2 A schematic diagram of the structure of the first intelligent cardiopulmonary resuscitation system provided in an embodiment of the present application.

[0053] The monitoring module 201 is used to collect the target perfusion waveform representing the current perfusion information of the patient's heart, and collect the actual operating parameters during the current cardiopulmonary resuscitation execution process.

[0054] The above target perfusion waveform is used to characterize the patient's current heart perfusion information. The current heart perfusion information refers to the actual perfusion of the patient's heart as a whole under the current cardiopulmonary resuscitation assistance conditions. The heart perfusion information is an important indicator for evaluating the heart's blood supply.

[0055] Parameters that characterize the patient's current heart perfusion information may be coronary artery perfusion pressure, cardiac output, mean diastolic pressure and other parameters. However, the above parameter data are usually collected in an invasive manner, which is more harmful to the patient. Based on this, in one embodiment of the present application, the above target perfusion waveform may be a pulse oximetry waveform and / or a thoracic impedance waveform. Since the above pulse oximetry and thoracic impedance can be collected in a non-invasive manner, it is possible to reduce harm to the patient and reduce risks.

[0056] The pulse oximetry waveform is the signal waveform of the pulse oximetry parameter. Pulse oximetry is an indicator of the oxygen content in the blood, which can reflect the patient's cardiac perfusion status information. The thoracic impedance waveform is the signal waveform of the thoracic impedance parameter. The thoracic impedance is an important indicator reflecting the patient's cardiopulmonary function status, and can also provide the patient's cardiac perfusion status information.

[0057] The actual operating parameters represent the actual operating information of the current cardiopulmonary resuscitation. For example, the actual operating parameters may be the actual compression depth, the actual compression frequency, the actual compression duration, the actual ventilation frequency, the actual ventilation concentration, the actual ventilation duration, the actual defibrillation waveform, the actual defibrillation current, the actual defibrillation voltage, etc.

[0058] The above waveforms and parameters can be collected through corresponding data sensors. Specifically, various data sensors collect raw data in real time and send the above raw data to the monitoring module. The monitoring module can pre-process the above raw data, such as denoising and standardization, so as to collect the target perfusion waveform and actual operating parameters.

[0059] The patient status assessment module 202 includes:

[0060] The first data acquisition submodule 2021 is used to acquire the target perfusion waveform and actual operating parameters, and identify signal feature points of the target perfusion waveform.

[0061] 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 target perfusion waveform and actual operating parameters.

[0062] The above-mentioned signal characteristic points can be characteristic points such as peak values ​​and valley values ​​of the target perfusion waveform. The implementation method of identifying the signal characteristic points can be: the signal characteristic points to be identified can be pre-set, such as peak values ​​or valley values, and the signal characteristic points of the target perfusion waveform can be identified according to the characteristic information of the pre-set characteristic points.

[0063] The data identification submodule 2022 is used to identify the target circulation waveform representing the patient's cardiac active circulation information in the target perfusion waveform based on the signal feature points and the actual operating parameters.

[0064] The target circulation waveform represents the patient's active cardiac circulation information. Active cardiac circulation refers to the blood circulation promoted by the heart's own function after the patient's heart begins to recover. Since it is promoted by the heart's own function rather than directly caused by other auxiliary means, this state is called the active cardiac circulation state.

[0065] One implementation method of identifying the target circulation waveform is to input the target perfusion waveform, signal feature points, and actual operating parameters into a pre-trained waveform recognition model to obtain a waveform output by the waveform recognition model as the target circulation waveform. The above-mentioned waveform recognition model is a pre-trained circulation waveform used to identify the circulation waveform that represents the patient's cardiac active circulation information in the perfusion waveform.

[0066] Other implementations of identifying target cycle waveforms can be found in the following Figure 3a The corresponding embodiments are not described in detail here.

[0067] The state assessment submodule 2023 is used to assess the patient's cardiac recovery state based on the target cyclic waveform.

[0068] The cardiac recovery state represents the current cardiac recovery status of the patient. Since the target circulation waveform represents the patient's active cardiac circulation state, and the active cardiac circulation state reflects the blood circulation state promoted by the heart's own function, the patient's current cardiac recovery state can be accurately assessed based on the target circulation waveform.

