Intelligent drug delivery control method and system based on anesthesia physiological index depth monitoring

Abstract

The invention relates to the technical field of medical health, in particular to an intelligent drug delivery control method and system based on anesthesia physiological index depth monitoring, and the method comprises the steps: obtaining target patient information based on a target patient, obtaining a historical data set, obtaining a target data set based on a data processing unit, the target patient information and the historical data set, the method comprises the following steps: acquiring a first dosage set, acquiring a target dosage based on the first dosage set and a target data set, acquiring a target anesthetic according to the target dosage, and after determining that the target anesthetic is injected to a target patient, monitoring the target patient injected with the target anesthetic based on a monitoring frequency. And obtaining a monitoring index range set and a monitoring stage, determining that the monitoring stage is different from the anesthesia stage, obtaining an updated anesthetic by using the monitoring stage and the monitoring index range set, and realizing intelligent administration of the target patient based on the updated anesthetic. According to the invention, the accuracy and safety of anesthetic dosage control can be improved.

Description

Technical Field

[0001] The present invention relates to the field of medical health technology, and in particular to an intelligent drug administration control method and system based on deep monitoring of anesthesia physiological indicators. Background Art

[0002] In clinical anesthesia, the dosage of anesthetics is related to the patient's life safety and the normal implementation of the operation. Therefore, how to accurately control the dosage of anesthetics is crucial.

[0003] At present, the traditional anesthesia administration method mainly relies on the experience of the anesthesiologist, who subjectively judges the amount of anesthetic required to anesthetize the patient.

[0004] Although the above method can achieve the control of the dosage of anesthetic drugs, it only relies on the subjective judgment of the anesthesiologist, which may cause the problem of inaccurate dosage of anesthetic drugs. Therefore, accurate control of the dosage of anesthetic drugs has become an urgent problem to be solved. Summary of the invention

[0005] The present invention provides an intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators and a computer-readable storage medium, the main purpose of which is to improve the accuracy and safety of controlling the dosage of anesthetic agents.

[0006] To achieve the above-mentioned purpose, the present invention provides an intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators, comprising:

[0007] receiving an intelligent medication instruction, and identifying an intelligent monitoring system and a target patient based on the intelligent medication instruction, wherein the intelligent monitoring system includes a medication sharing unit, a data collection unit, and a data processing unit;

[0008] Acquire target patient information based on the target patient, confirm receipt of a data collection instruction from a data collection unit, acquire a historical data set using the data collection instruction, wherein the historical data set includes a plurality of historical data, acquire a target data set based on the data processing unit, the target patient information and the historical data set, wherein the target data set includes a plurality of target data, wherein the target patient information includes anesthesia stage, target treatment site, target gender, target weight and target age;

[0009] Confirming receipt of a medication sharing instruction from a medication sharing unit, acquiring a first medication dosage set based on the medication sharing instruction and target patient information, wherein the first medication dosage set includes a plurality of first medication dosages, and acquiring a target medication dosage based on the first medication dosage set and a target data set;

[0010] Acquire a target anesthetic drug according to the target dosage, confirm that the target anesthetic drug is injected into the target patient, and then perform a monitoring operation on the target patient after the injection of the target anesthetic drug based on a preset monitoring frequency to obtain a monitoring indicator range set and a monitoring stage;

[0011] Determining whether the monitoring stage is the anesthesia stage;

[0012] If the monitoring stage is different from the anesthesia stage, updated anesthetic drugs are obtained using the monitoring stage and the monitoring indicator range set, and intelligent drug administration to the target patient is achieved based on the updated anesthetic drugs.

[0013] Optionally, acquiring a target data set based on the data processing unit, target patient information and historical data sets includes:

[0014] The following operations are performed on the historical data in the historical data set:

[0015] Acquiring historical information based on the historical data, wherein the historical information includes a reference treatment site, a reference age, a reference gender, a reference weight, a reference stage, an anesthetic dosage, and a set of monitored physiological indicator ranges, wherein the set of monitored physiological indicator ranges includes a blood oxygen saturation range, a heart rate range, a blood pressure range, and a respiratory rate range;

[0016] Performing an identification operation on the historical data using the historical information to obtain identification information, and summarizing the identification information to obtain an identification information set;

[0017] The identification information set is filtered using the target patient information to obtain an initial information set, wherein the initial information set includes a plurality of initial information, and the reference treatment site, reference gender, and reference stage corresponding to the initial information are the same as the target treatment site, target gender, and anesthesia stage of the target patient information;

[0018] A target data set is obtained using the data processing unit and the initial information set.

[0019] Optionally, the acquiring the target data set by using the data processing unit and the initial information set includes:

[0020] The following operations are performed on the initial information in the initial information set:

[0021] The reference assessment value is calculated based on the reference age and reference weight corresponding to the initial information, and the calculation formula is as follows:

[0022] C=αY+βT

[0023] Among them, C represents the reference evaluation value, α and β are preset coefficients, Y represents the reference age, and T represents the reference weight;

[0024] Calculating a target evaluation value using the target age and target weight corresponding to the target patient information, summarizing the reference evaluation values ​​to obtain a reference evaluation value set, constructing a screening relationship using the target evaluation values, and obtaining an updated information set based on the screening relationship and the reference evaluation value set;

[0025] A target data set is acquired according to the update information set and the data processing unit.

