Monitoring and guiding method and system for cardio-pulmonary resuscitation

Abstract

The invention provides a cardiopulmonary resuscitation monitoring guidance method and system, and the method comprises the steps: obtaining the current detection information, body data, current cardiopulmonary resuscitation modes and current cardiopulmonary resuscitation monitoring information of each detection type of a patient, and recognizing an applicable cardiopulmonary resuscitation strategy of the patient; identifying the cardiopulmonary resuscitation degree and the current cardiopulmonary resuscitation effect Based on the suitable cardiopulmonary resuscitation strategy and the current cardiopulmonary resuscitation effect of the patient, current cardiopulmonary resuscitation mode guiding information of the patient is obtained through adjustment, and based on the cardiopulmonary resuscitation degree of the patient and the current cardiopulmonary resuscitation mode guiding information, the current target cardiopulmonary resuscitation guiding process of the patient is recognized; the current target cardio-pulmonary resuscitation guiding process is used for guiding cardio-pulmonary resuscitation to a worker through a guiding transmission unit of cardio-pulmonary resuscitation equipment, and the steps are iterated until the cardio-pulmonary resuscitation task of the patient is completed. By adopting the scheme, the effect recognition accuracy of the cardio-pulmonary resuscitation effect can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cardiopulmonary resuscitation, and in particular to a monitoring and guiding method and system for cardiopulmonary resuscitation. Background Art

[0002] As a key technology in emergency medical treatment, cardiopulmonary resuscitation can often effectively help patients restore spontaneous circulation, breathing, consciousness, prevent cerebral edema, and avoid death. It is one of the most effective and easy-to-use medical technologies under current general, special, and medical environments. Therefore, improving the accuracy of identifying the effect of cardiopulmonary resuscitation is the current research focus.

[0003] The traditional method of accurately identifying the effect of cardiopulmonary resuscitation is to manually determine the effect of cardiopulmonary resuscitation through direct observation, pulse examination, and empirical judgment by medical personnel. However, this method is affected by human experience and human observation, resulting in low accuracy in identifying the effect of cardiopulmonary resuscitation. Summary of the invention

[0004] The main purpose of the present invention is to provide a monitoring and guiding method and system for cardiopulmonary resuscitation, aiming to solve the problem that the prior art is affected by human experience and human observation, resulting in low accuracy in identifying the effect of cardiopulmonary resuscitation.

[0005] To achieve the above object, the present invention provides a monitoring and guiding method for cardiopulmonary resuscitation, the method comprising:

[0006] Acquire the current detection information of each detection type of the patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information, and identify the applicable cardiopulmonary resuscitation strategy for the patient based on the patient's physical data;

[0007] Based on the current cardiopulmonary resuscitation monitoring information, identifying the cardiopulmonary resuscitation degree of the patient, and based on the current detection information of each detection type, identifying the current cardiopulmonary resuscitation effect of the patient;

[0008] Based on the applicable cardiopulmonary resuscitation strategy of the patient and the current cardiopulmonary resuscitation effect of the patient, the current cardiopulmonary resuscitation method of the patient is adjusted to obtain the current cardiopulmonary resuscitation method guidance information of the patient, and based on the cardiopulmonary resuscitation degree of the patient and the current cardiopulmonary resuscitation method guidance information, the current target cardiopulmonary resuscitation guidance process of the patient is identified;

[0009] The current target cardiopulmonary resuscitation guidance process is used to provide cardiopulmonary resuscitation guidance to the staff through the guidance transmission unit of the cardiopulmonary resuscitation equipment, and returns to execute the steps of obtaining the current test information of each test type of the patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information until the patient's cardiopulmonary resuscitation task is completed.

[0010] Optionally, the identifying an applicable cardiopulmonary resuscitation strategy for the patient based on the patient's physical data includes:

[0011] Splitting the patient's body data into body shape data and physiological data, and identifying the body shape range and the physiological range of the patient in a patient cardiopulmonary resuscitation database based on the body shape data and the physiological data;

[0012] In the patient cardiopulmonary resuscitation database, a first cardiopulmonary resuscitation strategy corresponding to the body size range and a second cardiopulmonary resuscitation strategy corresponding to the physiological range are identified, and based on the first cardiopulmonary resuscitation strategy and the second cardiopulmonary resuscitation strategy, an applicable cardiopulmonary resuscitation strategy for the patient is identified.

[0013] Optionally, the identifying the patient's cardiopulmonary resuscitation level based on the current cardiopulmonary resuscitation monitoring information includes:

[0014] Splitting the current cardiopulmonary resuscitation monitoring information into sub-monitoring data of each resuscitation monitoring type, and obtaining a cardiopulmonary resuscitation evaluation strategy;

[0015] The cardiopulmonary resuscitation evaluation strategy is split into sub-evaluation strategies for each resuscitation monitoring type, and based on the sub-monitoring data of each resuscitation monitoring type, the sub-evaluation strategy for each resuscitation monitoring type and the resuscitation evaluation network are used to identify the sub-cardiopulmonary resuscitation level corresponding to each resuscitation monitoring type;

[0016] The resuscitation weight value of each resuscitation monitoring type is obtained, and based on the resuscitation weight value of each resuscitation monitoring type, the sub-cardiopulmonary resuscitation degree corresponding to each resuscitation monitoring type is weighted and summed to obtain the cardiopulmonary resuscitation degree of the patient.

[0017] Optionally, the identifying the current cardiopulmonary resuscitation effect of the patient based on the current detection information of each detection type includes:

[0018] Obtaining each historical detection information of each detection type and the current cardiopulmonary resuscitation duration of the patient, and performing distribution sorting processing on each historical detection information of each detection type and the current detection information of each detection type according to the cardiopulmonary resuscitation time point corresponding to each historical detection information, to obtain detection distribution information of each detection type;

[0019] Based on the detection distribution information of each detection type, identifying the detection trend information of each detection type and the change trend information of each detection type, and based on the detection trend information of each detection type and the change trend information of each detection type, identifying the change degree trend of cardiopulmonary resuscitation of each detection type;

[0020] The trend of the change degree of cardiopulmonary resuscitation of all detected types is taken as the current cardiopulmonary resuscitation effect of the patient.

[0021] Optionally, adjusting the patient's current cardiopulmonary resuscitation method based on the patient's applicable cardiopulmonary resuscitation strategy and the patient's current cardiopulmonary resuscitation effect to obtain the patient's current cardiopulmonary resuscitation method guidance information includes:

[0022] Based on the trend of the degree of change of cardiopulmonary resuscitation of each of the detection types, the resuscitation effect evaluation value of the cardiopulmonary resuscitation method is evaluated through a resuscitation method evaluation network, and the applicable cardiopulmonary resuscitation strategy is divided into the resuscitation condition range of each cardiopulmonary resuscitation type;

[0023] Based on the current resuscitation condition data of each cardiopulmonary resuscitation type of the current cardiopulmonary resuscitation method and the resuscitation effect evaluation value, within the resuscitation condition range of each cardiopulmonary resuscitation type, selecting target resuscitation condition data of each cardiopulmonary resuscitation type;

[0024] The target resuscitation condition data of all cardiopulmonary resuscitation types are used as the current cardiopulmonary resuscitation method guidance information for the patient.

