Defibrillation electrode pad assembly, device, defibrillation electrode pad loss estimation method, and medium

Abstract

The present application discloses a defibrillation electrode pad assembly, a device, a defibrillation electrode pad loss estimation method, and a medium. The defibrillation electrode pad loss estimation method comprises: providing an environment container for performing electrochemical attenuation estimation of a gel material, establishing a hidden Markov model, learning the hidden Markov model, and decoding the hidden Markov model and estimating defibrillation electrode pad loss. The defibrillation electrode pad assembly comprises: an environment container, a defibrillation electrode pad, an island electrode pad, a measurement module, and a display module. A defibrillation device comprises a defibrillation electrode pad assembly and a defibrillator. The defibrillation electrode pad assembly comprises the island electrode pad used for feeding back performance parameters of the defibrillation electrode pad, the island electrode pad is placed in a sealed packaging bag, and the island electrode pad is provided with the measurement module that is connected to an external connecting end. According to the present solution, rescuers can use a correct defibrillation electrode pad on the basis of the obtained defibrillation electrode pad loss so as to improve the survival rate of patients, and can provide CPR first aid to the patients quickly and effectively so as to improve the survival rate of the patients and the first-aid effect, thereby further ensuring the life safety and health protection of the patients.

Description

Defibrillator electrode assembly, equipment, and defibrillator electrode loss estimation method and medium

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on September 27, 2023, with application number 202311263066.5 and invention name “Defibrillator electrode assembly and defibrillator device”, and the Chinese patent application filed with the China Patent Office on December 28, 2023, with application number 202311826856.X and invention name “Defibrillator electrode assembly, device and defibrillator electrode loss estimation method and medium”, all of which are incorporated by reference into this application. Technical Field

[0002] The present application belongs to the field of medical device technology, and in particular relates to a defibrillation electrode assembly, a defibrillation device, and a defibrillation electrode loss estimation method and medium. Background Art

[0003] The statements in this section merely provide background technical information related to this application and do not necessarily constitute prior art.

[0004] In the early stages of cardiac arrest, 85% to 90% of patients experience ventricular fibrillation. The most effective treatment for ventricular fibrillation is early defibrillation with an AED (Automated External Defibrillator). Defibrillation is most effective within 3-5 minutes of onset. For every minute of delay, survival decreases by 7% to 10%. Approximately 540,000 people die from cardiac arrest in my country each year. Placing AEDs in public places is a crucial measure to reduce sudden death from cardiac arrest. External defibrillation with an AED is a crucial step in CPR (Cardio Pulmonary Resuscitation). The person using an AED is called the AED CPR performer (hereinafter referred to as the performer), and the person receiving external defibrillation with an AED is called the AED CPR recipient (hereinafter referred to as the patient).

[0005] Currently, AEDs are widely used in public places outside of hospitals to provide timely assistance to patients suffering from sudden cardiac arrest. The main components of an AED are energy storage, a main control unit, a discharge unit, and electrodes. AED electrodes are a crucial component of an automated external defibrillator (AED), used to deliver electrical energy to the patient's heart to restore a normal heart rhythm. AED electrodes are generally made of conductive and gel materials, offering excellent conductivity and adhesion, allowing them to fit tightly against the patient's chest skin. During the research and development of AED electrodes, it was found that the lifespan (or shelf life) of the electrodes is mostly determined by the degree of loss of the gel material. When an AED device is placed in a public place for a long time, it is affected by the external environment and the airtightness of the AED device itself, and the gel material in the AED electrode may become invalid. When the implementer needs to use the AED, he cannot know whether the AED electrode has failed. As a result, the defibrillation effect is compromised when the AED external defibrillation is performed on the patient, and the treatment effect on the patient is reduced. If the AED electrode is found to have failed and is replaced after use, one or two minutes of rescue time will be lost in vain, reducing the patient's survival rate.

[0006] Given the widespread and dispersed nature of defibrillator equipment installations, manual inspection and maintenance of defibrillator electrodes is costly and requires a long inspection cycle. Traditionally, monitoring the status of defibrillator electrodes through an IoT platform with an expiration date has been ineffective. This approach fails to accurately monitor the electrodes' performance parameters. Changes in the temperature, humidity, and pressure of the environment surrounding the electrodes, even exceeding the set range, can cause them to fail. These changes can also alter the impedance parameters of the conductive gel layer, leading to abnormal gel impedance and reduced conductivity, making signal detection and defibrillation difficult.

[0007] Existing technologies have developed a method for testing the performance parameters of defibrillation electrodes. This involves overlapping two defibrillation electrodes, with the defibrillation layers facing each other, and then connecting them to an AC current detector to measure the gel impedance. This method requires the two defibrillation electrodes to be fixed and stacked, and the defibrillation electrodes must be separated before use, which slows down rescue efforts. Furthermore, due to the large size of the humidity sensor itself, placing it on the defibrillation electrodes used for first aid would increase their weight and size, affecting their effectiveness.

[0008] Therefore, how to solve the current lack of technical means to continuously measure and display the life loss of defibrillator electrodes, and how to effectively monitor the status of defibrillator electrodes while maintaining their working performance have become the topics to be studied and solved in this application.

[0009] Summary of the Invention

[0010] The purpose of this application is to provide a defibrillation electrode assembly, equipment, and a defibrillation electrode loss estimation method and medium.

[0011] To achieve the above-mentioned object, the first aspect of the present application provides a method for estimating the loss of defibrillation electrodes, the method comprising the following steps:

[0012] S100, setting an environmental container for performing electrochemical attenuation estimation of gel material, wherein the environmental container is equipped with a humidity sensor and an air pressure sensor for observing humidity and air pressure sequences, and determining an environmental variable and an activation energy failure mechanism variable as implicit airtightness-related parameters for the electrochemical attenuation estimation of the gel material to estimate the loss of the defibrillation electrode pad;

[0013] S200, establishing a hidden Markov model, using the hidden Markov model to establish a hidden Markov process of hidden airtightness related parameters under the observed humidity and pressure sequences, using the observed values ​​of the humidity and pressure sequences as the observation vectors of the hidden Markov chain and defining them as a collection of humidity and pressure observation sequences, and using the hidden airtightness related parameters as the hidden state vectors of the hidden Markov chain and defining them as an airtightness hidden state sequence;

[0014] S300, learning a hidden Markov model, collecting multiple sets of humidity and air pressure observation sequences to adjust model parameters, wherein the optimal model parameter set obtained under each set of humidity and air pressure observation sequences is used as the determined model parameters;

[0015] S400. Decode the hidden Markov model and estimate the loss of the defibrillator electrode. When using the device, decode the humidity and pressure observation sequence corresponding to the humidity and pressure sequence at the previous moment and determine the model parameters to obtain the implicit airtightness-related parameters of the current corresponding airtightness hidden state sequence, and use the environmental variables and activation energy failure mechanism variables corresponding to the implicit airtightness-related parameters to estimate the life measurement of the gel material, and finally obtain and display the estimated current defibrillator electrode loss value.

[0016] The second aspect of the present application proposes a defibrillation electrode assembly for intelligently displaying the loss of defibrillation electrode pads. The assembly includes defibrillation electrode pads and island electrode pads arranged in a sealed environmental container. The environmental container is equipped with a humidity sensor for observing humidity and air pressure sequences, an air pressure sensor, and a temperature sensor for observing temperature values. The humidity sensor, air pressure sensor, and temperature sensor are connected to a detection module. The detection module estimates the loss of the defibrillation electrode pad according to the defibrillation electrode pad loss estimation method described in the first aspect of the present application through the parameters obtained by the humidity sensor, air pressure sensor, and temperature sensor, and displays the estimation result through the display module.

[0017] The third aspect of the present application provides a defibrillator device, which includes the defibrillator electrode assembly described in the second aspect of the present application and a defibrillator electrically connected to the assembly. The defibrillator device can intelligently display the loss of the defibrillator electrode.

[0018] The fourth aspect of the present application provides a readable storage medium having a control program stored thereon. When the control program is executed by a detection module, the detection module executes the steps of the defibrillation electrode pad loss estimation method as described in the first aspect.

[0019] The fifth aspect of the present application proposes another defibrillation electrode assembly, in which an island electrode is arranged in a sealed packaging bag where the defibrillation electrode is located. The performance parameters of the defibrillation electrode are fed back by detecting the island electrode, with high monitoring accuracy, thereby improving the defibrillation effect.

[0020] The technical solution adopted in the fifth aspect of this application is to design a defibrillation electrode assembly, including: two defibrillation electrode pads located in a sealed packaging bag, and an island electrode pad for feedback of defibrillation electrode pad performance parameters, the two defibrillation electrode pads are connected to the external connection end through a defibrillation discharge high-voltage line, the island electrode pad is placed in the sealed packaging bag, and the island electrode pad is provided with a detection module, which is connected to the external connection end.

[0021] The sixth aspect of the present application further provides a defibrillator device, which comprises the defibrillator electrode assembly provided by the fifth aspect.