[0026] Optionally, the acquiring the update information set based on the screening relational expression and the reference evaluation value set includes:

[0027] The screening relation is as follows:

[0028] S=(γm,δm)

[0029] Wherein, S represents the screening relationship, m represents the target evaluation value, and γ and δ are both preset coefficients;

[0030] The following operations are performed on the reference evaluation values ​​in the reference evaluation value set:

[0031] If the reference evaluation value meets the screening relationship, the initial information corresponding to the reference evaluation value is retained; otherwise, the initial information corresponding to the reference evaluation value is discarded;

[0032] The retained initial information is aggregated to obtain an updated information set.

[0033] Optionally, acquiring a target data set according to the update information set and the data processing unit includes:

[0034] Confirming receipt of a data optimization instruction from a data processing unit, and acquiring a reference physiological indicator range set based on the data optimization instruction, wherein the reference physiological indicator range set includes a reference blood oxygen saturation range, a reference heart rate range, a reference blood pressure range, and a reference respiratory rate range;

[0035] Perform the following operations on the update information in the update information set:

[0036] If it is confirmed that the blood oxygen saturation range, heart rate range, blood pressure range and respiratory rate range in the monitored physiological indicator range set corresponding to the updated information are subsets of the reference blood oxygen saturation range, reference heart rate range, reference blood pressure range and reference respiratory rate range in the reference physiological indicator range set, the updated information is retained; otherwise, the updated information is discarded, the retained updated information is summarized, and the target data set is obtained.

[0037] Optionally, obtaining a reference physiological indicator range set based on the data optimization instruction includes:

[0038] Based on the target patient information and the data optimization instruction, a plurality of initial physiological indicator range sets are identified, wherein the initial physiological indicator range set includes an initial blood oxygen saturation range, an initial heart rate range, an initial blood pressure range, and an initial respiratory rate range;

[0039] The following operations are performed on an initial physiological indicator range set in the multiple initial physiological indicator range sets:

[0040] Mapping the initial blood oxygen saturation range corresponding to the initial physiological indicator range set to a pre-constructed indicator coordinate system to obtain a mapping range, and dividing the mapping range into one or more initial divided ranges according to the number of initial physiological indicator range sets in the multiple initial physiological indicator range sets corresponding to the mapping range;

[0041] The reference extraction value is calculated based on the preset reliability coefficient. The calculation formula is as follows:

[0042] R = τk

[0043] Wherein, R represents the reference extraction value, τ is the reliability coefficient, and k represents a total of k initial physiological index range sets;

[0044] Using the reference extraction value, extract one or more first division ranges from one or more initial division ranges, wherein the number of initial physiological indicator range sets corresponding to the first division ranges is greater than or equal to the reference extraction value;

[0045] Acquire one or more second partition ranges based on the one or more first partition ranges, wherein the second partition range is composed of one or more continuous first partition ranges;

[0046] Obtain a third range value using the one or more second divided ranges, and calculate one or more range ratios based on the one or more second divided ranges and the third range value, wherein the range ratios correspond to the second ranges one-to-one;

[0047] Sorting the range ratios in one or more range ratios in order from large to small to obtain an initial range ratio sequence, and identifying a target range ratio sequence in the initial range ratio sequence using a preset range ratio threshold, wherein the range ratios in the target range ratio sequence are all greater than or equal to the range ratio threshold;

[0048] The reference range ratios are sequentially extracted from the target range ratio sequence, and the following operations are performed on the extracted reference range ratios:

[0049] Based on the reference range ratio, a hysteresis range ratio is identified in the target range ratio sequence, wherein the hysteresis range ratio is a range ratio located adjacent to the reference range ratio in the target range ratio sequence and lags behind the reference range ratio;

[0050] The proportion interval is obtained by using the reference range proportion and the hysteresis range proportion. If the proportion interval is less than or equal to a preset interval threshold, a fitting proportion range is obtained based on the reference range proportion and the hysteresis range proportion, wherein the minimum value and the maximum value corresponding to the fitting proportion range are respectively the minimum value corresponding to the reference range proportion or the minimum value corresponding to the hysteresis range proportion and the maximum value corresponding to the reference range proportion or the maximum value corresponding to the hysteresis range proportion;

[0051] Based on the fitting ratio range, a reference blood oxygen saturation range is obtained, and a reference heart rate range, a reference blood pressure range and a reference respiratory rate range are obtained respectively. The reference blood oxygen saturation range, the reference heart rate range, the reference blood pressure range and the reference respiratory rate range are summarized to obtain a reference physiological indicator range set.