[0025] Optionally, the identifying the current target cardiopulmonary resuscitation guidance process of the patient based on the cardiopulmonary resuscitation level of the patient and the current cardiopulmonary resuscitation method guidance information includes:

[0026] Based on the patient's cardiopulmonary resuscitation level, identifying the patient's initial cardiopulmonary resuscitation process, and dividing the initial cardiopulmonary resuscitation process into sub-initial processes of each process stage;

[0027] Identify each cardiopulmonary resuscitation type corresponding to each sub-initial process, and identify sub-process guidance information of each sub-initial process based on target resuscitation condition data of each cardiopulmonary resuscitation type and each cardiopulmonary resuscitation type corresponding to each sub-initial process;

[0028] Sorting the sub-process guidance information of all sub-initial processes according to the position information of the process nodes to which each sub-initial process belongs in the initial cardiopulmonary resuscitation process, to obtain the target process guidance information of the initial cardiopulmonary resuscitation process;

[0029] The initial cardiopulmonary resuscitation process and the target process guidance information of the initial cardiopulmonary resuscitation process are used as the current target cardiopulmonary resuscitation guidance process of the patient.

[0030] In addition, to achieve the above-mentioned purpose, the present invention also provides a cardiopulmonary resuscitation monitoring and guidance system, the cardiopulmonary resuscitation monitoring and guidance system comprising:

[0031] an acquisition module, used to acquire current detection information of each detection type of the patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information, and identify an applicable cardiopulmonary resuscitation strategy for the patient based on the patient's physical data;

[0032] an identification module, configured to identify the patient's cardiopulmonary resuscitation degree based on the current cardiopulmonary resuscitation monitoring information, and to identify the patient's current cardiopulmonary resuscitation effect based on the current detection information of each detection type;

[0033] an adjustment module, configured to adjust the current cardiopulmonary resuscitation method of the patient based on the applicable cardiopulmonary resuscitation strategy of the patient and the current cardiopulmonary resuscitation effect of the patient, obtain the current cardiopulmonary resuscitation method guidance information of the patient, and identify the current target cardiopulmonary resuscitation guidance process of the patient based on the cardiopulmonary resuscitation degree of the patient and the current cardiopulmonary resuscitation method guidance information;

[0034] The iteration module is used to provide cardiopulmonary resuscitation guidance to the staff through the guidance transmission unit of the cardiopulmonary resuscitation equipment via the current target cardiopulmonary resuscitation guidance process, and return to execute the steps of obtaining the current detection information of each detection type of the patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information until the cardiopulmonary resuscitation task for the patient is completed.

[0035] Optionally, the acquisition module is specifically used to:

[0036] Splitting the patient's body data into body shape data and physiological data, and identifying the body shape range and the physiological range of the patient in a patient cardiopulmonary resuscitation database based on the body shape data and the physiological data;

[0037] In the patient cardiopulmonary resuscitation database, a first cardiopulmonary resuscitation strategy corresponding to the body size range and a second cardiopulmonary resuscitation strategy corresponding to the physiological range are identified, and based on the first cardiopulmonary resuscitation strategy and the second cardiopulmonary resuscitation strategy, an applicable cardiopulmonary resuscitation strategy for the patient is identified.

[0038] Optionally, the identification module is specifically used to:

[0039] Splitting the current cardiopulmonary resuscitation monitoring information into sub-monitoring data of each resuscitation monitoring type, and obtaining a cardiopulmonary resuscitation evaluation strategy;

[0040] The cardiopulmonary resuscitation evaluation strategy is split into sub-evaluation strategies for each resuscitation monitoring type, and based on the sub-monitoring data of each resuscitation monitoring type, the sub-evaluation strategy for each resuscitation monitoring type and the resuscitation evaluation network are used to identify the sub-cardiopulmonary resuscitation level corresponding to each resuscitation monitoring type;

[0041] The resuscitation weight value of each resuscitation monitoring type is obtained, and based on the resuscitation weight value of each resuscitation monitoring type, the sub-cardiopulmonary resuscitation degree corresponding to each resuscitation monitoring type is weighted and summed to obtain the cardiopulmonary resuscitation degree of the patient.

[0042] Optionally, the identification module is specifically used to:

[0043] Obtaining each historical detection information of each detection type and the current cardiopulmonary resuscitation duration of the patient, and performing distribution sorting processing on each historical detection information of each detection type and the current detection information of each detection type according to the cardiopulmonary resuscitation time point corresponding to each historical detection information, to obtain detection distribution information of each detection type;

[0044] Based on the detection distribution information of each detection type, identifying the detection trend information of each detection type and the change trend information of each detection type, and based on the detection trend information of each detection type and the change trend information of each detection type, identifying the change degree trend of cardiopulmonary resuscitation of each detection type;

[0045] The trend of the change degree of cardiopulmonary resuscitation of all detected types is taken as the current cardiopulmonary resuscitation effect of the patient.

[0046] Optionally, the iteration module is specifically used for:

[0047] Based on the trend of the degree of change of cardiopulmonary resuscitation of each of the detection types, the resuscitation effect evaluation value of the cardiopulmonary resuscitation method is evaluated through a resuscitation method evaluation network, and the applicable cardiopulmonary resuscitation strategy is divided into the resuscitation condition range of each cardiopulmonary resuscitation type;

[0048] Based on the current resuscitation condition data of each cardiopulmonary resuscitation type of the current cardiopulmonary resuscitation method and the resuscitation effect evaluation value, within the resuscitation condition range of each cardiopulmonary resuscitation type, selecting target resuscitation condition data of each cardiopulmonary resuscitation type;

[0049] The target resuscitation condition data of all cardiopulmonary resuscitation types are used as the current cardiopulmonary resuscitation method guidance information for the patient.

[0050] Optionally, the iteration module is specifically used for:

[0051] Based on the patient's cardiopulmonary resuscitation level, identifying the patient's initial cardiopulmonary resuscitation process, and dividing the initial cardiopulmonary resuscitation process into sub-initial processes of each process stage;

[0052] Identify each cardiopulmonary resuscitation type corresponding to each sub-initial process, and identify sub-process guidance information of each sub-initial process based on target resuscitation condition data of each cardiopulmonary resuscitation type and each cardiopulmonary resuscitation type corresponding to each sub-initial process;

[0053] Sorting the sub-process guidance information of all sub-initial processes according to the position information of the process nodes to which each sub-initial process belongs in the initial cardiopulmonary resuscitation process, to obtain the target process guidance information of the initial cardiopulmonary resuscitation process;

[0054] The initial cardiopulmonary resuscitation process and the target process guidance information of the initial cardiopulmonary resuscitation process are used as the current target cardiopulmonary resuscitation guidance process of the patient.