[0022] The relevant contents of this application are explained as follows:

[0023] 1. Through the implementation of the above-mentioned technical solution of the present application, in view of the fact that the life loss of defibrillator electrodes is directly related to the gel material and is affected by the external environment and the airtightness of the AED device itself, an environmental container for estimating the electrochemical decay of the gel material is first set up, and a humidity sensor and an air pressure sensor for observing humidity and air pressure sequences are equipped in the environmental container. That is, the humidity and air pressure are continuously and regularly observed during the operation of the device and collected and listed as humidity and air pressure sequences. Then, environmental variables related to the life of the gel material and activation energy failure mechanism variables are selected as implicit airtightness-related parameters for estimating the electrochemical decay of the gel material to estimate the loss of the defibrillator electrode. In this step, the sealing requirements for daily storage of defibrillator electrodes are taken into account, as well as the influence of the sealing environment on environmental variables related to the life of the gel material and the activation energy failure mechanism variables, so as to ensure the accuracy and reference value of the estimated electrode loss; and because the life state of the gel material of the defibrillator electrode depends only on the current state and external environmental factors, and is not related to the previous state, and the environmental variables and activation energy failure mechanism variables cannot be directly observed, a hidden Markov model is established to represent the implicit state of the implicit airtightness-related parameters affected by airtightness in the gel electrochemical accelerated decay estimation through the measured observation humidity and air pressure sequences, and to establish a relationship between the humidity and air pressure observation sequence and the airtightness. The method is to establish an association model of the airtightness hidden state sequence and the implicit airtightness related parameters, so that the process of electrode loss estimation has a model basis; then the hidden Markov model is learned to optimize the model, thereby improving the performance of the model and the accuracy of the model output. Finally, when using the device, the humidity and pressure observation sequence corresponding to the humidity and pressure sequence at the previous moment and the model parameters are decoded to obtain the implicit airtightness related parameters of the corresponding airtightness hidden state sequence related to the life state of the gel material of the defibrillator electrode. The life measurement of the gel material is estimated with the parameter, and finally the estimated current defibrillator electrode loss value is obtained and displayed, so that the defibrillator can When using the AED device, the rescuer can directly know the defibrillator electrode loss value (or convert it into the current validity period and service life of the defibrillator electrode) from the display module to decide whether the defibrillator electrode needs to be replaced. This ensures that the defibrillator electrode has good conductivity and adhesion when performing AED external defibrillation on the patient, ensures that the current can be accurately transmitted to the heart for defibrillation, and allows the rescuer to use the AED device correctly for AED external defibrillation without delay, racing against time to improve the patient's survival rate, and quickly and effectively perform CPR first aid on the patient, improving the patient's survival rate and first aid effect, thereby further ensuring the patient's life safety and health protection.

[0024] 2. In the first aspect of the above technical solution, in step S100, the environmental container is further equipped with a temperature sensor for observing temperature values. In step S400, the defibrillation electrode loss value is estimated in combination with the temperature value. Adding the temperature value to the defibrillation electrode loss estimation increases reliability.

[0025] 3. In the first aspect of the above technical solution, the following reaction formula is used to estimate the life loss of the electrode sheet mainly due to the loss of activation energy of the gel material:

[0026] Where F represents the chemical reaction rate of the gel material. The life of the defibrillator electrode can be calculated by the inverse of the chemical reaction rate of the gel material, that is, 1 / F; C represents the environmental variable; e represents the base of the natural logarithm; E represents the activation energy failure mechanism variable; kB is the Boltzmann constant; and M represents the temperature.

[0027] 4. In the first aspect of the above technical solution, step S200 includes the following steps:

[0028] S210, defining each tuple in the hidden Markov model, each tuple including a humidity and air pressure observation sequence set, a hidden state set, a state probability matrix, a transmission probability matrix, and an initial probability matrix;

[0029] S220, establishing a hidden Markov model, establishing a hidden Markov model related to the state probability matrix, the emission probability matrix, and the initial probability matrix;

[0030] S230 , performing hidden Markov process representation, where the hidden Markov process representation is the output probability of the humidity and air pressure observation sequence under the hidden Markov model, that is, the joint probability of the humidity and air pressure observation sequence and the airtightness implicit state representation occurring simultaneously under the hidden Markov model.

[0031] Through the implementation of the above-mentioned establishment of the hidden Markov model, the implicit airtightness-related parameters of the corresponding airtightness hidden state sequence related to the life state of the gel material of the defibrillator electrode can be effectively associated with the humidity time series sequence and the humidity and pressure observation sequence of the timed measurement of the humidity time series and the pressure time series, and the joint probability of the simultaneous occurrence of the humidity and pressure observation sequence and the airtightness implicit state representation under the hidden Markov model can be expressed through the hidden Markov process, which can provide a basis for the subsequent optimization of the model and the output of the model to ensure the accuracy of the model output and ensure that the obtained implicit airtightness-related parameters are consistent with and correct with the relevant variables of the gel material in the current state.

[0032] 5. In the first aspect of the above technical solution, step S200 includes the following steps:

[0033] S210. Define each tuple in the hidden Markov model:

[0034] S211, define a humidity and pressure observation sequence set, and convert the humidity time series sequence and the pressure time series sequence of the regular measurement into a humidity and pressure observation sequence O = [o1, o2, ..., o T ] is used as the observation vector of the hidden Markov chain and defines the humidity and pressure observation sequence set. T represents the period of time when the humidity sensor and pressure sensor are started to measure when the device is working. The observation values ​​of the measured pressure and humidity at time t are o t =[pressure t ,humidity t ] T ;

[0035] S212. Define a hidden state set, represent the airtight hidden state as the airtight hidden state sequence Q of the Markov chain, and define the airtight hidden state sequence as Q = [q1, q2, ..., q T ], then the implicit expression of the airtightness related parameters at time t in the reaction formula is q t =[C t ,E t ] T ;

[0036] S213. Define the state probability matrix: The state transition set of the airtight hidden state at different times is expressed as the state probability matrix A, where each element a of the state probability matrix A is ij represents the transition probability from state i to state j;

[0037] S214. Define the emission probability matrix: The set of possible humidity and pressure measurement values ​​generated in the airtightness hidden state is expressed as an emission probability matrix B, where each element b of the emission probability matrix B is qi Represents the hidden state q i The probability of emission to the observed state;

[0038] S215. Define the initial probability matrix: For the factory airtightness initialization hidden state expression, it is expressed as the initial probability matrix Π, where each element π in the matrix qi Represents the hidden state q i The initial probability of , i.e. the factory probability distribution;

[0039] S220, establishing a hidden Markov model, wherein the established hidden Markov model is λ={A, B, ∏};

[0040] S230, perform hidden Markov process representation, the hidden Markov process representation is the output probability of the humidity and pressure observation sequence O in the model λ={A,B,∏}, P(O|λ) is the humidity and pressure observation sequence O and the airtightness hidden state sequence Q=[q1,q2,...,q T ]The joint probability of simultaneous occurrence is as follows:

[0041] For a fixed hidden state Q = [q1,q2,...,q T ], and obtain the humidity and pressure observation sequence O=[o1,o2,...,o T The probability of ] is

[0042] Through the implementation of the above-mentioned hidden Markov model, the precision, accuracy and efficiency of the model are further enhanced, and a more reasonable and accurate model building process is adopted to provide a guarantee for subsequent loss estimation.

[0043] 6. In the first aspect of the above technical solution, in step S300 of learning the hidden Markov model, the following steps are adopted:

[0044] S310, collect K groups of humidity and pressure observation sequences O=[O 1 ,O 2 ,...,O K ],in represents the kth set of humidity and pressure observation sequence;

[0045] S320, obtain the kth group of humidity and pressure observation sequence O k The model parameters with the largest value of the joint probability are defined as optimal;

[0046] S330, using K groups of humidity and pressure observation sequences for training to obtain an optimal parameter set under a given humidity and pressure observation sequence O;

[0047] S340, by adjusting, the humidity and pressure observation sequence O and the airtightness hidden state sequence Q under the model λ are equal to [q1, q2, ..., q T ]The joint probability of simultaneous occurrence is the largest, and the optimal model parameters obtained under each group of humidity and pressure observation sequences are used as the determined model parameters.

[0048] By implementing the above process of learning the hidden Markov model, the accuracy of the implicit airtightness-related parameters obtained during subsequent model decoding can be effectively improved, thereby improving the performance of the model.

[0049] 7. In the first aspect of the above technical solution, in step S400, in obtaining the parameters representing the airtightness implicit state corresponding to the implicit airtightness-related parameters, the following steps are adopted:

[0050] S410, in determining the model parameters, define δ t (i) is a path q1,q2,...,q at time t T Generate o1, o2, ..., o t The maximum probability of

[0051] S420, initialization δ t (i) = π i b i (o i );

[0052] S430, calculate the results of the humidity and pressure observation sequence corresponding to the humidity and pressure sequence at the previous moment on the next path j

[0053] S440, take the maximum value in the path of step S430 as the output result: P(Q|λ) is the parameter representing the hidden state of its environmental variable C and activation energy failure mechanism variable E under the influence of airtightness.