[0069] The evaluation results obtained by evaluating the patient's cardiac recovery status can be displayed through the user interface coupled to the monitoring module for reference by medical staff; it can also serve as a basis for adaptive adjustment of control parameters for controlling cardiopulmonary resuscitation function components. For example, when the evaluation results show that the patient's cardiac recovery status is better, the cardiopulmonary resuscitation system can adjust the control parameters of the cardiopulmonary resuscitation function components in real time, or stop the operation of the cardiopulmonary resuscitation function components, so that the operation of the cardiopulmonary resuscitation system can adapt to the real-time status of the current patient.

[0070] The above evaluation results can be represented in the form of state levels, such as presetting the patient's cardiac recovery state into three state levels of high, medium and low, which represent the degree of the patient's cardiac recovery state from strong to weak from high to low. Based on this, one implementation method of evaluating the patient's cardiac recovery state is to extract waveform characteristic parameters of the target cycle waveform, determine the state level corresponding to the waveform characteristic parameters, and use them as the evaluation result of the patient's cardiac recovery state.

[0071] The above-mentioned waveform characteristic parameters can be the mean, change rate, peak value and other parameters of the target cyclic waveform, according to a preset correspondence, that is, the correspondence between the characteristic parameters and the state level, to determine the state level corresponding to the above-mentioned waveform characteristic parameters as an evaluation result of the patient's heart recovery status.

[0072] The above correspondence relationship includes various preset state levels and characteristic parameters corresponding to each preset state level. In this way, the current spontaneous circulation state of the patient can be determined according to the above correspondence relationship.

[0073] The cardiopulmonary resuscitation system provided in this embodiment is applied, and the cardiopulmonary resuscitation system includes a monitoring module, a patient status assessment 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 patient status assessment module assesses the patient's cardiac recovery status based on the data collected by the monitoring module, thereby realizing the integration and intelligence of cardiopulmonary resuscitation.

[0074] Moreover, in this embodiment, the signal characteristic points of the target perfusion waveform reflect the perfusion information of the patient's current heart, that is, the overall perfusion status of the patient's current heart; the actual operating parameters are the real-time operating parameters of cardiopulmonary resuscitation. Cardiopulmonary resuscitation, as an auxiliary means, directly affects the perfusion status of the patient's heart, so the actual operating parameters reflect the perfusion status of the patient's heart from the perspective of cardiopulmonary resuscitation. Under the conditions of cardiopulmonary resuscitation assistance, the overall perfusion status of the heart is affected by the heart's own function and the assistance of cardiopulmonary resuscitation. Therefore, based on the signal characteristic points of the target perfusion waveform and the actual operating parameters, the cardiac perfusion information caused by the patient's own heart function can be accurately determined, so that the identified target circulation waveform is close to the current real situation. The patient's heart recovery state is directly related to the heart's own function, so that the accuracy of the patient's heart recovery state evaluated is high, and high-precision and intelligent patient status evaluation is achieved.

[0075] The aforementioned data identification submodule 2022 may use the following methods in addition to the aforementioned embodiments to identify the target cycle waveform: Figure 3a In the corresponding embodiment, 3022 and 3023 are implemented. Based on this, see Figure 3a , Figure 3a A schematic diagram of the structure of a second intelligent cardiopulmonary resuscitation system provided in an embodiment of the present application.

[0076] The monitoring module 301 is used to collect the target perfusion waveform representing the current perfusion information of the patient's heart, and collect the actual operating parameters during the current cardiopulmonary resuscitation execution process.

[0077] The above 301 is the same as the above 201 and will not be repeated here.

[0078] The patient status assessment module 302 includes:

[0079] The first data acquisition submodule 3021 is used to acquire the target perfusion waveform and actual operating parameters, and identify signal feature points of the target perfusion waveform.

[0080] The above 3021 is the same as the aforementioned 2021 and will not be repeated here.

[0081] The candidate identification unit 3022 is used to determine, based on the signal feature points, a sub-waveform containing a signal peak in the target perfusion waveform as a candidate cycle waveform.

[0082] There may be multiple signal peaks in the target perfusion waveform, and each sub-waveform contains one signal peak.