[0055] In a third aspect, the present application provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0056] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0057] In a fifth aspect, the present application provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0058] The present invention provides a monitoring and guiding method and system for cardiopulmonary resuscitation, the method comprising: obtaining current detection information of each detection type of a patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information, and identifying the patient's applicable cardiopulmonary resuscitation strategy based on the patient's physical data; identifying the patient's cardiopulmonary resuscitation degree based on the current cardiopulmonary resuscitation monitoring information, and identifying the patient's current cardiopulmonary resuscitation effect based on the current detection information of each detection type; adjusting the patient's current cardiopulmonary resuscitation method based on the patient's applicable cardiopulmonary resuscitation strategy and the patient's current cardiopulmonary resuscitation effect to obtain the patient's current cardiopulmonary resuscitation method guidance information, and identifying the patient's current target cardiopulmonary resuscitation guidance process based on the patient's cardiopulmonary resuscitation degree and the current cardiopulmonary resuscitation method guidance information; providing cardiopulmonary resuscitation guidance to the staff through the guidance transmission unit of the cardiopulmonary resuscitation device with the current target cardiopulmonary resuscitation guidance process, and returning to execute the steps of obtaining the patient's current detection information of each detection type, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information until the patient's cardiopulmonary resuscitation task is completed. This solution, by acquiring the patient's cardiopulmonary resuscitation monitoring information and the current detection information of each detection type, identifies the patient's cardiopulmonary resuscitation degree and cardiopulmonary resuscitation effect, avoiding the error and low applicability of artificial experience identification or human observation judgment, thereby improving the accuracy of the analysis of the patient's recovery status and degree of recovery during the cardiopulmonary resuscitation process. Then, this solution generates an applicable cardiopulmonary resuscitation strategy for the patient through the patient's physical data, so as to effectively guide the staff to perform cardiopulmonary resuscitation on the patient through a cardiopulmonary resuscitation method that is more suitable for the patient, so as to improve the cardiopulmonary resuscitation effect and speed up the cardiopulmonary resuscitation process. After that, this solution generates the patient's current target cardiopulmonary resuscitation guidance process by detecting and identifying the cardiopulmonary resuscitation effect and cardiopulmonary resuscitation degree, and analyzing the applicable cardiopulmonary resuscitation strategy, thereby guiding the staff to perform the cardiopulmonary resuscitation process, improving the degree of improvement of the patient's cardiopulmonary resuscitation effect, and speeding up the patient's cardiopulmonary resuscitation degree. Finally, by iterating the overall process of this solution, we ensure that under emergency conditions, the cardiopulmonary guidance process can be detected, analyzed, and optimized in real time, ensuring that staff can be effectively guided to conduct real-time monitoring and guidance of patients at different stages of cardiopulmonary resuscitation, thereby comprehensively improving the effectiveness of cardiopulmonary resuscitation and the accuracy of identifying the effectiveness of cardiopulmonary resuscitation. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0060] Figure 1 is a flow chart of a monitoring and guiding method for cardiopulmonary resuscitation provided by an embodiment of the present invention;

[0061] Figure 2 is a structural schematic diagram of a cardiopulmonary resuscitation monitoring and guidance system provided by an embodiment of the present invention;

[0062] Figure 3 An internal structure diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The monitoring and guiding method for cardiopulmonary resuscitation provided by the embodiment of the present invention is applied to the monitoring and guiding system for cardiopulmonary resuscitation. Unless otherwise defined, all technical and scientific terms used in this document have the same meaning as those generally understood by technicians in the technical field of this application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned drawings and any variations thereof are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0064] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0065] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0066] The monitoring and guiding method for cardiopulmonary resuscitation provided in the embodiment of the present application can be applied to the application environment of monitoring and guiding for cardiopulmonary resuscitation. The method can be applied to a terminal, a server, or a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. Among them, the terminal can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, etc. Among them, the terminal obtains the cardiopulmonary resuscitation monitoring information of the patient and the current detection information of each detection type, and respectively identifies the cardiopulmonary resuscitation degree and cardiopulmonary resuscitation effect of the patient, thereby avoiding the error and low applicability of artificial experience recognition or human observation judgment, thereby improving the analysis accuracy of the patient's recovery status and recovery degree during the cardiopulmonary resuscitation process. Then, this solution generates an applicable cardiopulmonary resuscitation strategy for the patient through the patient's physical data, so as to effectively guide the staff to perform cardiopulmonary resuscitation on the patient through a cardiopulmonary resuscitation method that is more suitable for the patient, so as to improve the cardiopulmonary resuscitation effect and speed up the cardiopulmonary resuscitation process. Then, this solution generates the current target cardiopulmonary resuscitation guidance process for the patient by detecting and identifying the cardiopulmonary resuscitation effect and degree, and analyzing the applicable cardiopulmonary resuscitation strategy, thereby guiding the staff to perform the cardiopulmonary resuscitation process, improving the degree of cardiopulmonary resuscitation effect on the patient, and accelerating the effect of cardiopulmonary resuscitation on the patient. Finally, by iterating the overall process of this solution, it is ensured that the cardiopulmonary guidance process can be detected, analyzed, and optimized in real time under emergency conditions, ensuring that the staff can be effectively guided to monitor and guide the patient in real time at different stages of cardiopulmonary resuscitation, thereby comprehensively improving the degree of cardiopulmonary resuscitation effect and the accuracy of identifying the effect of cardiopulmonary resuscitation.

[0067] In one embodiment, Figure 1 As shown, a cardiopulmonary resuscitation monitoring and guidance method is provided, which is described by taking the application of the method to a terminal as an example, and includes the following steps:

[0068] Step S101, obtaining the patient's current test information of each test type, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information, and identifying the patient's applicable cardiopulmonary resuscitation strategy based on the patient's physical data.

[0069] In this embodiment, the terminal obtains the current detection information of each detection type of the patient by receiving the data transmitted by each detection instrument set on the patient's body surface, wherein each detection instrument corresponds to a detection type, and the detection includes but is not limited to a muscle hardness detection instrument, a facial recognition instrument, and a pupil detection instrument, wherein the pulse detection instrument is used for the muscle hardness detection instrument to detect the muscle hardness of the user, the facial recognition instrument is used to detect the facial blood color state / expression change state of the user, and the pupil detection instrument is used to detect the pupil diameter size of the user. Then, the terminal responds to the patient's body shape information input by the staff to obtain the patient's body data and the cardiopulmonary resuscitation method when the staff currently performs cardiopulmonary resuscitation on the patient. Among them, the patient's body data includes but is not limited to the patient's height, gender, skeleton size / dimensions, and age value (estimated), etc. Among them, the cardiopulmonary resuscitation method includes the resuscitation condition data of each cardiopulmonary resuscitation type, and the cardiopulmonary resuscitation type is but is not limited to the compression resuscitation cycle type, the breathing resuscitation frequency type, the compression resuscitation frequency type, and the compression resuscitation depth type. Then, the terminal collects real-time monitoring data of the patient through each monitoring instrument to obtain the patient's current cardiopulmonary resuscitation monitoring information. Each monitoring instrument corresponds to a resuscitation monitoring type, including an electrocardiogram monitoring instrument, an end-tidal carbon dioxide monitoring instrument, an invasive arterial blood pressure detection instrument, and an instilled arterial perfusion pressure detection instrument. Finally, the terminal identifies the patient's applicable cardiopulmonary resuscitation strategy based on the patient's physical data. The applicable cardiopulmonary resuscitation strategy includes the scope of application of the cardiopulmonary resuscitation method. The specific identification process will be described in detail later.