[0052] Optionally, acquiring a first medication dosage set based on the medication sharing instruction and target patient information includes:

[0053] The medication sharing instruction is used to identify multiple data transmission groups, wherein the data transmission group includes a data transmission end and a data receiving end, and an encryption parameter is calculated based on the target patient information, and the calculation formula is as follows:

[0054] J = random{[T f(Y) ]}

[0055] Where J represents the encryption parameter, {} represents taking a prime number, [] represents taking an integer, f(Y) represents the processing function of the target age, and random represents taking a random number;

[0056] The decryption parameters are calculated using the encryption parameters. The calculation formula is as follows:

[0057] X = random {[J T +arctan(J)]}

[0058] Where X represents the decryption parameter;

[0059] Obtaining a public key and a private key according to encryption parameters and decryption parameters, performing encryption operations on target patient information based on the public key, and obtaining encrypted information;

[0060] The following operations are performed on each of the multiple data transmission groups:

[0061] The data transmission end is used to send the encrypted information and the private key to the data receiving end, confirm the reception of the first medication instruction sent back from the data receiving end, parse the first medication instruction, obtain reference parameters, wherein the reference parameters include a reference medication amount and a reference number of surgeries, summarize the reference parameters, obtain a reference parameter set, and calculate the first medication amount set based on the reference parameter set.

[0062] Optionally, the first dosage set is calculated based on the reference parameter set, and the calculation formula is as follows:

[0063]

[0064] Among them, D U represents the Uth first dosage in the first dosage set, I U represents the number of reference surgeries corresponding to the Uth reference parameter in the reference parameter set, S represents the total number of S reference parameters in the reference parameter set, and I Q represents the number of reference surgeries corresponding to the Qth reference parameter in the reference parameter set, H U Represents the reference dosage corresponding to the Uth reference parameter in the reference parameter set.

[0065] Optionally, the target dosage is obtained based on the first dosage set and the target data set, and the calculation formula is as follows:

[0066]

[0067] Wherein, L represents the target dosage, ω is the preset coefficient, r j represents the preset j-th target drug administration coefficient, p j represents the amount of anesthetic agent corresponding to the j-th target data in the target data set, and b represents that there are b target data in the target data set.

[0068] To achieve the above object, the present invention also provides an intelligent drug administration control system based on deep monitoring of anesthesia physiological indicators, comprising:

[0069] An intelligent medication environment confirmation module, used to receive an intelligent medication instruction, and confirm an intelligent monitoring system and a target patient based on the intelligent medication instruction, wherein the intelligent monitoring system includes a medication sharing unit, a data collection unit, and a data processing unit;

[0070] A historical data screening module, used to obtain target patient information based on the target patient, confirm receiving a data collection instruction from a data collection unit, obtain a historical data set using the data collection instruction, wherein the historical data set includes a plurality of historical data, and obtain a target data set based on the data processing unit, the target patient information and the historical data set, wherein the target data set includes a plurality of target data, wherein the target patient information includes anesthesia stage, target treatment site, target gender, target weight and target age;

[0071] a target medication amount acquisition module, configured to confirm receipt of a medication sharing instruction from a medication sharing unit, acquire a first medication amount set based on the medication sharing instruction and target patient information, wherein the first medication amount set includes a plurality of first medication amounts, and acquire a target medication amount based on the first medication amount set and a target data set;

[0072] A patient monitoring module is used to obtain a target anesthetic drug according to the target dosage, confirm that the target anesthetic drug is injected into the target patient, and perform a monitoring operation on the target patient after the injection of the target anesthetic drug based on a preset monitoring frequency to obtain a monitoring indicator range set and a monitoring stage;

[0073] Determining whether the monitoring stage is the anesthesia stage;

[0074] If the monitoring stage is different from the anesthesia stage, updated anesthetic drugs are obtained using the monitoring stage and the monitoring indicator range set, and intelligent drug administration to the target patient is achieved based on the updated anesthetic drugs.

[0075] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0076] A memory storing at least one instruction; and a processor executing the instruction stored in the memory to implement the above-mentioned intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators.

[0077] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators.

[0078] The present invention is to solve the problem described in the background technology. An embodiment of the present invention obtains target patient information based on the target patient, confirms receipt of a data collection instruction from a data collection unit, and uses the data collection instruction to obtain a historical data set, wherein the historical data set includes multiple historical data. A target data set is obtained based on the data processing unit, the target patient information and the historical data set, wherein the target data set includes multiple target data, wherein the target patient information includes anesthesia stage, target treatment site, target gender, target weight and target age. It can be seen that the embodiment of the present invention takes into account the specific information of the target patient, and filters the historical data in the historical data set through the target patient information to obtain the target data set, so that the obtained target data set can more accurately characterize the situation of anesthetic agents required by general patients, thereby improving the accuracy of predicting the amount of anesthetic agents required for the target patient. The embodiment of the present invention confirms receipt of a medication sharing instruction from a medication sharing unit, obtains a first medication dosage set based on the medication sharing instruction and target patient information, wherein the first medication dosage set includes multiple first medication dosages, and obtains a target medication dosage based on the first medication dosage set and the target data set. It can be seen that the embodiment of the present invention not only considers the prediction of the anesthetic medication dosage required for the target patient according to the target data set, but also combines the first medication dosage set to jointly predict the anesthetic medication dosage required for the target patient, and encrypts the target patient information before obtaining the first medication dosage set to ensure that the target patient information will not be tampered with or leaked, thereby improving the accuracy and security of the prediction of the anesthetic medication dosage required for the target patient. The embodiment of the present invention is based on the target medication The target anesthetic drug is obtained by measuring the amount of the target anesthetic drug, and after confirming that the target anesthetic drug is injected into the target patient, a monitoring operation is performed on the target patient after the injection of the target anesthetic drug based on a preset monitoring frequency, and a monitoring indicator range set and a monitoring stage are obtained to determine whether the monitoring stage is the anesthesia stage. If the monitoring stage is different from the anesthesia stage, the updated anesthetic drug is obtained using the monitoring stage and the monitoring indicator range set, and the intelligent administration of the target patient is realized based on the updated anesthetic drug. It can be seen that after the target patient is injected with the target anesthetic drug, the present invention monitors the monitoring indicator range set and the monitoring stage of the target patient, and updates the anesthetic drug dosage required for the target patient through the monitoring indicator range set and the monitoring stage, thereby ensuring the accuracy of the prediction of the anesthetic drug dosage required for the target patient. Therefore, the present invention can improve the accuracy and safety of the control of the anesthetic drug dosage. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 A schematic flow chart of an intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators provided by an embodiment of the present invention;