[0054] By implementing the specific process of obtaining the parameters represented by the implicit airtightness state of the corresponding implicit airtightness-related parameters, the humidity and air pressure observation sequence corresponding to the humidity and air pressure sequence collected at the previous moment when the equipment is used can be effectively and correctly adopted based on the fact that the life state of the gel material of the defibrillator electrode depends only on the current state and external environmental factors, and the output result taken is the maximum value in the step S430 path as the output result, so that the obtained implicit airtightness-related parameters are closest to and most consistent with the current state of the gel material, and are the most representative. The electrode loss value obtained by estimation will also be the closest to the truth, thereby providing the rescuer with the most accurate and true defibrillator electrode loss value that is as accurate as possible, and providing protection for the patient's AED external defibrillation.

[0055] 8. In the second aspect of the above technical solution, the detection module includes a controller, the humidity sensor is connected to the controller via a data processing module, the temperature sensor is connected to the controller via a series resistor voltage divider module, and the air pressure sensor is connected to the controller. This allows the detection module to obtain correct, accurate, and valid relevant detection values, providing hardware support for the implementation of the defibrillation electrode loss estimation method.

[0056] 9. In the second aspect of the above technical solution, the island electrode sheet comprises two test sheets made of the same material as the defibrillation electrode sheet. The defibrillation layers of the two test sheets are aligned and superimposed, and the impedance test points of the two test sheets are connected to the detection module to form an impedance detection circuit for receiving direct current. Except for size, the structure and materials of the test sheets are identical to those of the defibrillation electrode sheet. Therefore, the gel impedance parameters of the island electrode sheet, after conversion to account for the size difference, are fully equivalent to the gel impedance test values ​​of the defibrillation electrode sheet.

[0057] 10. In the second aspect of the above technical solution, the detection module is equipped with a controller, the humidity sensor is connected to the IIC communication channel of the controller through the data processing module, the temperature sensor is connected in series with a resistor voltage divider module and connected to the second ADC channel of the controller, the impedance test point is connected in series with an impedance test bridge and an instrumentation amplifier and connected to the third ADC channel of the controller, the air pressure sensor is connected to the serial communication channel of the controller, and the display is connected to the SPI communication port of the controller; wherein the controller converts the analog signals of each ADC channel into digital signals.

[0058] 11. In the second aspect of the above technical solution, the temperature sensor is a thermistor, which is built into the environmental container or placed on the detection module.

[0059] 12. In the second aspect of the above technical solution, the isolated electrode sheet is installed in the environmental container and connected to the detection module through a detection connection line.

[0060] 13. In the second aspect of the above technical solution, the humidity sensor and / or the air pressure sensor is installed in the environmental container and connected to the detection module via a detection connection line, or is directly installed on the detection module.

[0061] 14. In the second aspect of the above technical solution, the area of ​​the island electrode pad is smaller than that of the defibrillation electrode pad.

[0062] 15. In the third aspect of the above technical solution, the display module is provided on at least one of the detection module, the defibrillator, the rescuer's mobile terminal or the first aid platform terminal.

[0063] 16. In the third aspect of the above technical solution, the detection module is connected to the electrode plug through a communication line and then inserted into the defibrillator. The defibrillator is located outside the environmental container, and the communication line extends from the detection module and is connected to the defibrillator through the electrode plug.

[0064] Due to the application of the above solution, this application has the following advantages and effects compared with the prior art:

[0065] 1. Through the implementation of the technical solution of the present application, an environmental container for estimating the electrochemical attenuation of the gel material is set up, and a humidity sensor and an air pressure sensor for observing the humidity and air pressure sequence are provided in the environmental container. That is, when the equipment is running, the humidity and air pressure are continuously and regularly observed and collected and listed as humidity and air pressure sequences. Then, environmental variables related to the life of the gel material and activation energy failure mechanism variables are selected as implicit airtightness-related parameters for estimating the electrochemical attenuation of the gel material to estimate the loss of the defibrillator electrode. In this step, the sealing requirements for daily storage of the defibrillator electrode are taken into account, and the influence of the sealing environment on the environmental variables related to the life of the gel material and the activation energy failure mechanism variables are taken into account to ensure the accuracy and reference value of the estimated electrode loss.

[0066] 2. Through the implementation of the technical solution of the present application, since the life state of the gel material of the defibrillator electrode depends only on the current state and external environmental factors, and is not related to the previous state, and the environmental variables and activation energy failure mechanism variables cannot be directly observed, a hidden Markov model is established to represent the implicit state of the implicit airtightness-related parameters affected by airtightness in the gel electrochemical accelerated decay estimation through the measured observed humidity and air pressure sequences, and an association model is established between the humidity and air pressure observation sequence and the airtightness hidden state sequence and the implicit airtightness-related parameters, so that the process of electrode loss estimation has a model basis, and a correct and reliable model is designed to assist in the estimation of electrode loss. By learning the hidden Markov model, the model is optimized to improve the performance of the model and the accuracy of the model output.

[0067] 3. Through the implementation of the technical solution of the present application, when using the device, decoding is performed based on the humidity and pressure observation sequence corresponding to the humidity and pressure sequence at the previous moment and the determined model parameters, so as to obtain the implicit air tightness-related parameters of the corresponding air tightness hidden state sequence related to the current life state of the gel material of the defibrillator electrode pad, and then use the parameter to estimate the life measurement of the gel material, and finally obtain the estimated current defibrillator electrode pad loss value and display it, so that the rescuer can directly know the defibrillator electrode pad loss value (or convert it into the current validity period or service life of the defibrillator electrode pad) from the display module when using the AED device, so as to decide whether the defibrillator electrode pad needs to be replaced.

[0068] 4. In summary, the implementation of the above scheme has built a stable environment, used accurate and highly correlated parameters as the basis for model establishment and optimization learning, and was able to obtain the implicit airtightness-related parameters of the current corresponding airtightness implicit state sequence based on the key point that the life state of the gel material of the defibrillation electrode depends only on the current state and external environmental factors. In this way, the current defibrillation electrode loss value closest to the current state of the gel material is estimated, filling the technical gap in the continuous measurement and display of the life loss of defibrillation electrodes. It can ensure that the defibrillation electrodes have good conductivity and adhesion when the rescuer performs AED external defibrillation on the patient, ensure that the current can be accurately transmitted to the heart for defibrillation, and ensure that the rescuer uses the AED device correctly for AED external defibrillation without delay, saving every second, thereby improving the patient's survival rate, and can quickly and effectively perform CPR on the patient, improving the patient's survival rate and first aid effect, thereby further ensuring the patient's life safety and health protection.

[0069] 5. Compared with the prior art, the present application sets an island electrode sheet in the sealed packaging bag where the defibrillator electrode sheet is located, monitors various parameters of the island electrode sheet through the detection module, and then infers or directly reads the performance parameters of the defibrillator electrode sheet, with high monitoring accuracy. Moreover, the island electrode sheet and the detection module are completely independently arranged outside the defibrillator electrode sheet. The defibrillator electrode sheet has fewer wirings, is lighter and thinner, and is less subject to interference during operation, thereby improving the defibrillation effect and being more practical. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The present application is described in detail below with reference to the embodiments and accompanying drawings, wherein:

[0071] FIG1 is a flow chart of a method for estimating defibrillation electrode loss according to a first embodiment of the present application;

[0072] FIG2 is a schematic diagram of establishing a hidden Markov process in Example 1 of the present application;

[0073] FIG3 is a schematic diagram of the distribution of the defibrillation electrode assembly according to the second embodiment of the present application;

[0074] FIG4 is a circuit connection diagram of a defibrillator device according to a third embodiment of the present application;

[0075] FIG5 is a schematic diagram of the distribution of the defibrillation electrode assembly in a packaging bag according to a fifth embodiment of the present application;

[0076] FIG6 is a schematic diagram of the circuit connection of the defibrillation electrode assembly according to the fifth embodiment of the present application.

[0077] Figure numerals: 1. Defibrillation electrode pad; 11. Left defibrillation electrode pad; 12. Right defibrillation electrode pad; 13. Defibrillation discharge high-voltage line; 2. Island electrode pad; 21. Impedance detection line; 22. Temperature detection line; 23. Humidity detection line; 24. Air pressure detection line; 3. External connection terminal; 4. Temperature sensor; 5. Humidity sensor. DETAILED DESCRIPTION

[0078] To make the above-mentioned objects, features, and advantages of the present application more clearly understood, the specific embodiments of the present application are described in detail below with reference to the accompanying drawings. The following description sets forth many specific details to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways than those described herein, and those skilled in the art can make similar improvements without violating the scope of the present application. Therefore, the present application is not limited to the specific embodiments disclosed below.

[0079] The terms used herein are for describing specific embodiments only and are not intended to be limiting of the present invention. Singular forms such as "a," "the," "this," and "the" as used herein also include plural forms.

[0080] The terms “first”, “second”, etc. used in this document do not specifically refer to an order or sequence, nor are they used to limit this case. They are only used to distinguish components or operations described with the same technical terms.

[0081] As used herein, “connected” or “positioned” may refer to two or more components or devices being in direct or indirect physical contact with each other, or may refer to two or more components or devices operating or moving with each other.

[0082] The terms “include”, “including”, “have”, etc. used in this document are open-ended terms, meaning including but not limited to.

[0083] Unless otherwise noted, the terms used herein generally have their ordinary meanings in the art, within the context of the present invention, and in the specific context. Certain terms used to describe the present invention are discussed below or elsewhere in this specification to provide additional guidance to those skilled in the art regarding the present invention.