[0070] Step S102, based on the current cardiopulmonary resuscitation monitoring information, the patient's cardiopulmonary resuscitation degree is identified, and based on the current detection information of each detection type, the patient's current cardiopulmonary resuscitation effect is identified.

[0071] In this embodiment, the terminal identifies the patient's cardiopulmonary resuscitation degree based on the current cardiopulmonary resuscitation monitoring information, and identifies the patient's current cardiopulmonary resuscitation effect based on the current detection information of each detection type. The cardiopulmonary resuscitation degree is used to characterize the cardiopulmonary resuscitation progress of the current user, and the numerical value of the cardiopulmonary resuscitation degree is represented by a percentage value. When the cardiopulmonary resuscitation degree is 100%, it indicates that the patient has successfully undergone cardiopulmonary resuscitation and recovered vital signs. The patient's cardiopulmonary resuscitation effect represents the resuscitation effect of the current cardiopulmonary resuscitation method on the patient's cardiopulmonary resuscitation. The better the cardiopulmonary resuscitation effect, the more suitable the current cardiopulmonary resuscitation method is for the patient, and the worse the cardiopulmonary resuscitation effect, the less suitable the current cardiopulmonary resuscitation method is for the patient. The specific identification process will be described in detail later.

[0072] Step S103, based on the patient's applicable cardiopulmonary resuscitation strategy and the patient's current cardiopulmonary resuscitation effect, adjust the patient's current cardiopulmonary resuscitation method, obtain the patient's current cardiopulmonary resuscitation method guidance information, and identify the patient's current target cardiopulmonary resuscitation guidance process based on the patient's cardiopulmonary resuscitation level and the current cardiopulmonary resuscitation method guidance information.

[0073] In this embodiment, the terminal adjusts the patient's current cardiopulmonary resuscitation method based on the patient's applicable cardiopulmonary resuscitation strategy and the patient's current cardiopulmonary resuscitation effect, obtains the patient's current cardiopulmonary resuscitation method guidance information, and identifies the patient's current target cardiopulmonary resuscitation guidance process based on the patient's cardiopulmonary resuscitation level and the current cardiopulmonary resuscitation method guidance information. Among them, the cardiopulmonary resuscitation method guidance information is the adjustment guidance information for the resuscitation condition data of each cardiopulmonary resuscitation type of the patient. The current target cardiopulmonary resuscitation guidance process is the target guidance information for the resuscitation condition data of each cardiopulmonary resuscitation type at each cardiopulmonary resuscitation stage. The specific identification process will be described in detail later.

[0074] Step S104, the current target cardiopulmonary resuscitation guidance process is used to provide cardiopulmonary resuscitation guidance to the staff through the guidance transmission unit of the cardiopulmonary resuscitation equipment, and returns to execute the step of obtaining the patient's current test information of each test type, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information until the patient's cardiopulmonary resuscitation task is completed.

[0075] In this embodiment, the terminal provides cardiopulmonary resuscitation guidance to the staff through the guidance transmission unit of the cardiopulmonary resuscitation equipment according to the current target cardiopulmonary resuscitation guidance process, and returns to execute the steps of obtaining the patient's current test information of each test type, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information until the patient's cardiopulmonary resuscitation task is completed. Among them, the guidance transmission unit of the cardiopulmonary resuscitation equipment can be a transmission unit composed of one or more guidance transmission modules, and the guidance transmission module includes but is not limited to a broadcast transmission module, a display transmission module, an image transmission module, and an infrared guidance transmission module. The broadcast transmission module is applicable to broadcast equipment, the display transmission module is applicable to LRD display screens, the image transmission module is applicable to LCD display screens, and the infrared guidance transmission module is applicable to infrared displays.

[0076] Based on the above scheme, by obtaining the patient's cardiopulmonary resuscitation monitoring information and the current detection information of each detection type, the patient's cardiopulmonary resuscitation degree and cardiopulmonary resuscitation effect are identified respectively, avoiding the error and low applicability of artificial experience identification or human observation judgment, thereby improving the analysis accuracy of the patient's recovery status and recovery degree during the cardiopulmonary resuscitation process. Then, this scheme generates an applicable cardiopulmonary resuscitation strategy for the patient through the patient's physical data, so as to effectively guide the staff to perform cardiopulmonary resuscitation on the patient through a cardiopulmonary resuscitation method that is more suitable for the patient, so as to improve the cardiopulmonary resuscitation effect and speed up the cardiopulmonary resuscitation process. After that, this scheme generates the patient's current target cardiopulmonary resuscitation guidance process by detecting and identifying the cardiopulmonary resuscitation effect and cardiopulmonary resuscitation degree, and analyzing the applicable cardiopulmonary resuscitation strategy, so as to guide the staff to perform the cardiopulmonary resuscitation process, thereby improving the degree of improvement of the patient's cardiopulmonary resuscitation effect and the effect of accelerating the patient's cardiopulmonary resuscitation degree. Finally, by iterating the overall process of this solution, we ensure that under emergency conditions, the cardiopulmonary guidance process can be detected, analyzed, and optimized in real time, ensuring that staff can be effectively guided to conduct real-time monitoring and guidance of patients at different stages of cardiopulmonary resuscitation, thereby comprehensively improving the effectiveness of cardiopulmonary resuscitation and the accuracy of identifying the effectiveness of cardiopulmonary resuscitation.

[0077] Optionally, based on the patient's physical data, an applicable cardiopulmonary resuscitation strategy for the patient is identified, including: splitting the patient's physical data into body shape data and physiological data, and identifying, in a patient cardiopulmonary resuscitation database, the body shape range to which the patient belongs, and the physiological range to which the patient belongs, based on the body shape data and the physiological data; identifying in the patient cardiopulmonary resuscitation database a first cardiopulmonary resuscitation strategy corresponding to the body shape range, and a second cardiopulmonary resuscitation strategy corresponding to the physiological range, and identifying, based on the first cardiopulmonary resuscitation strategy and the second cardiopulmonary resuscitation strategy, an applicable cardiopulmonary resuscitation strategy for the patient.