[0080] Figure 2A functional module diagram of an intelligent drug delivery control system based on deep monitoring of anesthesia physiological indicators provided by an embodiment of the present invention;

[0081] Figure 3 A schematic diagram of the structure of an electronic device for implementing the intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators provided by an embodiment of the present invention.

[0082] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0083] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0084] The embodiment of the present application provides an intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators. The execution subject of the intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0085] Reference Figure 1 FIG. 1 is a flow chart of an intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators provided by an embodiment of the present invention. In this embodiment, the intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators includes:

[0086] S1. Receive an intelligent medication instruction, and identify an intelligent monitoring system and a target patient based on the intelligent medication instruction, wherein the intelligent monitoring system includes a medication sharing unit, a data collection unit, and a data processing unit.

[0087] It should be explained that the intelligent drug administration instruction is an instruction issued by medical staff. The target patient refers to the patient to be anesthetized. The intelligent monitoring system refers to an APP or applet used to control or predict the anesthetic agent required for the target patient, and the intelligent monitoring system includes a drug administration sharing unit, a data collection unit and a data processing unit. For the application of the specific units, please refer to the subsequent embodiments. The embodiment of the present invention is to improve the accuracy of drug administration to patients.

[0088] For example, Xiao Zhang works as an anesthesiologist in a hospital. In order to predict the amount of anesthesia required for patients, Xiao Zhang issues the intelligent medication instruction and confirms the intelligent monitoring system and the target patient.

[0089] S2. Acquire target patient information based on the target patient, confirm receipt of a data collection instruction from a data collection unit, use the data collection instruction to acquire a historical data set, wherein the historical data set includes a plurality of historical data, acquire a target data set based on the data processing unit, the target patient information and the historical data set, wherein the target data set includes a plurality of target data, wherein the target patient information includes anesthesia stage, target treatment site, target gender, target weight and target age.

[0090] Furthermore, the target patient information refers to the information obtained after the attending physician inquires and diagnoses the patient. Historical data refers to the data recorded in major hospitals, and the data includes relevant information of the patient. Therefore, historical information corresponding to the target patient information can be obtained through historical data. The target treatment site refers to the site where the target patient needs to undergo surgery after the attending physician diagnoses the target patient. For example: oral cavity, arm, etc. The target gender refers to the gender of the target patient, the target weight refers to the weight of the target patient, and the target age refers to the age of the target patient. The anesthesia stage refers to the degree of anesthesia that the target patient needs to enter when visiting the doctor. Optionally, the anesthesia stage can be divided into: awake stage, mild anesthesia stage, moderate anesthesia stage and deep anesthesia stage. In actual applications, the anesthesia stage may not only be a specific stage, but also refers to the stage that needs to be maintained during the operation. For example: the wound of the patient needs to be removed. Therefore, in order to ensure the stability of the operation, the patient needs to be maintained in the deep anesthesia stage. However, after the patient is injected with anesthetic drugs, the patient may experience the following stages in sequence: awake stage, light anesthesia stage, moderate anesthesia stage, deep anesthesia stage and awake stage. This anesthesia stage is the deep anesthesia stage.

[0091] It should be explained that the step of obtaining the target data set based on the data processing unit, the target patient information and the historical data set includes:

[0092] The following operations are performed on the historical data in the historical data set:

[0093] Acquiring historical information based on the historical data, wherein the historical information includes a reference treatment site, a reference age, a reference gender, a reference weight, a reference stage, an anesthetic dosage, and a set of monitored physiological indicator ranges, wherein the set of monitored physiological indicator ranges includes a blood oxygen saturation range, a heart rate range, a blood pressure range, and a respiratory rate range;

[0094] Performing an identification operation on the historical data using the historical information to obtain identification information, and summarizing the identification information to obtain an identification information set;

[0095] The identification information set is filtered using the target patient information to obtain an initial information set, wherein the initial information set includes a plurality of initial information, and the reference treatment site, reference gender, and reference stage corresponding to the initial information are the same as the target treatment site, target gender, and anesthesia stage of the target patient information;

[0096] A target data set is obtained using the data processing unit and the initial information set.