[0084] This application aims to provide a technical solution that can regularly detect and estimate the loss of defibrillator electrodes and allow rescuers to directly know the loss of electrode pads when using defibrillator equipment, so as to fill the technical gap in the continuous measurement and display of the life loss of defibrillator electrode pads. It allows rescuers to know the loss value of defibrillator electrode pads and decide whether to replace the defibrillator electrode pads, thereby ensuring that the defibrillator electrode pads have good conductivity and adhesion when the patient undergoes AED external defibrillation, ensuring that the current can be accurately transmitted to the heart for defibrillation, and allowing rescuers to correctly use the AED equipment for AED external defibrillation without delay, saving every second, thereby improving the patient's survival rate, and being able to quickly and effectively perform CPR first aid on the patient, improving the patient's survival rate and first aid effect, thereby further ensuring the patient's life safety and health protection.

[0085] In the first embodiment, the life loss of defibrillation electrodes is directly related to the gel material and is affected by the external environment and the airtightness of the AED device itself. In the first embodiment of the present application, a method for estimating the loss of defibrillation electrodes is proposed. As shown in FIG1 , the method for estimating the loss of defibrillation electrodes comprises the following steps:

[0086] S100, setting an environmental container for performing electrochemical attenuation estimation of gel material, wherein the environmental container is equipped with a humidity sensor and an air pressure sensor for observing humidity and air pressure sequences, and determining an environmental variable and an activation energy failure mechanism variable as implicit airtightness-related parameters for the electrochemical attenuation estimation of the gel material to estimate the loss of the defibrillation electrode pad;

[0087] S200, establishing a hidden Markov model, using the hidden Markov model to establish a hidden Markov process of hidden airtightness related parameters under the observed humidity and pressure sequences, using the observed values ​​of the humidity and pressure sequences as the observation vectors of the hidden Markov chain and defining them as a collection of humidity and pressure observation sequences, and using the hidden airtightness related parameters as the hidden state vectors of the hidden Markov chain and defining them as an airtightness hidden state sequence;

[0088] S300, learning a hidden Markov model, collecting multiple sets of humidity and air pressure observation sequences to adjust model parameters, wherein the optimal model parameter set obtained under each set of humidity and air pressure observation sequences is used as the determined model parameters;

[0089] S400. Decode the hidden Markov model and estimate the loss of the defibrillator electrode. When using the device, decode the humidity and pressure observation sequence corresponding to the humidity and pressure sequence at the previous moment and determine the model parameters to obtain the implicit airtightness-related parameters of the current corresponding airtightness hidden state sequence, and use the environmental variables and activation energy failure mechanism variables corresponding to the implicit airtightness-related parameters to estimate the life measurement of the gel material, and finally obtain and display the estimated current defibrillator electrode loss value.

[0090] In the above-mentioned step S100 of setting up an environmental container for estimating the electrochemical attenuation of the gel material, in view of the fact that the life loss of the defibrillator electrode is directly related to the gel material and is affected by the external environment and the airtightness of the AED device itself, a humidity sensor and an air pressure sensor for observing humidity and air pressure sequences are provided in the environmental container. That is, when the device is running, continuous and regular humidity and air pressure observations are performed and collected and listed as humidity and air pressure sequences. Then, environmental variables related to the life of the gel material and activation energy failure mechanism variables are selected as implicit airtightness-related parameters for estimating the electrochemical attenuation of the gel material to estimate the loss of the defibrillator electrode. In this step, both the sealing requirements for daily storage of the defibrillator electrode and the influence of the sealing environment on the environmental variables related to the life of the gel material and the activation energy failure mechanism variables are taken into account to ensure the accuracy and reference value of the estimated electrode loss.

[0091] In the above-mentioned step S200 of establishing a hidden Markov model, it is taken into consideration that the life state of the gel material of the defibrillator electrode depends only on the current state and external environmental factors, but is unrelated to the previous state, and that environmental variables and activation energy failure mechanism variables cannot be directly observed. Therefore, a hidden Markov model is established to represent the implicit state of the implicit airtightness-related parameters affected by airtightness in the gel electrochemical accelerated decay estimation through the measured observed humidity and air pressure sequences, and to establish an association model between the humidity and air pressure observation sequence and the airtightness hidden state sequence and the implicit airtightness-related parameters, so that the process of electrode loss estimation has a model basis, and a correct and reliable model is designed to provide assistance for the estimation of electrode loss.

[0092] In the step of learning the hidden Markov model in S300 , the hidden Markov model is learned to optimize the model, thereby improving the performance of the model and the accuracy of the model output.

[0093] In the above-mentioned step S400 of decoding the hidden Markov model and estimating the loss of the defibrillator electrode pads, when using the device, decoding is performed based on the humidity and pressure observation sequence corresponding to the humidity and pressure sequence at the previous moment and the determined model parameters, so as to obtain the implicit air-tightness-related parameters of the corresponding air-tightness hidden state sequence related to the current life state of the gel material of the defibrillator electrode pads, and then the life measurement of the gel material is estimated using the parameter, and finally the estimated current defibrillator electrode pad loss value is obtained and displayed, so that the rescuer can directly know the defibrillator electrode pad loss value (or can be converted into the current validity period or service life of the defibrillator electrode pad) from the display module when using the AED device, so as to decide whether the defibrillator electrode pads need to be replaced.

[0094] In the first embodiment of the present application, in step S100, the environmental container is further equipped with a temperature sensor for observing temperature values. In step S400, the loss value of the defibrillation electrode is estimated in combination with the temperature value. Adding the temperature value to the loss estimation of the defibrillation electrode increases reliability.

[0095] In the first embodiment of the present application, step S200 includes the following steps:

[0096] S210, defining each tuple in the hidden Markov model, each tuple including a humidity and air pressure observation sequence set, a hidden state set, a state probability matrix, a transmission probability matrix, and an initial probability matrix;

[0097] S220, establishing a hidden Markov model, establishing a hidden Markov model related to the state probability matrix, the emission probability matrix, and the initial probability matrix;

[0098] S230 , performing hidden Markov process representation, where the hidden Markov process representation is the output probability of the humidity and air pressure observation sequence under the hidden Markov model, that is, the joint probability of the humidity and air pressure observation sequence and the airtightness implicit state representation occurring simultaneously under the hidden Markov model.

[0099] Through the implementation of the above-mentioned establishment of the hidden Markov model, the implicit airtightness-related parameters of the corresponding airtightness hidden state sequence related to the life state of the gel material of the defibrillator electrode can be effectively associated with the humidity time series sequence and the humidity and pressure observation sequence of the timed measurement of the humidity time series and the pressure time series, and the joint probability of the simultaneous occurrence of the humidity and pressure observation sequence and the airtightness implicit state representation under the hidden Markov model can be expressed through the hidden Markov process, which can provide a basis for the subsequent optimization of the model and the output of the model to ensure the accuracy of the model output and ensure that the obtained implicit airtightness-related parameters are consistent with and correct with the relevant variables of the gel material in the current state.

[0100] In the first embodiment of the present application, in step S300 of learning the hidden Markov model, the following steps are adopted:

[0101] S310, collect K groups of humidity and pressure observation sequences O=[O 1 ,O 2 ,...,O K ],in represents the kth set of humidity and pressure observation sequence;

[0102] S320, obtain the kth group of humidity and pressure observation sequence O k The model parameters with the largest value of the joint probability are defined as optimal;

[0103] S330, using K groups of humidity and pressure observation sequences for training to obtain an optimal parameter set under a given humidity and pressure observation sequence O;

[0104] S340, by adjusting, the humidity and pressure observation sequence O and the airtightness hidden state sequence Q under the model λ are equal to [q1, q2, ..., q T ]The joint probability of simultaneous occurrence is the largest, and the optimal model parameters obtained under each group of humidity and pressure observation sequences are used as the determined model parameters.

[0105] By implementing the above process of learning the hidden Markov model, the accuracy of the implicit airtightness-related parameters obtained during subsequent model decoding can be effectively improved, thereby improving the performance of the model.

[0106] In the first embodiment of the present application, in step S400, in obtaining the parameters representing the airtightness implicit state corresponding to the implicit airtightness-related parameters, the following steps are adopted:

[0107] S410, in determining the model parameters, define δ t (i) is a path q1,q2,...,q at time t T Generate o1, o2, ..., o t The maximum probability of

[0108] S420, initialization δ t (i) = π i b i (o i );

[0109] S430, calculate the results of the humidity and pressure observation sequence corresponding to the humidity and pressure sequence at the previous moment on the next path j

[0110] S440, take the maximum value in the path of step S430 as the output result: That is, the parameters representing the hidden state of the environmental variable C and the activation energy failure mechanism variable E under the influence of airtightness.

[0111] By implementing the specific process of obtaining the parameters represented by the implicit airtightness state of the corresponding implicit airtightness-related parameters, the humidity and air pressure observation sequence corresponding to the humidity and air pressure sequence collected at the previous moment when the equipment is used can be effectively and correctly adopted based on the fact that the life state of the gel material of the defibrillator electrode depends only on the current state and external environmental factors, and the output result taken is the maximum value in the step S430 path as the output result, so that the obtained implicit airtightness-related parameters are closest to and most consistent with the current state of the gel material, and are the most representative. The electrode loss value obtained by estimation will also be the closest to the truth, thereby providing the rescuer with the most accurate and true defibrillator electrode loss value that is as accurate as possible, and providing protection for the patient's AED external defibrillation.