[0078] In this embodiment, the terminal splits the patient's physical data into body shape data and physiological data, and based on the body shape data and physiological data, identifies the body shape range and physiological range of the patient in the patient's cardiopulmonary resuscitation database. The body shape data includes but is not limited to height data and skeleton size data, and the physiological data includes but is not limited to gender data, age value data, etc. The patient's cardiopulmonary resuscitation database includes multiple body shape data ranges and physiological data ranges. Each body shape data range corresponds to a cardiopulmonary resuscitation strategy, and each physiological data range corresponds to a cardiopulmonary resuscitation strategy. The cardiopulmonary resuscitation strategy includes the applicable scope of the cardiopulmonary resuscitation method, that is, the resuscitation condition data range of each cardiopulmonary resuscitation type.

[0079] In the patient cardiopulmonary resuscitation database, the terminal identifies the first cardiopulmonary resuscitation strategy corresponding to the body size range and the second cardiopulmonary resuscitation strategy corresponding to the physiological range, and identifies the patient's applicable cardiopulmonary resuscitation strategy based on the first cardiopulmonary resuscitation strategy and the second cardiopulmonary resuscitation strategy. The first cardiopulmonary resuscitation strategy includes the first range of each cardiopulmonary resuscitation type, and the second cardiopulmonary resuscitation strategy includes the second range of each cardiopulmonary resuscitation type. The terminal obtains the target range of each cardiopulmonary resuscitation type based on the first range of each cardiopulmonary resuscitation type and the overlapping range of the second range of each cardiopulmonary resuscitation type, and uses the target range of all cardiopulmonary resuscitation types as the applicable cardiopulmonary resuscitation strategy for the patient.

[0080] Based on the above scheme, by splitting the body data, the first cardiopulmonary resuscitation strategy for the body size range corresponding to the body size data and the second cardiopulmonary resuscitation strategy for the physiological range corresponding to the physiological data are identified respectively, so as to analyze the applicable cardiopulmonary resuscitation strategy for the patient, thereby improving the comprehensiveness and accuracy of the analysis.

[0081] Optionally, based on the current cardiopulmonary resuscitation monitoring information, the patient's cardiopulmonary resuscitation level is identified, including: splitting the current cardiopulmonary resuscitation monitoring information into sub-monitoring data for each resuscitation monitoring type, and obtaining a cardiopulmonary resuscitation evaluation strategy; splitting the cardiopulmonary resuscitation evaluation strategy into sub-evaluation strategies for each resuscitation monitoring type, and based on the sub-monitoring data for each resuscitation monitoring type, identifying the sub-cardiopulmonary resuscitation level corresponding to each resuscitation monitoring type through the sub-evaluation strategies of each resuscitation monitoring type and a resuscitation evaluation network; obtaining a resuscitation weight value for each resuscitation monitoring type, and based on the resuscitation weight value for each resuscitation monitoring type, performing weighted summation processing on the sub-cardiopulmonary resuscitation levels corresponding to each resuscitation monitoring type to obtain the patient's cardiopulmonary resuscitation level.

[0082] In this embodiment, the terminal splits the current cardiopulmonary resuscitation monitoring information into sub-monitoring data of each resuscitation monitoring type, and obtains a cardiopulmonary resuscitation evaluation strategy. Then, the terminal splits the cardiopulmonary resuscitation evaluation strategy into sub-evaluation strategies of each resuscitation monitoring type. Each sub-evaluation strategy includes an evaluation value corresponding to each detection data range.

[0083] Then, the terminal identifies the sub-cardiopulmonary resuscitation degree corresponding to each resuscitation monitoring type based on the sub-monitoring data of each resuscitation monitoring type, through the sub-evaluation strategy of each resuscitation monitoring type, and the resuscitation evaluation network. Wherein, the resuscitation evaluation network is a classifier based on a reinforcement learning neural network, which is obtained after training through the sample detection data of each resuscitation monitoring type and the sub-evaluation strategy of each resuscitation detection type, and is used to simultaneously identify the evaluation value corresponding to each resuscitation monitoring type according to the sub-monitoring data of each resuscitation monitoring type. Wherein, the evaluation value is used to characterize the resuscitation degree value corresponding to the sub-monitoring data. Then, the terminal obtains the resuscitation weight value of each resuscitation monitoring type, and the resuscitation weight value is the weight value preset in the database by the staff, wherein the more accurate the evaluation of the resuscitation effect, the higher the weight value, for example, the resuscitation weight value of the resuscitation monitoring type corresponding to the end-tidal carbon dioxide is high, or the resuscitation weight value of the resuscitation detection type corresponding to the electrocardiogram is high. Then, based on the resuscitation weight value of each resuscitation monitoring type, the terminal performs weighted summation processing on the sub-cardiopulmonary resuscitation degree corresponding to each resuscitation monitoring type to obtain the patient's cardiopulmonary resuscitation degree.

[0084] Based on the above scheme, the degree of cardiopulmonary resuscitation is identified by splitting each resuscitation monitoring type, and then the patient's cardiopulmonary resuscitation degree is calculated by weighted summation, which improves the accuracy of identifying the patient's cardiopulmonary resuscitation degree.

[0085] Optionally, based on the current detection information of each detection type, the current cardiopulmonary resuscitation effect of the patient is identified, including: obtaining historical detection information of each detection type and the current cardiopulmonary resuscitation duration of the patient, and distributing and sorting the historical detection information of each detection type and the current detection information of each detection type according to the cardiopulmonary resuscitation time point corresponding to each historical detection information to obtain the detection distribution information of each detection type; based on the detection distribution information of each detection type, identifying the detection trend information of each detection type and the change trend information of each detection type, and based on the detection trend information of each detection type and the change trend information of each detection type, identifying the trend of the degree of change of cardiopulmonary resuscitation of each detection type; taking the trend of the degree of change of cardiopulmonary resuscitation of all detection types as the current cardiopulmonary resuscitation effect of the patient.

[0086] In this embodiment, the terminal obtains each historical detection information of each detection type and the current cardiopulmonary resuscitation duration of the patient, and distributes and sorts each historical detection information of each detection type and the current detection information of each detection type according to the cardiopulmonary resuscitation time point corresponding to each historical detection information, to obtain the detection distribution information of each detection type. The cardiopulmonary resuscitation time point is the time point at which the historical detection information of each detection type is collected each time, and the cardiopulmonary resuscitation time point is the time point in the time period from the moment when the cardiopulmonary resuscitation treatment of the patient begins to the current time position.

[0087] Based on the detection distribution information of each detection type, the terminal identifies the detection trend information of each detection type and the change trend information of each detection type, wherein the detection trend information includes the detection range trend information and the detection data trend information, and the change trend information includes the change range trend information and the change direction trend information.

[0088] Then, the terminal identifies the cardiopulmonary resuscitation change degree trend of each detection type based on the detection trend information of each detection type and the change trend information of each detection type. The cardiopulmonary resuscitation change degree trend is the change amount trend information of the cardiopulmonary resuscitation of each detection type. Finally, the terminal uses the cardiopulmonary resuscitation change degree trend of all detection types as the patient's current cardiopulmonary resuscitation effect.