[0097] It should be understood that historical information refers to the medical information of the patient corresponding to the historical data. Optionally, the historical information corresponding to the historical data can be obtained by searching in major hospitals. The reference medical site, reference age, reference gender, and reference weight have the same effects as the target medical site, target gender, target weight, and target age, and will not be repeated here.

[0098] It should be explained that blood oxygen saturation refers to the degree of binding of hemoglobin to oxygen in the blood. In the embodiment of the present invention, the range of blood oxygen saturation refers to the range of blood oxygen saturation of the patient during the whole process of surgery. Heart rate refers to the number of heart beats per minute. In the embodiment of the present invention, the heart rate range refers to the range of heart rate of the patient during the whole process of surgery. Blood pressure is the lateral pressure exerted on the blood vessel wall when blood flows in the blood vessel. In the embodiment of the present invention, the blood pressure range refers to the range of blood pressure of the patient during the whole process of surgery. Respiratory rate refers to the number of breaths in a certain period of time, usually refers to the number of breaths per minute. In the embodiment of the present invention, the respiratory rate range refers to the range of respiratory rate of the patient during the whole process of surgery.

[0099] Exemplarily, for ease of understanding, partial historical information is taken as an example: the partial historical information corresponding to the historical data is: arm, 21, female, 60kg, 10ml, wherein arm is the reference treatment site, 21 is the reference age, female is the reference gender, and 10ml is the amount of anesthetic agent used. After using partial historical information to mark the historical data, the identification information obtained is: 1-arm-21-female-60-10.

[0100] It should be explained that the step of obtaining the target data set by using the data processing unit and the initial information set includes:

[0101] The following operations are performed on the initial information in the initial information set:

[0102] The reference assessment value is calculated based on the reference age and reference weight corresponding to the initial information, and the calculation formula is as follows:

[0103] C=αY+βT

[0104] Among them, C represents the reference evaluation value, α and β are preset coefficients, Y represents the reference age, and T represents the reference weight;

[0105] Calculating a target evaluation value using the target age and target weight corresponding to the target patient information, summarizing the reference evaluation values ​​to obtain a reference evaluation value set, constructing a screening relationship using the target evaluation values, and obtaining an updated information set based on the screening relationship and the reference evaluation value set;

[0106] A target data set is acquired according to the update information set and the data processing unit.

[0107] Furthermore, both the target weight and target age will affect the dosage of anesthetic drugs. Therefore, by calculating the reference evaluation value, historical information similar to the target patient's age and weight can be screened out in the initial information set, thereby improving the accuracy of drug administration to the target patient. In addition, by screening the initial information in the initial information set according to the target patient's age and weight, the energy consumption required for screening can be reduced.

[0108] It is understandable that the step of obtaining the update information set based on the screening relationship and the reference evaluation value set includes:

[0109] The screening relation is as follows:

[0110] S=(γm,δm)

[0111] Wherein, S represents the screening relationship, m represents the target evaluation value, and γ and δ are both preset coefficients;

[0112] The following operations are performed on the reference evaluation values ​​in the reference evaluation value set:

[0113] If the reference evaluation value meets the screening relationship, the initial information corresponding to the reference evaluation value is retained; otherwise, the initial information corresponding to the reference evaluation value is discarded;

[0114] The retained initial information is aggregated to obtain an updated information set.

[0115] Furthermore, historical information similar to the weight and age of the target patient can be screened out by screening the relationship, thereby improving the accuracy of drug administration to the target patient.

[0116] It should be understood that the step of obtaining the target data set according to the update information set and the data processing unit includes:

[0117] Confirming receipt of a data optimization instruction from a data processing unit, and acquiring a reference physiological indicator range set based on the data optimization instruction, wherein the reference physiological indicator range set includes a reference blood oxygen saturation range, a reference heart rate range, a reference blood pressure range, and a reference respiratory rate range;

[0118] Perform the following operations on the update information in the update information set:

[0119] If it is confirmed that the blood oxygen saturation range, heart rate range, blood pressure range and respiratory rate range in the monitored physiological indicator range set corresponding to the updated information are subsets of the reference blood oxygen saturation range, reference heart rate range, reference blood pressure range and reference respiratory rate range in the reference physiological indicator range set, the updated information is retained; otherwise, the updated information is discarded, the retained updated information is summarized, and the target data set is obtained.

[0120] It is understandable that if one of the ranges in the monitored physiological indicator range set corresponding to the updated information, including the blood oxygen saturation range, heart rate range, blood pressure range and respiratory rate range, is not a subset of the corresponding range in the reference physiological indicator range set, it indicates that there is an unexpected situation in the operation or the patient's condition is not applicable to general situations. Therefore, the updated information needs to be eliminated to improve the accuracy of the acquired target data set.