[0112] The following further illustrates Example 1 of the present application with a more specific detailed embodiment.

[0113] This detailed embodiment uses continuous and periodic measurements of humidity, air pressure, and temperature during device operation to estimate the lifespan of gel-based defibrillator electrodes. This approach utilizes a hidden Markov model to represent the implicit state of hyperparameters affected by airtightness in the electrochemical accelerated decay formula using the observed humidity and air pressure sequences. The formula is then combined with temperature to estimate the electrode lifespan.

[0114] To implement this detailed embodiment, the present application designs and uses a humidity sensor and an air pressure sensor to detect the sealing environment of the environmental container. Furthermore, a hidden Markov model is used to establish a hidden Markov process of airtightness-related parameters under the observed humidity and air pressure sequences. The implicit state representation of the hyperparameters affected by airtightness (environmental variables, failure mechanism variables of activation energy) in the Arrhenius formula is calculated to estimate the life loss of the electrode sheet.

[0115] Before the defibrillator equipment leaves the factory, the Baum-Welch algorithm is used to learn the hidden Markov model to obtain the hidden Markov model parameter set.

[0116] During the use of the defibrillator, the Viterbi algorithm is used to decode the hidden Markov model to obtain the implicit representation of the airtightness-related parameters (environmental variables, failure mechanism variables of activation energy) under the humidity and air pressure sequence measured by the timed sensor, and then the Arrhenius formula is used to further estimate the life measurement of the gel material components.

[0117] In step S100 of this detailed embodiment, which sets up an environmental container for estimating the electrochemical decay of the gel material, the gel activation energy is directly affected by the internal temperature of the defibrillation electrode. Temperature changes can reduce the viscosity of the electrode in contact with the human body, resulting in component life loss. We use the Arrhenius formula to estimate electrode life loss, primarily due to gel material activation energy loss. The Arrhenius acceleration model is widely used for life prediction and expresses life as a function of temperature. The Arrhenius formula is expressed as:

[0118] Here, F represents the chemical reaction rate of the gel material. Component life can be calculated as the inverse of the chemical reaction rate, i.e., 1 / F. C is an environmental variable. For gel materials, its value is directly related to the sealing environment of the component. e represents the base of the natural logarithm. E represents the failure mechanism variable of the gel activation energy, which decays with changes in air density. kB is the Boltzmann constant, specifically equal to 8.62×10e^(-5e)V / K. M represents temperature.

[0119] According to the above formula, in addition to being directly affected by temperature, the gel activation energy, its environmental variable C and activation energy failure mechanism variable E, are also affected by the sealing environment: in a completely open environment without sealing, the effectiveness of the gel material continues to decay, and its activation energy will gradually fail within 24 hours.

[0120] Therefore, in S100, an environmental container is set up for estimating the electrochemical attenuation of the gel material. The environmental container is equipped with a humidity sensor and an air pressure sensor for observing humidity and air pressure sequences. The environmental container is also equipped with a temperature sensor for observing temperature values. The environmental variables and activation energy failure mechanism variables are determined as implicit airtightness-related parameters for estimating the electrochemical attenuation of the gel material to estimate the loss of the defibrillator electrode.

[0121] In the process of establishing a hidden Markov model in step S200 of this detailed embodiment, the Markov substantive assumption is made, that is, the implicit state representation of the hyperparameters (environmental variables, failure mechanism variables of activation energy) affected by airtightness in the Arrhenius formula is only related to the implicit state at the previous moment and the observed pressure and humidity measurements. The Markov model is established as shown in Figure 2. The specific steps are as follows:

[0122] S210. Define each tuple in the hidden Markov model:

[0123] S211, define a humidity and pressure observation sequence set, and convert the humidity time series sequence and the pressure time series sequence of the regular measurement into a humidity and pressure observation sequence O = [o1, o2, ..., o T] is used as the observation vector of the hidden Markov chain and defines the humidity and pressure observation sequence set. T represents the period of time when the humidity sensor and pressure sensor are started to measure when the device is working. The observation values ​​of the measured pressure and humidity at time t are o t =[pressure t ,humidity t ] T ;

[0124] S212. Define a hidden state set, represent the airtight hidden state as the airtight hidden state sequence Q of the Markov chain, and define the airtight hidden state sequence as Q = [q1, q2, ..., q T ], then the implicit expression of the airtightness related parameters (environmental variables, failure mechanism variables of activation energy) at time t in the reaction formula is q t =[C t ,E t ] T ;

[0125] S213. Define the state probability matrix: The state transition set of the airtight hidden state at different times is expressed as the state probability matrix A, where each element a of the state probability matrix A is ij represents the transition probability from state i to state j;

[0126] S214. Define the emission probability matrix: The set of possible humidity and pressure measurement values ​​generated in the airtightness hidden state is expressed as an emission probability matrix B, where each element of the emission probability matrix B is Represents the hidden state q i The probability of emission to the observed state;

[0127] S215. Define the initial probability matrix: For the factory airtightness initialization hidden state expression, it is expressed as the initial probability matrix Ώ, where each element in the matrix Represents the hidden state q i The initial probability of , i.e. the factory probability distribution;

[0128] S220, establishing a hidden Markov model, wherein the established hidden Markov model is λ={A, B, ∏};

[0129] S230, perform hidden Markov process representation, the hidden Markov process representation is the output probability of the humidity and pressure observation sequence O in the model λ={A,B,∏}, P(O|λ) is the humidity and pressure observation sequence O and the airtightness hidden state sequence Q=[q1,q2,...,q T ]The joint probability of simultaneous occurrence is as follows:

[0130] For a fixed hidden state Q = [q1,q2,...,q T ], and obtain the humidity and pressure observation sequence O=[o1,o2,...,o T The probability of ] is

[0131] In the process of learning the hidden Markov model in step S300 of this detailed embodiment, before the device leaves the factory, learning is performed on the defined Markov model to obtain the optimal model parameters under the observation sequence O. This is the process of finding the optimal parameter set λ = {A, B, ∏} that maximizes P(O|λ) under the given observation sequence O. This can be performed using the Baum-Welch algorithm. Specifically, the following steps are included:

[0132] S310, collect K groups of humidity and pressure observation sequences O=[O 1 ,O 2 ,...,O K ],in represents the kth set of humidity and pressure observation sequence;

[0133] S320, obtain the kth group of humidity and pressure observation sequence O k The model parameters with the largest value of the joint probability are defined as optimal. The process is:

[0134] Among them, the hidden Markov observation value is a continuous variable, and its emission probability probability density function is expressed by a mixed one-dimensional Gaussian probability density function as follows:

[0135] Where: c jm ,μ jm ,σ jm State Q j The mixing weight, density, and variance of the Gaussian density in the mth column, when the airtightness hidden state is only affected by humidity and air pressure, is m = 2;

[0136] definition Indicates that it is in state Q at time t i , and is in state Q at time t+1 j probability; Indicates that it is in state Q at time t i probability; Indicates that it is in state Q at time t i The probability of the mixed number of the mth column, the posterior probability of the parameter estimate is expressed as follows:

[0137] in, is the forward-backward variable of the k-th observation sample sequence.

[0138] S330, using K groups of humidity and pressure observation sequences for training to obtain an optimal parameter set under a given humidity and pressure observation sequence O;

[0139] S340, by adjusting, the humidity and pressure observation sequence O and the airtightness hidden state sequence Q under the model λ are equal to [q1, q2, ..., q T ]The joint probability of simultaneous occurrence is the largest. The optimal model parameters obtained under each group of humidity and pressure observation sequences are used as the determined model parameters. The Baum-Welch algorithm is used to estimate the model parameters λ={A, B, π} as follows:

[0140] Calculate the initial probability distribution π as:

[0141] Calculate the state transition probability A as:

[0142] The mixed one-dimensional Gaussian probability density in the emission probability density B is calculated as:

[0143] In step S400 of this detailed embodiment, decoding the hidden Markov model and estimating defibrillation electrode loss involves decoding the defined Markov model to obtain the implicit representation of airtightness Q under the observation sequence O. This involves finding the most likely state sequence Q under the given observation sequence O and the determined model parameters λ = {A, B, ∏}, such that the joint P(Q|λ) is maximized. The specific steps are as follows:

[0144] S410, in determining the model parameters, define δ t (i) is a path q1,q2,...,q at time t T Generate o1, o2, ..., o t The maximum probability of

[0145] S420, initialization δ t (i) = π i b i (o i );

[0146] S430, calculate the results of the humidity and pressure observation sequence corresponding to the humidity and pressure sequence at the previous moment on the next path j

[0147] S440, take the maximum value in the path of step S430 as the output result: That is, the parameters representing the hidden state of the environmental variable C and the activation energy failure mechanism variable E under the influence of airtightness.

[0148] S450, using the environmental variable C and activation energy failure mechanism variable E obtained in step S440, as well as the temperature value measured by the temperature sensor, using the reaction formula The chemical reaction rate can be estimated and the life of the defibrillator electrode can be calculated by taking the inverse of the chemical reaction rate of the gel material, i.e. 1 / F.