[0089] Based on the above solution, by identifying the changing trend information of each detection type, the cardiopulmonary resuscitation effect of the patient can be identified, thereby improving the accuracy and comprehensiveness of the identification.

[0090] Optionally, based on the patient's applicable cardiopulmonary resuscitation strategy and the patient's current cardiopulmonary resuscitation effect, the patient's current cardiopulmonary resuscitation method is adjusted to obtain the patient's current cardiopulmonary resuscitation method guidance information, including: evaluating the resuscitation effect evaluation value of the cardiopulmonary resuscitation method through a resuscitation method evaluation network based on the cardiopulmonary resuscitation change degree trend of each detection type, and splitting the applicable cardiopulmonary resuscitation strategy into resuscitation condition ranges for each cardiopulmonary resuscitation type; screening the target resuscitation condition data for each cardiopulmonary resuscitation type within the resuscitation condition range of each cardiopulmonary resuscitation type based on the current resuscitation condition data of each cardiopulmonary resuscitation type of the current cardiopulmonary resuscitation method, and using the target resuscitation condition data for all cardiopulmonary resuscitation types as the patient's current cardiopulmonary resuscitation method guidance information.

[0091] In this embodiment, the terminal evaluates the resuscitation effect evaluation value of the cardiopulmonary resuscitation method through the resuscitation method evaluation network based on the trend of the degree of change of cardiopulmonary resuscitation of each detection type, and splits the applicable cardiopulmonary resuscitation strategy into the resuscitation condition range of each cardiopulmonary resuscitation type. Among them, the resuscitation method evaluation network includes sub-resuscitation effect evaluation values ​​corresponding to each change degree trend range of each detection type. Based on the trend of the degree of change of cardiopulmonary resuscitation of each detection type, the terminal identifies the resuscitation effect evaluation value corresponding to the change degree trend range of each detection type through the resuscitation method evaluation network. The resuscitation method evaluation network is a classifier based on a reinforcement learning neural network.

[0092] Afterwards, the terminal screens the target resuscitation condition data of each cardiopulmonary resuscitation type within the resuscitation condition range of each cardiopulmonary resuscitation type based on the current resuscitation condition data of each cardiopulmonary resuscitation type of the current cardiopulmonary resuscitation method and the resuscitation effect evaluation value. Specifically, the terminal normalizes the resuscitation effect evaluation value to obtain a resuscitation effect percentage value, and then the terminal adds 1 to the resuscitation effect percentage and multiplies it by the current resuscitation condition data of each cardiopulmonary resuscitation type to obtain the initial target resuscitation condition data of each cardiopulmonary resuscitation type. When the initial target resuscitation condition data does not belong to the resuscitation condition range, the terminal uses the edge value of the resuscitation condition range close to the initial target resuscitation condition data as the target resuscitation condition data of each cardiopulmonary resuscitation type. When the initial target resuscitation condition data belongs to the resuscitation condition range, the terminal uses each initial target resuscitation condition data as the target resuscitation condition data of each cardiopulmonary resuscitation type.

[0093] Finally, the terminal uses the target resuscitation condition data of all cardiopulmonary resuscitation types as the patient's current cardiopulmonary resuscitation method guidance information.

[0094] Based on the above scheme, after the resuscitation effect evaluation, the target resuscitation condition data of each cardiopulmonary resuscitation type is screened within the resuscitation condition range corresponding to each cardiopulmonary resuscitation type, thereby improving the practicality and accuracy of the obtained cardiopulmonary resuscitation method guidance information.

[0095] Optionally, based on the patient's cardiopulmonary resuscitation level and current cardiopulmonary resuscitation method guidance information, the patient's current target cardiopulmonary resuscitation guidance process is identified, including: based on the patient's cardiopulmonary resuscitation level, the patient's initial cardiopulmonary resuscitation process is identified, and the initial cardiopulmonary resuscitation process is split into sub-initial processes for each process stage; each cardiopulmonary resuscitation type corresponding to each sub-initial process is identified, and based on the target resuscitation condition data of each cardiopulmonary resuscitation type and each cardiopulmonary resuscitation type corresponding to each sub-initial process, the sub-process guidance information of each sub-initial process is identified; the sub-process guidance information of all sub-initial processes is sorted according to the position information of the process nodes to which each sub-initial process belongs in the initial cardiopulmonary resuscitation process to obtain the target process guidance information of the initial cardiopulmonary resuscitation process; the initial cardiopulmonary resuscitation process and the target process guidance information of the initial cardiopulmonary resuscitation process are used as the patient's current target cardiopulmonary resuscitation guidance process.

[0096] In this embodiment, the terminal identifies the initial cardiopulmonary resuscitation process of the patient based on the patient's cardiopulmonary resuscitation level, and splits the initial cardiopulmonary resuscitation process into sub-initial processes for each process stage. The terminal presets the overall cardiopulmonary resuscitation process, and then splits the cardiopulmonary resuscitation process into remaining cardiopulmonary resuscitation processes corresponding to each cardiopulmonary resuscitation level, and identifies the remaining cardiopulmonary resuscitation processes corresponding to the cardiopulmonary resuscitation level to obtain the initial cardiopulmonary resuscitation process. Finally, the terminal identifies each process stage of the initial cardiopulmonary resuscitation process, and splits the initial cardiopulmonary resuscitation process into sub-initial processes for each process stage according to each process stage. The cardiopulmonary resuscitation process includes a chest compression stage and a process that alternates between a pulmonary breathing resuscitation stage. Each stage during the alternation is a process stage.

[0097] Then, the terminal identifies each cardiopulmonary resuscitation type corresponding to each sub-initial process, and identifies the sub-process guidance information of each sub-initial process based on the target resuscitation condition data of each cardiopulmonary resuscitation type and each cardiopulmonary resuscitation type corresponding to each sub-initial process. The cardiopulmonary resuscitation types corresponding to each sub-initial process may be the same, different, or partially the same.

[0098] Then, the terminal sorts the sub-process guidance information of all sub-initial processes according to the position information of the process nodes to which each sub-initial process belongs in the initial cardiopulmonary resuscitation process, and obtains the target process guidance information of the initial cardiopulmonary resuscitation process. Finally, the terminal uses the initial cardiopulmonary resuscitation process and the target process guidance information of the initial cardiopulmonary resuscitation process as the patient's current target cardiopulmonary resuscitation guidance process.

[0099] Based on the above scheme, by detecting and identifying the cardiopulmonary resuscitation effect and degree of cardiopulmonary resuscitation, and analyzing the applicable cardiopulmonary resuscitation strategy, the patient's current target cardiopulmonary resuscitation guidance process is generated to guide the staff to perform the cardiopulmonary resuscitation process, thereby improving the degree of improvement in the patient's cardiopulmonary resuscitation effect and accelerating the patient's cardiopulmonary resuscitation degree.