[0121] It is understandable that the obtaining of a reference physiological indicator range set based on the data optimization instruction includes:

[0122] Based on the target patient information and the data optimization instruction, a plurality of initial physiological indicator range sets are identified, wherein the initial physiological indicator range set includes an initial blood oxygen saturation range, an initial heart rate range, an initial blood pressure range, and an initial respiratory rate range;

[0123] The following operations are performed on an initial physiological indicator range set in the multiple initial physiological indicator range sets:

[0124] Mapping the initial blood oxygen saturation range corresponding to the initial physiological indicator range set to a pre-constructed indicator coordinate system to obtain a mapping range, and dividing the mapping range into one or more initial divided ranges according to the number of initial physiological indicator range sets in the multiple initial physiological indicator range sets corresponding to the mapping range;

[0125] The reference extraction value is calculated based on the preset reliability coefficient. The calculation formula is as follows:

[0126] R = τk

[0127] Wherein, R represents the reference extraction value, τ is the reliability coefficient, and k represents a total of k initial physiological index range sets;

[0128] Using the reference extraction value, extract one or more first division ranges from one or more initial division ranges, wherein the number of initial physiological indicator range sets corresponding to the first division ranges is greater than or equal to the reference extraction value;

[0129] Acquire one or more second partition ranges based on the one or more first partition ranges, wherein the second partition range is composed of one or more continuous first partition ranges;

[0130] Obtain a third range value using the one or more second divided ranges, and calculate one or more range ratios based on the one or more second divided ranges and the third range value, wherein the range ratios correspond to the second ranges one-to-one;

[0131] Sorting the range ratios in one or more range ratios in order from large to small to obtain an initial range ratio sequence, and identifying a target range ratio sequence in the initial range ratio sequence using a preset range ratio threshold, wherein the range ratios in the target range ratio sequence are all greater than or equal to the range ratio threshold;

[0132] The reference range ratios are sequentially extracted from the target range ratio sequence, and the following operations are performed on the extracted reference range ratios:

[0133] Based on the reference range ratio, a hysteresis range ratio is identified in the target range ratio sequence, wherein the hysteresis range ratio is a range ratio located adjacent to the reference range ratio in the target range ratio sequence and lags behind the reference range ratio;

[0134] The proportion interval is obtained by using the reference range proportion and the hysteresis range proportion. If the proportion interval is less than or equal to a preset interval threshold, a fitting proportion range is obtained based on the reference range proportion and the hysteresis range proportion, wherein the minimum value and the maximum value corresponding to the fitting proportion range are respectively the minimum value corresponding to the reference range proportion or the minimum value corresponding to the hysteresis range proportion and the maximum value corresponding to the reference range proportion or the maximum value corresponding to the hysteresis range proportion;

[0135] Based on the fitting ratio range, a reference blood oxygen saturation range is obtained, and a reference heart rate range, a reference blood pressure range and a reference respiratory rate range are obtained respectively. The reference blood oxygen saturation range, the reference heart rate range, the reference blood pressure range and the reference respiratory rate range are summarized to obtain a reference physiological indicator range set.

[0136] Optionally, the initial physiological indicator range set is obtained by monitoring multiple physiological indicators of patients with similar information to the target patient during the operation to obtain the initial physiological indicator range set. Optionally, a one-dimensional coordinate system is used as the indicator coordinate system. Since each patient has different physical conditions and living habits, different degrees of overlap will be obtained when the initial blood oxygen saturation range is mapped to the indicator coordinate system. In an embodiment of the present invention, the data of the initial physiological indicator range set in multiple initial physiological indicator range sets are used to represent the degree of overlap. Optionally, the reliability coefficient is obtained by statistical means. For example: in the medical field, it is believed that when the probability is above 0.7, the acquired data can represent the overall level, so the reliability coefficient is taken as 0.7.

[0137] Furthermore, when the degree of overlap is greater, it indicates that the range is more universal. Therefore, one or more first division ranges with universal characteristics are extracted from one or more initial division ranges using a reference extraction value. Since the number of initial physiological indicator range sets corresponding to the first division ranges may be different, one or more adjacent first division ranges are connected to obtain a second division range. The third range value refers to the absolute difference between the maximum value corresponding to one or more second division ranges and the minimum value corresponding to one or more second division ranges. The range ratio is obtained by calculating the absolute difference using the minimum value corresponding to the second division range and the maximum value corresponding to the second division range, wherein the range ratio is the ratio of the absolute difference to the third range value.

[0138] It should be understood that the ratio range refers to the interval value between the reference range ratio and the second division range corresponding to the hysteresis range ratio. For example: the reference range ratio is 0.4, the hysteresis range ratio is 0.3, and the second division range corresponding to the reference range ratio is: 95 to 96.5, and the second division range corresponding to the hysteresis range ratio is 97 to 98, then the ratio interval between the reference range ratio and the hysteresis range ratio is 0.5. By comparing the ratio interval with the preset interval threshold, it is possible to determine whether the second division range corresponding to the reference range ratio and the second division range corresponding to the hysteresis range ratio can be fitted as a whole, thereby solving the problem of inaccurate reference blood oxygen saturation range obtained due to accidental circumstances. The methods for obtaining the reference rate range, reference blood pressure range and reference respiratory rate range are the same as the methods for obtaining the reference blood oxygen saturation range, and can achieve the same effects, which will not be repeated here.

[0139] S3. Confirm receipt of a medication sharing instruction from a medication sharing unit, and obtain a first medication dosage set based on the medication sharing instruction and target patient information, wherein the first medication dosage set includes multiple first medication dosages, and obtain a target medication dosage based on the first medication dosage set and the target data set.