[0149] The validity period of the electrode sheet is Y years. Due to changes in the environment, the F value also changes. After algorithm analysis, the F value is obtained, and the validity period YT = Y / F, the current validity period of the electrode sheet can be obtained. The calculation result is displayed through the display module of the detection module, or on the defibrillator, or the rescuer's mobile terminal, or the first aid platform terminal, or displayed on at least one of the above.

[0150] Example 2. Example 2 of the present application proposes a defibrillator electrode assembly, which can intelligently display the loss of defibrillator electrode pads. The assembly includes an environmental container, a defibrillator electrode pad, an island electrode pad, and a detection module. The environmental container can be a sealed environmental container. The environmental container is equipped with a humidity sensor for observing humidity and air pressure sequences, an air pressure sensor, and a temperature sensor for observing temperature values. The humidity sensor, air pressure sensor, and temperature sensor are connected to the detection module. The detection module estimates the loss of the defibrillator electrode pad according to the defibrillator electrode pad loss estimation method described in the first aspect of the present application through the parameters obtained by the humidity sensor, air pressure sensor, and temperature sensor, and displays the estimation result through the display module.

[0151] In the second embodiment of the present application, the defibrillation electrode pad and the island electrode pad are located in the same environmental container. The two defibrillation electrode pads are connected to the electrode pad plug through the defibrillation discharge high-voltage line. The island electrode pad is connected to the detection module. The detection module is used to monitor various parameters of the island electrode pad. The detection module is inserted into the defibrillator through the electrode pad plug. The detection module controller obtains the various parameters sent from the sensor, and then performs algorithm analysis or directly reads the performance parameters of the defibrillation electrode pad. Temperature, air pressure, sealing and gel impedance are all performance parameters for judging the effectiveness of the defibrillation electrode pad.

[0152] In a preferred embodiment of the present application, the island electrode sheet includes two test sheets made of the same material as the defibrillation electrode sheet. That is, except for the size, the structure, material, etc. of the test sheets are the same as the defibrillation electrode sheets. Therefore, the gel impedance parameters of the monitored island electrode sheets can be completely equivalent to the gel impedance test values ​​of the defibrillation electrode sheets after conversion due to the size difference.

[0153] Gel impedance detection is achieved by aligning and overlapping the defibrillation layer of the test piece with the non-stick paper. The detection module includes: impedance test points provided on the defibrillation layer of the test piece. The impedance test points of the two test pieces are respectively connected to the detection module through impedance detection lines to form an impedance detection circuit for connecting to direct current. After connecting to direct current, an analog signal can be calculated based on the voltage and current data, and then the impedance of the gel layer to be obtained can be inferred from the detected analog signal. This method of detecting impedance with direct current is easy to implement and the results are more accurate.

[0154] The detection module also includes: a temperature sensor detection circuit and / or a humidity sensor detection circuit and / or an air pressure sensor detection circuit / display screen, each sensor detection circuit and display screen being connected to the detection module controller via their respective corresponding connection lines; in detail, the temperature sensor detection circuit detects a detection signal via a temperature detection line and is then connected to the detection module controller; the humidity sensor detection circuit is connected to the detection module via a humidity detection line and is then connected to the detection module controller; the air pressure sensor is connected to the detection module via an air pressure detection line and is then connected to the detection module controller. It should be understood that the detection lines herein are all designed with input lines and output lines to form a detection circuit, i.e., the detection lines shown in FIG3 are multiple lines.

[0155] The reason for designing a temperature sensor is that the internal temperature of the defibrillation electrode will directly affect the viscosity of the gel and the human body. Too high or too low a temperature may even directly cause the electrode to fail. Therefore, the temperature of the defibrillation electrode can effectively reflect the effectiveness of the defibrillation electrode.

[0156] The reason for designing humidity sensors and air pressure sensors is that defibrillator electrodes are usually sealed in an environmental container. In an unsealed state, defibrillator electrodes are usually only valid for 24 hours. Therefore, the sealing of the defibrillator electrode packaging can effectively reflect the effectiveness of the defibrillator electrode. The changes in humidity and air pressure in a sealed environment can determine whether the seal of the environmental container has leaks or other faults. That is, the sealing can be reflected by the humidity information and air pressure information in the environmental container.

[0157] The reason for designing the display screen is that the performance parameters of the defibrillator electrodes can be displayed on the display screen, or on the defibrillator's display screen or on the defibrillator cloud, which is intuitive and clear.

[0158] As shown in Figures 3 and 4, in some embodiments of the present application, the detection module includes a temperature sensor, a humidity sensor, and an air pressure sensor. The detection module is provided with a controller and a display screen. The humidity sensor is connected to the controller's IIC communication channel via the data processing module. The temperature sensor is connected in series with a second resistor to the controller's second ADC channel. The temperature AD value is detected via the second ADC channel, and the humidity AD value is detected via the IIC communication channel. The controller can then obtain temperature information and humidity information based on the temperature and humidity impedance linear table. The impedance test point is connected in series with an impedance test bridge and an instrumentation amplifier to the controller's third ADC channel. The controller converts the AD value of the third ADC channel to obtain gel impedance information. The air pressure sensor is connected to the controller's serial communication channel. The air pressure sensor converts the change in air pressure into an electrical signal. After the electrical signal is amplified, the analog signal is converted into a digital signal through AD conversion, and finally transmitted to the controller via serial communication. The controller communicates with the display screen via SPI to display the defibrillation electrode parameters.

[0159] In some embodiments of the present application, the temperature sensor is a thermistor, which is built into the environmental container or on the detection module to improve the accuracy of temperature monitoring.

[0160] It should be understood that since the island electrode and the defibrillation electrode are located in the same environmental container, that is, both are in the same environment, and the material of the island electrode is the same as that of the defibrillation electrode, the internal temperature of the island electrode can be equivalent to the internal temperature of the defibrillation electrode.

[0161] As shown in FIG3 , the isolated electrode sheet and / or the humidity sensor and / or the air pressure sensor and / or the temperature sensor are installed in the environmental container. A preferred solution is that the isolated electrode sheet, the humidity sensor, the temperature sensor, and the air pressure sensor are arranged adjacent to each other, so that the isolated electrode sheet, the temperature sensor, the humidity sensor, and the air pressure sensor are completely independent of the defibrillation electrode sheet. The defibrillation electrode sheet is only designed with a defibrillation discharge high-voltage wire, with fewer wiring and a thinner electrode sheet. Moreover, since the defibrillation electrode sheet is not additionally installed with a sensor, the interference during defibrillation operation is small, thereby effectively improving the defibrillation effect.

[0162] As shown in Figure 3, the defibrillator is located outside the environmental container, the detection module is located between the environmental container and the defibrillator, the detection line extends from the environmental container and is connected to the detection module, the electrode plug connects the defibrillator electrode and the detection module, the detection module connects the island electrode and various sensors, and the electrode plug is inserted into the defibrillator. It should be understood that the "connection" mentioned herein can be a wired connection, such as the various detection lines described above, or a wireless connection. This application imposes special restrictions on the specific implementation of the connection, as long as it can achieve energy or signal transmission.

[0163] On this basis, the area of ​​the island electrode sheet is smaller than that of the defibrillator electrode sheet, which reduces the space occupied by the island electrode sheet and reduces production costs. The defibrillator is located on one side of the environmental container, and the island electrode sheet is set close to the detection module. The detection module is between the island electrode sheet and the defibrillator, shortening the length of the detection line between the island electrode sheet and the detection module.

[0164] Embodiment 3. Embodiment 3 of the present application further proposes a defibrillator device having the above-mentioned defibrillator electrode assembly. The defibrillator device includes a defibrillator and a defibrillator device. The defibrillator device includes a defibrillator controller. The defibrillator controller obtains the temperature, humidity, package sealing, and impedance data of the defibrillator electrode in real time through a detection module, and makes a judgment on the effectiveness and loss of the defibrillator electrode. The controller of the detection module can also obtain the temperature, humidity, package sealing, and impedance data of the defibrillator electrode in real time, and estimate the loss of the defibrillator electrode. The relevant personnel are then notified through the display screen of the detection module, the display screen of the defibrillator, the cloud networking of the defibrillator, voice broadcast, or other means.

[0165] Example 4. Example 4 of the present application also proposes a readable storage medium, on which a control program is stored. When the control program is executed by the detection module, the detection module executes the steps of the defibrillation electrode loss estimation method described in Example 1 of the present application.

[0166] Example 5, as shown in Figure 5, another defibrillation electrode pad assembly proposed in the present application includes: two defibrillation electrode pads 1 and an island electrode pad 2, the two defibrillation electrode pads 1 are respectively a left defibrillation electrode pad 11 and a right defibrillation electrode pad 12, the defibrillation electrode pad 1 has a defibrillation layer, the defibrillation layer includes a conductive layer and a gel layer provided on the outer surface of the conductive layer, and then the outer surface of the gel layer is covered with non-stick paper, the function of the non-stick paper is to protect the gel layer.