[0100] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0101] Based on the same inventive concept, the embodiment of the present application also provides a cardiopulmonary resuscitation monitoring and guidance system for implementing the cardiopulmonary resuscitation monitoring and guidance method involved above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more cardiopulmonary resuscitation monitoring and guidance system embodiments provided below can refer to the limitations of the cardiopulmonary resuscitation monitoring and guidance method above, and will not be repeated here.

[0102] Further references Figure 2 , as a response to the above Figure 1 In order to realize the method shown in the figure, the present application provides an embodiment of a monitoring and guiding system 200 for cardiopulmonary resuscitation, wherein the monitoring and guiding system for cardiopulmonary resuscitation comprises an acquisition module 210, an identification module 220, an adjustment module 230 and an iteration module 240, wherein:

[0103] An acquisition module 210 is used to acquire the current detection information of each detection type of the patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information, and identify the applicable cardiopulmonary resuscitation strategy for the patient based on the patient's physical data;

[0104] An identification module 220, for identifying the patient's cardiopulmonary resuscitation degree based on the current cardiopulmonary resuscitation monitoring information, and identifying the patient's current cardiopulmonary resuscitation effect based on the current detection information of each detection type;

[0105] The adjustment module 230 is used to adjust the current cardiopulmonary resuscitation method of the patient based on the applicable cardiopulmonary resuscitation strategy of the patient and the current cardiopulmonary resuscitation effect of the patient, obtain the current cardiopulmonary resuscitation method guidance information of the patient, and identify the current target cardiopulmonary resuscitation guidance process of the patient based on the cardiopulmonary resuscitation degree of the patient and the current cardiopulmonary resuscitation method guidance information;

[0106] Iteration module 240 is used to provide cardiopulmonary resuscitation guidance to the staff through the guidance transmission unit of the cardiopulmonary resuscitation equipment via the current target cardiopulmonary resuscitation guidance process, and return to execute the steps of obtaining the current test information of each test type of the patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information until the cardiopulmonary resuscitation task for the patient is completed.

[0107] Optionally, the acquisition module 210 is specifically configured to:

[0108] Splitting the patient's body data into body shape data and physiological data, and identifying the body shape range and the physiological range of the patient in a patient cardiopulmonary resuscitation database based on the body shape data and the physiological data;

[0109] In the patient cardiopulmonary resuscitation database, a first cardiopulmonary resuscitation strategy corresponding to the body size range and a second cardiopulmonary resuscitation strategy corresponding to the physiological range are identified, and based on the first cardiopulmonary resuscitation strategy and the second cardiopulmonary resuscitation strategy, an applicable cardiopulmonary resuscitation strategy for the patient is identified.

[0110] Optionally, the identification module 220 is specifically configured to:

[0111] Splitting the current cardiopulmonary resuscitation monitoring information into sub-monitoring data of each resuscitation monitoring type, and obtaining a cardiopulmonary resuscitation evaluation strategy;

[0112] The cardiopulmonary resuscitation evaluation strategy is split into sub-evaluation strategies for each resuscitation monitoring type, and based on the sub-monitoring data of each resuscitation monitoring type, the sub-evaluation strategy for each resuscitation monitoring type and the resuscitation evaluation network are used to identify the sub-cardiopulmonary resuscitation level corresponding to each resuscitation monitoring type;

[0113] The resuscitation weight value of each resuscitation monitoring type is obtained, and based on the resuscitation weight value of each resuscitation monitoring type, the sub-cardiopulmonary resuscitation degree corresponding to each resuscitation monitoring type is weighted and summed to obtain the cardiopulmonary resuscitation degree of the patient.

[0114] Optionally, the identification module 220 is specifically configured to:

[0115] Obtaining each historical detection information of each detection type and the current cardiopulmonary resuscitation duration of the patient, and performing distribution sorting processing on each historical detection information of each detection type and the current detection information of each detection type according to the cardiopulmonary resuscitation time point corresponding to each historical detection information, to obtain detection distribution information of each detection type;

[0116] Based on the detection distribution information of each detection type, identifying the detection trend information of each detection type and the change trend information of each detection type, and based on the detection trend information of each detection type and the change trend information of each detection type, identifying the change degree trend of cardiopulmonary resuscitation of each detection type;

[0117] The trend of the change degree of cardiopulmonary resuscitation of all detected types is taken as the current cardiopulmonary resuscitation effect of the patient.

[0118] Optionally, the iteration module 230 is specifically configured to:

[0119] Based on the trend of the degree of change of cardiopulmonary resuscitation of each of the detection types, the resuscitation effect evaluation value of the cardiopulmonary resuscitation method is evaluated through a resuscitation method evaluation network, and the applicable cardiopulmonary resuscitation strategy is divided into the resuscitation condition range of each cardiopulmonary resuscitation type;

[0120] Based on the current resuscitation condition data of each cardiopulmonary resuscitation type of the current cardiopulmonary resuscitation method and the resuscitation effect evaluation value, within the resuscitation condition range of each cardiopulmonary resuscitation type, selecting target resuscitation condition data of each cardiopulmonary resuscitation type;

[0121] The target resuscitation condition data of all cardiopulmonary resuscitation types are used as the current cardiopulmonary resuscitation method guidance information for the patient.

[0122] Optionally, the iteration module 230 is specifically configured to:

[0123] Based on the patient's cardiopulmonary resuscitation level, identifying the patient's initial cardiopulmonary resuscitation process, and dividing the initial cardiopulmonary resuscitation process into sub-initial processes of each process stage;

[0124] Identify each cardiopulmonary resuscitation type corresponding to each sub-initial process, and identify sub-process guidance information of each sub-initial process based on target resuscitation condition data of each cardiopulmonary resuscitation type and each cardiopulmonary resuscitation type corresponding to each sub-initial process;

[0125] Sorting the sub-process guidance information of all sub-initial processes according to the position information of the process nodes to which each sub-initial process belongs in the initial cardiopulmonary resuscitation process, to obtain the target process guidance information of the initial cardiopulmonary resuscitation process;

[0126] The initial cardiopulmonary resuscitation process and the target process guidance information of the initial cardiopulmonary resuscitation process are used as the current target cardiopulmonary resuscitation guidance process of the patient.

[0127] Each module in the above-mentioned cardiopulmonary resuscitation monitoring and guidance system can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0128] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input system connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a monitoring and guidance method for cardiopulmonary resuscitation is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input system of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse, etc.

[0129] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0130] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0131] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0132] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of any one of the methods in the first aspect.