[0140] Furthermore, the obtaining of a first medication dosage set based on the medication sharing instruction and the target patient information includes:

[0141] The medication sharing instruction is used to identify multiple data transmission groups, wherein the data transmission group includes a data transmission end and a data receiving end, and an encryption parameter is calculated based on the target patient information, and the calculation formula is as follows:

[0142] J = random{[T f(Y) ]}

[0143] Where J represents the encryption parameter, {} represents taking a prime number, [] represents taking an integer, f(Y) represents the processing function of the target age, and random represents taking a random number;

[0144] The decryption parameters are calculated using the encryption parameters. The calculation formula is as follows:

[0145] X = random {[J T +arctan(J)]}

[0146] Where X represents the decryption parameter;

[0147] Obtaining a public key and a private key according to encryption parameters and decryption parameters, performing encryption operations on target patient information based on the public key, and obtaining encrypted information;

[0148] The following operations are performed on each of the multiple data transmission groups:

[0149] The data transmission end is used to send the encrypted information and the private key to the data receiving end, confirm the reception of the first medication instruction sent back from the data receiving end, parse the first medication instruction, obtain reference parameters, wherein the reference parameters include a reference medication amount and a reference number of surgeries, summarize the reference parameters, obtain a reference parameter set, and calculate the first medication amount set based on the reference parameter set.

[0150] It should be explained that the technology of obtaining the public key and private key using the public key parameters and the private key parameters is an existing technology and will not be described in detail here. The technology of encrypting the target patient information using the public key is an existing technology and will not be described in detail here. Optionally, the sieve of Eratosthenes method is used to obtain prime numbers, and other methods can achieve the same effect, which will not be described in detail here. By encrypting the target patient information, the target patient information can be protected to avoid security issues caused by the target patient information being changed or leaked, thereby improving the accuracy and safety of obtaining the target anesthetic drug. The processing function of the target age refers to a function that converts the target age into days. For example: if the target age of the patient is two years old, the two years old can be processed into 730 days through the processing function of the target age.

[0151] For example, when a hospital obtains the target patient information, it needs the assistance of anesthesiologists in other hospitals to implement the medication for the patient. Therefore, the medical staff of the patient uses the data transmission end in the intelligent monitoring system to send the target disease information to the data receiving end of other hospitals that can receive the target patient information, and encrypts the target patient information before sending it to improve the security of the target patient information when sending it. When the anesthesiologists in other hospitals receive the encrypted information, they use the private key to decrypt the encrypted information and obtain the target patient information. The anesthesiologists diagnose the target patient information and give a reference dosage and reference number of surgeries based on their own experience.

[0152] It is understandable that the reference dosage refers to the dosage of anesthetic given by the anesthesiologist based on the diagnosis of the target patient information and his / her own experience. The reference number of surgeries refers to the number of times the anesthesiologist has successfully performed anesthesia.

[0153] Furthermore, the first dosage set is calculated based on the reference parameter set, and the calculation formula is as follows:

[0154]

[0155] Among them, D U represents the Uth first dosage in the first dosage set, I U represents the number of reference surgeries corresponding to the Uth reference parameter in the reference parameter set, S represents the total number of S reference parameters in the reference parameter set, and I Q represents the number of reference surgeries corresponding to the Qth reference parameter in the reference parameter set, H U Represents the reference dosage corresponding to the Uth reference parameter in the reference parameter set.

[0156] It is understandable that setting the weight value of the reference dosage in combination with the reference number of surgeries can improve the reliability of calculating the first dosage, wherein the weight value is:

[0157] It should be explained that the target dosage is obtained based on the first dosage set and the target data set, and the calculation formula is as follows:

[0158]

[0159] Wherein, L represents the target dosage, ω is the preset coefficient, r j represents the preset j-th target drug administration coefficient, p j represents the amount of anesthetic agent corresponding to the j-th target data in the target data set, and b represents that there are b target data in the target data set.

[0160] It is understandable that the method for obtaining the target dosage refers to both the first dosage set from the medical staff and the target data set from the historical data. Therefore, the obtained target dosage can solve the problem of inaccurate anesthetic dosage caused by insufficient experience of the medical staff.

[0161] S4. Obtaining a target anesthetic drug according to the target dosage.

[0162] It should be explained that the target anesthetic drug refers to an anesthetic drug whose mass or volume is equal to the target dosage.

[0163] S5. After confirming that the target anesthetic drug is injected into the target patient, a monitoring operation is performed on the target patient after the injection of the target anesthetic drug based on a preset monitoring frequency to obtain a monitoring indicator range set and a monitoring stage.

[0164] It is understandable that the monitoring indicator range set and the reference physiological indicator range set have the same effect, which will not be repeated here. The difference between the monitoring indicator range set and the reference physiological indicator range set is that the monitoring indicator range set is the range obtained by real-time monitoring of the target patient after injection of the target anesthetic drug, while the reference physiological indicator range set refers to a collection of known ranges. The monitoring stage has the same effect as the anesthesia stage and can achieve the same effect, which will not be repeated here.

[0165] S6. Determine whether the monitoring stage is the anesthesia stage.