[0167] The defibrillation electrode pad 1 and the island electrode pad 2 are located in the same sealed packaging bag. The two defibrillation electrode pads 1 are connected to the external connection terminal 3 through the defibrillation discharge high-voltage line 13. The island electrode pad 2 is provided with a detection module, which is used to monitor the various parameters of the island electrode pad 2. The detection module is connected to the external connection terminal 3. The controller obtains the various parameters sent by the detection module from the external connection terminal 3, and then infers or directly reads the performance parameters of the defibrillation electrode pad. Temperature, air pressure, sealing and gel impedance are all performance parameters for judging the effectiveness of the defibrillation electrode pad.

[0168] In an embodiment of the present application, the island electrode piece 2 includes two test pieces made of the same material as the defibrillation electrode piece 1. That is, except for the size, the structure, material, etc. of the test pieces are the same as the defibrillation electrode piece. Therefore, the gel impedance parameters of the monitored island electrode piece 2 can be completely equivalent to the gel impedance test value of the defibrillation electrode piece 1 after conversion due to the size difference.

[0169] The gel impedance detection is implemented by aligning and overlapping the defibrillation layers of the two test pieces. The detection module includes: impedance test points provided on the defibrillation layer of the test piece. The impedance test points of the two test pieces are respectively connected to the external connection terminal 3 through the impedance detection line 21 to form an impedance detection circuit for accessing alternating current. The two test pieces of the isolated electrode piece 2 are overlapped to form a capacitor of the impedance detection circuit. After the alternating current is connected, the capacitance of the capacitor can be calculated based on the voltage and current data, and then the impedance of the gel layer to be obtained can be inferred from the detected capacitance. This method of detecting impedance with alternating current is easy to implement and the results are more accurate.

[0170] The detection module also includes: a temperature sensor 4 and / or a humidity sensor 5 and / or an air pressure sensor, each of which is connected to the external connection terminal via its own corresponding detection line. Furthermore, the temperature sensor 4 is connected to the external connection terminal 3 via a temperature detection line 22, the humidity sensor 5 is connected to the external connection terminal 3 via a humidity detection line 23, and the air pressure sensor is connected to the external connection terminal 3 via an air pressure detection line 24. It should be understood that the detection lines herein are designed with input lines and output lines to form a detection loop, that is, in Figure 1, there are two detection lines of each type.

[0171] The temperature sensor 4 is designed because the internal temperature of the defibrillation electrode 1 directly affects the viscosity of the gel combined with the human body. Too high or too low a temperature may even directly cause the electrode to fail. Therefore, the temperature of the defibrillation electrode 1 can effectively reflect the effectiveness of the defibrillation electrode 1.

[0172] The reason for designing the humidity sensor 5 and the air pressure sensor is that the defibrillator electrode 1 is usually sealed in a packaging bag. In an unsealed state, the defibrillator electrode 1 is usually only valid for 24 hours. Therefore, the sealing of the packaging of the defibrillator electrode 1 can effectively reflect the effectiveness of the defibrillator electrode 1, and the humidity and air pressure changes in a sealed environment can determine whether the sealing of the packaging bag has leaks or other faults. That is, the sealing can be reflected by the humidity information and air pressure information in the packaging bag.

[0173] As shown in Figures 5 and 6, in some embodiments of the present application, the detection module includes a temperature sensor 4, a humidity sensor 5, and an air pressure sensor. The external connection terminal 3 is connected to the controller. The humidity sensor is connected to the controller's IIC communication channel through the data processing module. The temperature sensor 4 is connected in series with a second resistor to the controller's second ADC channel. The temperature AD value is detected through the second ADC channel, and the humidity AD value is detected through the IIC communication channel. The controller can then obtain temperature information and humidity information based on the temperature and humidity impedance linear table. The impedance test point is connected in series with an impedance test bridge and an instrumentation amplifier to the controller's third ADC channel. The controller converts the AD value of the third ADC channel to obtain gel impedance information. The air pressure sensor is connected to the controller's serial communication channel. The air pressure sensor converts the change in air pressure into an electrical signal. After the electrical signal is amplified, the analog signal is converted into a digital signal through AD conversion, and finally transmitted to the controller via serial communication.

[0174] In some embodiments of the present application, the temperature sensor 4 is a thermistor, which is built into any test piece of the isolated electrode piece 2 to improve the accuracy of temperature monitoring.

[0175] It should be understood that since the island electrode sheet 2 and the defibrillation electrode sheet 1 are located in the same sealed packaging bag, that is, both are in the same environment, and the material of the island electrode sheet 2 is the same as that of the defibrillation electrode sheet 1, the internal temperature of the island electrode sheet 2 can be equivalent to the internal temperature of the defibrillation electrode sheet 1.

[0176] As shown in Figure 5, the island electrode sheet 2 is installed on the humidity sensor 5 and / or the air pressure sensor. An optional solution is to set the humidity sensor 5 and the air pressure sensor adjacent to each other, and the island electrode sheet 2 is installed on the humidity sensor 5 and the air pressure sensor, so that the island electrode sheet 2, the temperature sensor 4, the humidity sensor 5 and the air pressure sensor as a whole are completely independent of the defibrillation electrode sheet 1. The defibrillation electrode sheet 1 is only designed with a defibrillation discharge high-voltage line 13, with fewer connections and a thinner electrode sheet. Moreover, since the defibrillation electrode sheet 1 is not additionally installed with a sensor, the interference during defibrillation operation is small, which effectively improves the defibrillation effect.

[0177] As shown in Figure 5, the external connection terminal 3 is located outside the sealed packaging bag, and the detection line extends from the sealed packaging bag and is connected to the external connection terminal 3. The controller or other host computer connects the defibrillation electrode pad 1 and the island electrode pad 2 through the external connection terminal 3. It should be understood that the "connection" mentioned herein can be a wired connection, such as the various detection lines described above, or a wireless connection. This application imposes special restrictions on the specific implementation method of the connection, as long as it can achieve energy or signal transmission.

[0178] On this basis, the area of ​​the island electrode sheet 2 is smaller than that of the defibrillation electrode sheet 1, which reduces the space occupied by the island electrode sheet 2 and reduces the production cost. The external connection end 3 is located on one side of the sealed packaging bag, and the island electrode sheet 2 is arranged close to the external connection end 3, shortening the length of the detection line between the island electrode sheet 2 and the external connection end 3.

[0179] The present application also proposes a defibrillator device having the above-mentioned defibrillator electrode assembly, wherein the external connection terminal 3 is connected to the controller of the defibrillator device. The controller obtains the temperature, humidity, packaging sealing, and impedance data of the defibrillator electrode 1 in real time through the external connection terminal, and makes a judgment on the effectiveness of the defibrillator electrode 1, and then notifies relevant personnel through networking, voice broadcast or other means.

[0180] Compared with the existing technology, the present application can effectively monitor the status of the defibrillator electrode pads while maintaining the working performance of the defibrillator electrode pads, which not only greatly reduces the cost of manual maintenance and manual monitoring of the defibrillator electrode pads, but also has high monitoring accuracy and good defibrillation effect.

[0181] It should be noted that the terms used above are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0182] At the same time, it should be understood that for ease of description, the dimensions of the various parts shown in the drawings are not drawn according to the actual proportional relationship. Technologies, methods and equipment known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the technologies, methods and equipment should be considered as part of the authorization specification. In all examples shown and discussed here, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that similar numbers and letters represent similar items in the following figures, so once an item is defined in one figure, it does not need to be further discussed in subsequent figures.

[0183] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for estimating the loss of defibrillation electrodes, wherein: The loss estimation method comprises the following steps: S100, setting an environmental container for estimating electrochemical attenuation of gel material, the environmental container being equipped with a humidity sensor and an air pressure sensor for observing humidity and air pressure sequences, and determining to estimate the loss of defibrillator electrode pads using environmental variables and activation energy failure mechanism variables as implicit airtightness-related parameters for estimating electrochemical attenuation of gel material; S200, establishing a hidden Markov model, and using the hidden Markov model to establish a state transition process of hidden air tightness related parameters under the observed humidity and air pressure sequences, wherein the observed values ​​of the humidity and air pressure sequences are used as observation vectors of the hidden Markov chain and defined as a collection of humidity and air pressure observation sequences, and the hidden air tightness related parameters are used as hidden state vectors of the hidden Markov chain and defined as an air tightness hidden state sequence; S300, learning the hidden Markov model, collecting multiple groups of humidity and air pressure observation sequences to adjust the model parameters, wherein the optimal model parameter set obtained under each group of humidity and air pressure observation sequences is used as the determined model parameters; S400, decoding the hidden Markov model and estimating the loss of the defibrillator electrode pads. When using the device, decoding is performed based on the humidity and air pressure observation sequence corresponding to the humidity and air pressure sequence at the previous moment and the determined model parameters to obtain the implicit airtightness related parameters of the current corresponding airtightness hidden state sequence, and the environmental variables and activation energy failure mechanism variables corresponding to the implicit airtightness related parameters are used to estimate the life measurement of the gel material, and finally the estimated current defibrillator electrode pad loss value is obtained and displayed.

2. The defibrillation electrode sheet loss estimation method according to claim 1, wherein: In step S100, the environmental container is also equipped with a temperature sensor for observing temperature values. In step S400, the defibrillation electrode pad loss value is estimated in combination with the temperature value.