[0083] The heart's blood circulation is in a fluctuating state, and the signal peak in the target perfusion waveform can be used to characterize the fluctuation information of the heart's blood circulation, and the sub-waveform containing the signal peak is used to accurately characterize the perfusion information of the heart's blood circulation.

[0084] One implementation method for determining an alternative cyclic waveform is to use signal feature points to determine the signal peak in the target perfusion waveform, take each signal peak as the center, determine the signal valley value closest to the signal peak on the left and right, and use the two signal valley values ​​as the starting point and end point to determine a sub-waveform containing the signal peak.

[0085] by Figure 3b For example, waveform S is the target perfusion waveform, the signal peaks are P1 and P2, and the determined candidate cycle waveforms are bs1 and bs2.

[0086] The data identification unit 3023 is used to determine the cyclic waveform that does not match the actual operating parameters among the candidate cyclic waveforms as the target cyclic waveform that represents the patient's cardiac active circulation information.

[0087] A circulatory waveform that does not match the actual operating parameters indicates that the current cardiac perfusion is not directly caused by cardiopulmonary resuscitation, that is, the waveform of the passive cardiac circulation information is excluded. Cardiac perfusion includes two situations, one is the active cardiac circulation information, and the other is the passive cardiac circulation information. Therefore, the circulatory waveform that does not match the actual operating parameters is more likely to represent the patient's active cardiac circulation information. Therefore, the accuracy of determining the above-mentioned mismatched circulatory waveform as the target circulatory waveform is higher.

[0088] One implementation method for determining the target cyclic waveform is as follows: for each alternative cyclic waveform, the resuscitation parameters corresponding to the alternative cyclic waveform are calculated according to a preset resuscitation parameter calculation strategy, and the alternative cyclic waveform corresponding to the resuscitation parameters whose error with the actual operating parameters exceeds a preset error threshold is determined as the target cyclic waveform.

[0089] Other implementations of determining the target cycle waveform can be found in the following Figure 4 The corresponding embodiments are not described in detail here.

[0090] The state assessment submodule 3023 is used to assess the patient's cardiac recovery state based on the target cycle waveform.

[0091] The above 3023 is the same as the above 2023 and will not be repeated here.

[0092] In the aforementioned Figure 3a In the corresponding embodiment, the data identification unit can be implemented in the above-mentioned manner and can also include the following 4023-4025. Figure 4 In the corresponding embodiment, the target perfusion waveform includes a pulse blood sample waveform and a chest impedance waveform, and correspondingly, the candidate waveforms include a first candidate cycle waveform of the pulse blood oxygen waveform and a second candidate cycle waveform of the chest impedance signal waveform. Based on this, see Figure 4 , Figure 4 A schematic diagram of the structure of a third intelligent cardiopulmonary resuscitation system provided in an embodiment of the present application.

[0093] The monitoring module 401 is used to collect the target perfusion waveform representing the current perfusion information of the patient's heart, and collect the actual operating parameters during the current cardiopulmonary resuscitation execution process.

[0094] The patient status assessment module 402 includes:

[0095] The first data acquisition submodule 4021 is used to acquire the target perfusion waveform and actual operating parameters, and identify signal feature points of the target perfusion waveform.

[0096] The candidate identification unit 4022 is used to determine, based on the signal feature points, a sub-waveform containing a signal peak in the target perfusion waveform as a candidate cycle waveform.

[0097] The first data identification subunit 4023 is used to determine a cyclic waveform that does not match the actual operating parameters in the first candidate cyclic waveform as the first cyclic waveform.

[0098] The implementation method for determining the first cyclic waveform is as follows: for each first alternative cyclic waveform, the resuscitation parameter corresponding to the first alternative cyclic waveform is calculated according to the first calculation strategy of the preset resuscitation parameter, and the first alternative cyclic waveform corresponding to the resuscitation parameter whose error with the actual operating parameter exceeds the preset error threshold is determined as the first cyclic waveform.

[0099] The second data identification subunit 4024 is used to determine a cyclic waveform that does not match the actual operating parameters in the second candidate cyclic waveform as the second cyclic waveform.

[0100] The implementation method for determining the second cyclic waveform is as follows: for each second alternative cyclic waveform, the resuscitation parameters corresponding to the second alternative cyclic waveform are calculated according to the second calculation strategy of the preset resuscitation parameters, and the second alternative cyclic waveform corresponding to the resuscitation parameters whose error with the actual operating parameters exceeds the preset error threshold is determined as the second cyclic waveform.