[0133] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0134] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0135] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0136] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A cardiopulmonary resuscitation monitoring and guidance method, characterized in that: The method comprises: Acquire the current detection information of each detection type of the patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information, and identify the applicable cardiopulmonary resuscitation strategy for the patient based on the patient's physical data; Based on the current cardiopulmonary resuscitation monitoring information, identifying the cardiopulmonary resuscitation degree of the patient, and based on the current detection information of each detection type, identifying the current cardiopulmonary resuscitation effect of the patient; Based on the applicable cardiopulmonary resuscitation strategy of the patient and the current cardiopulmonary resuscitation effect of the patient, the current cardiopulmonary resuscitation method of the patient is adjusted to obtain the current cardiopulmonary resuscitation method guidance information of the patient, and based on the cardiopulmonary resuscitation degree of the patient and the current cardiopulmonary resuscitation method guidance information, the current target cardiopulmonary resuscitation guidance process of the patient is identified; The current target cardiopulmonary resuscitation guidance process is used to provide cardiopulmonary resuscitation guidance to the staff through the guidance transmission unit of the cardiopulmonary resuscitation equipment, and returns to execute the steps of obtaining the current test information of each test type of the patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information until the patient's cardiopulmonary resuscitation task is completed.

2. The method according to claim 1, characterized in that The step of identifying an applicable cardiopulmonary resuscitation strategy for the patient based on the patient's physical data comprises: Splitting the patient's body data into body shape data and physiological data, and identifying the body shape range and the physiological range of the patient in a patient cardiopulmonary resuscitation database based on the body shape data and the physiological data; In the patient cardiopulmonary resuscitation database, a first cardiopulmonary resuscitation strategy corresponding to the body size range and a second cardiopulmonary resuscitation strategy corresponding to the physiological range are identified, and based on the first cardiopulmonary resuscitation strategy and the second cardiopulmonary resuscitation strategy, an applicable cardiopulmonary resuscitation strategy for the patient is identified.

3. The method according to claim 2, characterized in that The step of identifying the patient's cardiopulmonary resuscitation level based on the current cardiopulmonary resuscitation monitoring information includes: Splitting the current cardiopulmonary resuscitation monitoring information into sub-monitoring data of each resuscitation monitoring type, and obtaining a cardiopulmonary resuscitation evaluation strategy; The cardiopulmonary resuscitation evaluation strategy is split into sub-evaluation strategies for each resuscitation monitoring type, and based on the sub-monitoring data of each resuscitation monitoring type, the sub-evaluation strategy for each resuscitation monitoring type and the resuscitation evaluation network are used to identify the sub-cardiopulmonary resuscitation level corresponding to each resuscitation monitoring type; The resuscitation weight value of each resuscitation monitoring type is obtained, and based on the resuscitation weight value of each resuscitation monitoring type, the sub-cardiopulmonary resuscitation degree corresponding to each resuscitation monitoring type is weighted and summed to obtain the cardiopulmonary resuscitation degree of the patient.

4. The method according to claim 3, characterized in that The identifying the current cardiopulmonary resuscitation effect of the patient based on the current detection information of each detection type includes: Obtaining each historical detection information of each detection type and the current cardiopulmonary resuscitation duration of the patient, and performing distribution sorting processing on each historical detection information of each detection type and the current detection information of each detection type according to the cardiopulmonary resuscitation time point corresponding to each historical detection information, to obtain detection distribution information of each detection type; Based on the detection distribution information of each detection type, identifying the detection trend information of each detection type and the change trend information of each detection type, and based on the detection trend information of each detection type and the change trend information of each detection type, identifying the change degree trend of cardiopulmonary resuscitation of each detection type; The trend of the change degree of cardiopulmonary resuscitation of all detected types is taken as the current cardiopulmonary resuscitation effect of the patient.

5. The method according to claim 4, characterized in that The adjusting the current cardiopulmonary resuscitation method of the patient based on the applicable cardiopulmonary resuscitation strategy of the patient and the current cardiopulmonary resuscitation effect of the patient to obtain the current cardiopulmonary resuscitation method guidance information of the patient includes: Based on the trend of the degree of change of cardiopulmonary resuscitation of each of the detection types, the resuscitation effect evaluation value of the cardiopulmonary resuscitation method is evaluated through a resuscitation method evaluation network, and the applicable cardiopulmonary resuscitation strategy is divided into the resuscitation condition range of each cardiopulmonary resuscitation type; Based on the current resuscitation condition data of each cardiopulmonary resuscitation type of the current cardiopulmonary resuscitation method and the resuscitation effect evaluation value, within the resuscitation condition range of each cardiopulmonary resuscitation type, selecting target resuscitation condition data of each cardiopulmonary resuscitation type; The target resuscitation condition data of all cardiopulmonary resuscitation types are used as the current cardiopulmonary resuscitation method guidance information for the patient.

6. The method according to claim 5, characterized in that The step of identifying the current target cardiopulmonary resuscitation guidance process of the patient based on the cardiopulmonary resuscitation level of the patient and the current cardiopulmonary resuscitation method guidance information includes: Based on the patient's cardiopulmonary resuscitation level, identifying the patient's initial cardiopulmonary resuscitation process, and dividing the initial cardiopulmonary resuscitation process into sub-initial processes of each process stage; Identify each cardiopulmonary resuscitation type corresponding to each sub-initial process, and identify sub-process guidance information of each sub-initial process based on target resuscitation condition data of each cardiopulmonary resuscitation type and each cardiopulmonary resuscitation type corresponding to each sub-initial process; Sorting the sub-process guidance information of all sub-initial processes according to the position information of the process nodes to which each sub-initial process belongs in the initial cardiopulmonary resuscitation process, to obtain the target process guidance information of the initial cardiopulmonary resuscitation process; The initial cardiopulmonary resuscitation process and the target process guidance information of the initial cardiopulmonary resuscitation process are used as the current target cardiopulmonary resuscitation guidance process of the patient.

7. A cardiopulmonary resuscitation monitoring and guidance system, characterized in that: The system comprises: an acquisition module, used to acquire current detection information of each detection type of the patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information, and identify an applicable cardiopulmonary resuscitation strategy for the patient based on the patient's physical data; an identification module, configured to identify the patient's cardiopulmonary resuscitation degree based on the current cardiopulmonary resuscitation monitoring information, and to identify the patient's current cardiopulmonary resuscitation effect based on the current detection information of each detection type; an adjustment module, configured to adjust the current cardiopulmonary resuscitation method of the patient based on the applicable cardiopulmonary resuscitation strategy of the patient and the current cardiopulmonary resuscitation effect of the patient, obtain the current cardiopulmonary resuscitation method guidance information of the patient, and identify the current target cardiopulmonary resuscitation guidance process of the patient based on the cardiopulmonary resuscitation degree of the patient and the current cardiopulmonary resuscitation method guidance information; The iteration module is used to provide cardiopulmonary resuscitation guidance to the staff through the guidance transmission unit of the cardiopulmonary resuscitation equipment via the current target cardiopulmonary resuscitation guidance process, and return to execute the steps of obtaining the current detection information of each detection type of the patient, the patient's physical data, the patient's current cardiopulmonary resuscitation method, and the patient's current cardiopulmonary resuscitation monitoring information until the cardiopulmonary resuscitation task for the patient is completed.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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