3. The defibrillation electrode sheet loss estimation method according to claim 2, wherein: The following reaction formula is used to estimate the life loss of the electrode sheet mainly due to the loss of activation energy of the gel material: In the formula, F represents the chemical reaction rate of the gel material. The life of the defibrillator electrode can be calculated by the inverse of the chemical reaction rate of the gel material, that is, 1 / F; C represents the environmental variable; e represents the natural logarithm base; E represents the activation energy failure mechanism variable; kB is the Boltzmann constant; and M represents the temperature.

4. The defibrillation electrode sheet loss estimation method according to claim 3, wherein: In step S200, the following steps are included: S210, defining each tuple in the hidden Markov model, each tuple includes a humidity and air pressure observation sequence set, a hidden state set, a state probability matrix, a transmission probability matrix, and an initial probability matrix; S220, establishing a hidden Markov model, establishing a hidden Markov model related to the state probability matrix, the emission probability matrix, and the initial probability matrix; S230, performing hidden Markov process representation, where the hidden Markov process representation is the output probability of the humidity and air pressure observation sequence under the hidden Markov model, that is, the joint probability of the humidity and air pressure observation sequence and the airtightness implicit state representation occurring simultaneously under the hidden Markov model.

5. The defibrillation electrode sheet loss estimation method according to claim 4, wherein: In step S200, the following steps are included: S210. Define each tuple in the hidden Markov model: S211, define a humidity and air pressure observation sequence set, and convert the humidity time series sequence and the air pressure time series sequence measured regularly into a humidity and air pressure observation sequence O = [o1, o2, ..., o T ] as the observation vector of the hidden Markov chain and define the humidity and air pressure observation sequence set. T represents the period of time when the humidity sensor and air pressure sensor are started to measure when the equipment is working. The observation values ​​of the measured air pressure and humidity at time t are o t =[pressure t ,humidity t ] T ; S212, define a hidden state set, represent the airtight hidden state as the airtight hidden state sequence Q of the Markov chain, and define the airtight hidden state sequence to be represented as Q = [q1, q2, ..., q T ], then the implicit expression of the airtightness-related parameter at time t in the reaction formula is q t =[C t ,E t ] T ; S213. Define the state probability matrix: The state transition set of the airtight hidden state at different times is expressed as the state probability matrix A, where each element a of the state probability matrix A is ij represents the transition probability from state i to state j; S214, define the emission probability matrix: for the set of possible humidity and air pressure measurement values ​​generated in the airtight hidden state, it is expressed as an emission probability matrix B, where each element b of the emission probability matrix B is qi Represents the hidden state q i The probability of emission to the observed state; S215. Define the initial probability matrix: For the factory airtightness initialization hidden state expression, it is expressed as the initial probability matrix Π, where each element π in the matrix qi represents the hidden state q i The initial probability of , i.e., the factory probability distribution; S220, establish a hidden Markov model, the established hidden Markov model is λ={A,B,∏}; S230, perform hidden Markov process representation, the hidden Markov process representation is the output probability of the humidity and air pressure observation sequence O in the model λ={A,B,∏}, P(O|λ) is the humidity and air pressure observation sequence O and the airtightness hidden state sequence Q=[q1,q2,...,q T ]The joint probability of simultaneous occurrence is as follows: For a fixed hidden state Q = [q1,q2,...,q T ], and obtain the humidity and pressure observation sequence O = [o1, o2, ..., o T The probability of ] is 6. The defibrillation electrode sheet loss estimation method according to claim 5, wherein: In step S300, in learning the hidden Markov model, the following steps are adopted: S310, collect K groups of humidity and pressure observation sequences O = [O 1 ,O 2 ,...,O K ],in represents the kth group of humidity and pressure observation sequence; S320, obtain the kth group of humidity and pressure observation sequence O k The model parameters with the largest value of the joint probability are defined as optimal; S330, using K groups of humidity and pressure observation sequences for training to obtain an optimal parameter set under a given humidity and pressure observation sequence O; S340, by adjusting, the humidity and pressure observation sequence O and the airtightness hidden state sequence Q under the model λ are equal to [q1, q2, ..., q T ]The joint probability of simultaneous occurrence is the largest, and the optimal model parameters obtained under each group of humidity and pressure observation sequences are used as the determined model parameters.

7. The defibrillation electrode loss estimation method according to claim 6, wherein: In step S400, in obtaining the parameters of the airtightness implicit state representation corresponding to the implicit airtightness related parameters, the following steps are adopted: S410, in determining the model parameters, define δ t (i) is a path q1,q2,...,q along a path q1,q2,...,q at time t T Generate o1, o2, ..., o t The maximum probability of S420, initialization δ t (i) = π i b i (o i ); S430, calculate the result of the humidity and pressure observation sequence corresponding to the humidity and pressure sequence at the previous moment on the next path j S440, taking the maximum value in the path of step S430 as the output result: That is, it is the parameter representing the hidden state of the environmental variable C and the activation energy failure mechanism variable E under the influence of airtightness.

8. A defibrillation electrode assembly for intelligently displaying defibrillation electrode loss, wherein: The component comprises an environmental container, a defibrillation electrode sheet, an island electrode sheet, and a detection module. The defibrillation electrode sheet and the island electrode sheet are placed in the environmental container. The detection module comprises a humidity sensor, an air pressure sensor, and a temperature sensor placed in the environmental container. The detection module estimates the loss of the defibrillation electrode sheet according to the defibrillation electrode sheet loss estimation method according to any one of claims 1 to 7 using parameters obtained by the humidity sensor, the air pressure sensor, and the temperature sensor, and displays the estimation result through a display module.

9. The defibrillation electrode pad assembly according to claim 8, wherein: The detection module includes a controller, the humidity sensor is connected to the controller via a data processing module, the temperature sensor series resistor voltage divider module is connected to the controller, and the air pressure sensor is connected to the controller.

10. The defibrillation electrode pad assembly according to claim 9, wherein: The island electrode sheet comprises two test sheets made of the same material as the defibrillation electrode sheet, the defibrillation layers of the two test sheets are aligned and overlapped, and the impedance test points of the two test sheets are connected to the detection module to form an impedance detection loop for accessing direct current.

11. A defibrillator device, wherein: The defibrillation device comprises the defibrillation electrode assembly as claimed in claim 8 and a defibrillator electrically connected to the defibrillation electrode assembly.

12. The defibrillator device according to claim 11, wherein: The display module is arranged on at least one of the detection module, the defibrillator, the rescuer's mobile terminal or the emergency platform terminal.

13. A readable storage medium, wherein: The readable storage medium stores a control program, and when the control program is executed by the detection module, the detection module executes the steps of the method according to any one of claims 1 to 7.

14. A defibrillation electrode assembly, comprising: Two defibrillation electrode pads are located in a sealed packaging bag, and the two defibrillation electrode pads are connected to an external connection terminal through a defibrillation discharge high-voltage line; wherein, it also includes: an island electrode pad for feeding back performance parameters of the defibrillation electrode pads, the island electrode pad is placed in the sealed packaging bag, and the island electrode pad is provided with a detection module, and the detection module is connected to the external connection terminal.

15. The defibrillation electrode pad assembly according to claim 14, wherein: The island electrode sheet comprises two test sheets made of the same material as the defibrillation electrode sheet, and the defibrillation layers of the two test sheets are aligned and overlapped; The detection module comprises: an impedance test point arranged on the defibrillation layer, and the impedance test points of the two test pieces are connected to the external connection end to form an impedance detection loop for accessing alternating current.

16. The defibrillation electrode pad assembly according to claim 15, wherein: The detection module further comprises: a temperature sensor and / or a humidity sensor and / or an air pressure sensor, each of which is respectively connected to the external connection end.

17. The defibrillation electrode pad assembly according to claim 16, wherein: The external connection end is connected to the controller, the humidity sensor is connected to the IIC communication channel of the controller through the data processing module, the temperature sensor is connected in series with a second resistor to the second ADC channel of the controller, the impedance test point is connected in series with an impedance test bridge and an instrument amplifier to the third ADC channel of the controller, and the air pressure sensor is connected to the serial communication channel of the controller; wherein the controller converts the AD value of each ADC channel into a digital signal.

18. The defibrillation electrode pad assembly according to claim 16, wherein: The temperature sensor is a thermistor, and the thermistor is built into any one of the test pieces.

19. The defibrillation electrode pad assembly according to claim 16, wherein: The isolated electrode sheet is mounted on the humidity sensor and / or the air pressure sensor.

20. The defibrillation electrode pad assembly according to any one of claims 14 to 19, wherein: The detection module is connected to the external connection end through a detection line, the external connection end is located outside the sealed packaging bag, and the detection line extends from the sealed packaging bag and is connected to the external connection end.

21. The defibrillation electrode pad assembly according to claim 20, wherein: The area of ​​the isolated electrode sheet is smaller than that of the defibrillation electrode sheet.

22. The defibrillation electrode pad assembly according to claim 21, wherein: The external connection end is located at one side of the sealed packaging bag, and the isolated electrode sheet is arranged close to the external connection end.

23. A defibrillator device, wherein: The defibrillator device comprises the defibrillator electrode pad assembly according to any one of claims 14 to 22.

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