[0101] The third data identification subunit 4025 is used to determine a target cycle waveform based on the first cycle waveform and the second cycle waveform.

[0102] A first implementation method of determining the target cycle waveform is: determining an intersection waveform between the first cycle waveform and the second cycle waveform, and determining the intersection waveform as the target cycle waveform.

[0103] A second implementation method for determining a target cyclic waveform is as follows: extracting a first parameter value of a preset waveform parameter item in a first cyclic waveform, and extracting a second parameter value of a preset waveform parameter item in a second cyclic waveform; for each cyclic waveform, counting the number of parameter values ​​that satisfy a preset numerical range corresponding to the preset waveform parameter item, and determining the cyclic waveform corresponding to the highest number as the target cyclic waveform.

[0104] The above-mentioned preset waveform parameter items may include a waveform length item, a peak value item, a mean value item, and the like.

[0105] The preset numerical range corresponding to the preset waveform parameter item is obtained in advance based on the statistics of active circulation information of a large number of sample patients. When the parameter value meets the above preset numerical range, it means that the parameter value is credible, otherwise it is unreliable.

[0106] For example, when there are 4 preset waveform parameter items, among which, the number of parameter values ​​in the first cycle waveform that satisfy the preset numerical ranges corresponding to the above 4 items is 3, and the number of parameter values ​​in the second cycle waveform that satisfy the preset numerical ranges corresponding to the above 4 items is 2, then the cycle waveform corresponding to the highest number is the first cycle waveform, that is, the first cycle waveform is the target cycle waveform.

[0107] The state assessment submodule 4026 is used to assess the patient's cardiac recovery state based on the target cyclic waveform.

[0108] Corresponding to the aforementioned intelligent cardiopulmonary resuscitation system, the present application also provides a patient status assessment method, see Figure 5 , Figure 5 A schematic diagram of a patient status assessment method provided in an embodiment of the present application, the method comprising:

[0109] Step S501: collecting a target perfusion waveform representing the current perfusion information of the patient's heart, collecting actual operating parameters during the current cardiopulmonary resuscitation execution process, and identifying signal feature points of the target perfusion waveform;

[0110] Step S502: Based on the signal feature points and actual operating parameters, identifying a target circulation waveform representing the patient's cardiac active circulation information in the target perfusion waveform;

[0111] Step S503: Based on the target cyclic waveform, assess the patient's cardiac recovery state.

[0112] In one embodiment of the present application, the identifying, based on the signal feature points and the actual operating parameters, a target circulation waveform representing the patient's cardiac active circulation information in the target perfusion waveform includes:

[0113] Based on the signal feature points, determining a sub-waveform of the target perfusion waveform that contains a signal peak as a candidate cyclic waveform;

[0114] A cyclic waveform among the candidate cyclic waveforms that does not match the actual operating parameters is determined as a target cyclic waveform that represents the patient's cardiac active circulation information.

[0115] In one embodiment of the present application, the target perfusion waveform includes: a pulse oximetry waveform and / or a chest impedance signal waveform.

[0116] In one embodiment of the present application, the candidate cyclic waveforms include a first candidate cyclic waveform of a pulse oximetry waveform and a second candidate cyclic waveform of a chest impedance signal waveform;

[0117] The step of determining a cyclic waveform that does not match the actual operating parameters among the candidate cyclic waveforms as a target cyclic waveform that represents the patient's cardiac active circulation information includes:

[0118] Determine a cyclic waveform that does not match the actual operating parameters in the first candidate cyclic waveform as the first cyclic waveform;

[0119] Determine a cyclic waveform that does not match the actual operating parameters in the second candidate cyclic waveform as the second cyclic waveform;

[0120] A target cyclic waveform is determined based on the first cyclic waveform and the second cyclic waveform.

[0121] In one embodiment of the present application, the above-mentioned determining the target cycle waveform based on the first cycle waveform and the second cycle waveform includes:

[0122] Extracting a first parameter value of a preset waveform parameter item in the first cyclic waveform, and extracting a second parameter value of a preset waveform parameter item in the second cyclic waveform;

[0123] For each cyclic waveform, the number of parameter values ​​that meet the preset numerical range corresponding to the preset waveform parameter item is counted, and the cyclic waveform corresponding to the highest number is determined as the target cyclic waveform.

[0124] The cardiopulmonary resuscitation system provided in this embodiment is applied, and the cardiopulmonary resuscitation system includes a monitoring module, a patient status assessment 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 patient status assessment module assesses the patient's cardiac recovery status based on the data collected by the monitoring module, thereby realizing the integration and intelligence of cardiopulmonary resuscitation.

[0125] Moreover, in this embodiment, the signal characteristic points of the target perfusion waveform reflect the perfusion information of the patient's current heart, that is, the overall perfusion status of the patient's current heart; the actual operating parameters are the real-time operating parameters of cardiopulmonary resuscitation. Cardiopulmonary resuscitation, as an auxiliary means, directly affects the perfusion status of the patient's heart, so the actual operating parameters reflect the perfusion status of the patient's heart from the perspective of cardiopulmonary resuscitation. Under the conditions of cardiopulmonary resuscitation assistance, the overall perfusion status of the heart is affected by the heart's own function and the assistance of cardiopulmonary resuscitation. Therefore, based on the signal characteristic points of the target perfusion waveform and the actual operating parameters, the cardiac perfusion information caused by the patient's own heart function can be accurately determined, so that the identified target circulation waveform is close to the current real situation. The patient's heart recovery state is directly related to the heart's own function, so that the accuracy of the patient's heart recovery state evaluated is high, and high-precision and intelligent patient status evaluation is achieved.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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. An intelligent cardiopulmonary resuscitation system, characterized in that: The system comprises a monitoring module, a patient status assessment module and a cardiopulmonary resuscitation function component, wherein the cardiopulmonary resuscitation function component comprises a compression function component, a ventilation function component and a defibrillation function component, wherein: The monitoring module is used to collect a target perfusion waveform representing the current perfusion information of the patient's heart, and to collect actual operating parameters during the current cardiopulmonary resuscitation execution process, wherein the target perfusion waveform reflects the overall perfusion information of the patient's heart, and the target perfusion waveform includes: a pulse oximetry waveform and / or a chest impedance signal waveform; and the actual operating parameters reflect the perfusion information of the patient's heart from the perspective of cardiopulmonary resuscitation; The patient status assessment module comprises: A first data acquisition submodule, used to acquire the target perfusion waveform and actual operating parameters, and identify signal feature points of the target perfusion waveform; A data identification submodule, for identifying a target circulation waveform representing the patient's cardiac active circulation information in the target perfusion waveform based on the signal characteristic points and the actual operating parameters, wherein the target circulation waveform reflects the cardiac perfusion information caused by the patient's heart function itself; a state assessment submodule, for assessing the cardiac recovery state of the patient based on the target cyclic waveform; The data identification submodule includes: an alternative identification unit, configured to determine, based on the signal feature points, a sub-waveform of the target perfusion waveform that contains a signal peak value as an alternative cycle waveform; A data identification unit, used to determine a cyclic waveform that does not match the actual operating parameters among the candidate cyclic waveforms as a target cyclic waveform that represents the patient's cardiac active circulation information; The candidate cyclic waveforms include a first candidate cyclic waveform of a pulse oximetry waveform and a second candidate cyclic waveform of a chest impedance signal waveform. The data identification unit includes: A first data identification subunit is used to determine a cyclic waveform that does not match the actual operating parameters in the first candidate cyclic waveform as the first cyclic waveform; A second data identification subunit is used to determine a cyclic waveform that does not match the actual operating parameters in the second candidate cyclic waveform as the second cyclic waveform; A third data identification subunit, configured to determine a target cyclic waveform based on the first cyclic waveform and the second cyclic waveform; The third data identification subunit is specifically used to extract the first parameter value of the preset waveform parameter item in the first cycle waveform, and extract the second parameter value of the preset waveform parameter item in the second cycle waveform. For each cycle waveform, the number of parameter values ​​that meet the preset numerical range corresponding to the preset waveform parameter item is counted, and the cycle waveform corresponding to the highest number is determined as the target cycle waveform.

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