[0166] Optionally, whether the monitoring stage is the anesthesia stage is determined by determining whether the monitoring indicator range set is within the reference physiological indicator range set. If the monitoring indicator range set is within the reference physiological indicator range set, it indicates that the monitoring stage is the anesthesia stage.

[0167] S7. If the monitoring stage is different from the anesthesia stage, the updated anesthetic drug is obtained by using the monitoring stage and the monitoring indicator range set, and intelligent drug administration to the target patient is achieved based on the updated anesthetic drug.

[0168] It is understandable that before using the monitoring stage and the monitoring indicator range set to obtain updated anesthetic drugs, the remaining indicator range sets corresponding to the remaining anesthesia stages can also be obtained respectively, where the remaining anesthesia stages include: awake stage, light anesthesia stage, moderate anesthesia stage or deep anesthesia stage. The method of obtaining the remaining indicator parameter sets is the same as the method of obtaining the reference physiological indicator range set, and can achieve the same effect, which will not be repeated here.

[0169] Furthermore, after confirming the current anesthesia stage of the target patient through the monitoring indicator range set and the remaining indicator range sets, updated anesthetic drugs are obtained based on the current anesthesia stage, the anesthesia stage to be maintained and the monitoring indicator range set, wherein the current anesthesia stage is a mild anesthesia stage, a moderate anesthesia stage or a deep anesthesia stage, and the method of obtaining updated anesthetic drugs is the same as the method of obtaining the target anesthetic drugs, and can achieve the same effect, which will not be repeated here.

[0170] The present invention is to solve the problem described in the background technology. An embodiment of the present invention obtains target patient information based on the target patient, confirms receipt of a data collection instruction from a data collection unit, and uses the data collection instruction to obtain a historical data set, wherein the historical data set includes multiple historical data. A target data set is obtained based on the data processing unit, the target patient information and the historical data set, wherein the target data set includes multiple target data, wherein the target patient information includes anesthesia stage, target treatment site, target gender, target weight and target age. It can be seen that the embodiment of the present invention takes into account the specific information of the target patient, and filters the historical data in the historical data set through the target patient information to obtain the target data set, so that the obtained target data set can more accurately characterize the situation of anesthetic agents required by general patients, thereby improving the accuracy of predicting the amount of anesthetic agents required for the target patient. The embodiment of the present invention confirms receipt of a medication sharing instruction from a medication sharing unit, obtains a first medication dosage set based on the medication sharing instruction and target patient information, wherein the first medication dosage set includes multiple first medication dosages, and obtains a target medication dosage based on the first medication dosage set and the target data set. It can be seen that the embodiment of the present invention not only considers the prediction of the anesthetic medication dosage required for the target patient according to the target data set, but also combines the first medication dosage set to jointly predict the anesthetic medication dosage required for the target patient, and encrypts the target patient information before obtaining the first medication dosage set to ensure that the target patient information will not be tampered with or leaked, thereby improving the accuracy and security of the prediction of the anesthetic medication dosage required for the target patient. The embodiment of the present invention is based on the target medication The target anesthetic drug is obtained by measuring the amount of the target anesthetic drug, and after confirming that the target anesthetic drug is injected into the target patient, a monitoring operation is performed on the target patient after the injection of the target anesthetic drug based on a preset monitoring frequency, and a monitoring indicator range set and a monitoring stage are obtained to determine whether the monitoring stage is the anesthesia stage. If the monitoring stage is different from the anesthesia stage, the updated anesthetic drug is obtained using the monitoring stage and the monitoring indicator range set, and the intelligent administration of the target patient is realized based on the updated anesthetic drug. It can be seen that after the target patient is injected with the target anesthetic drug, the present invention monitors the monitoring indicator range set and the monitoring stage of the target patient, and updates the anesthetic drug dosage required for the target patient through the monitoring indicator range set and the monitoring stage, thereby ensuring the accuracy of the prediction of the anesthetic drug dosage required for the target patient. Therefore, the present invention can improve the accuracy and safety of the control of the anesthetic drug dosage.

[0171] like Figure 2 , which is a functional module diagram of an intelligent drug administration control system based on deep monitoring of anesthesia physiological indicators provided by an embodiment of the present invention.

[0172] The intelligent drug delivery control system 100 based on the deep monitoring of anesthesia physiological indicators of the present invention can be installed in an electronic device. According to the functions implemented, the intelligent drug delivery control system 100 based on the deep monitoring of anesthesia physiological indicators can include an intelligent drug delivery environment confirmation module 101, a historical data screening module 102, a target drug delivery acquisition module 103 and a patient monitoring module 104. The module of the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0173] The intelligent medication environment confirmation module 101 is used to receive an intelligent medication instruction, and confirm an intelligent monitoring system and a target patient based on the intelligent medication instruction, wherein the intelligent monitoring system includes a medication sharing unit, a data collection unit, and a data processing unit;

[0174] The historical data screening module 102 is used to obtain target patient information based on the target patient, confirm receiving a data collection instruction from a data collection unit, obtain a historical data set using the data collection instruction, wherein the historical data set includes a plurality of historical data, and obtain a target data set based on the data processing unit, the target patient information and the historical data set, wherein the target data set includes a plurality of target data, wherein the target patient information includes anesthesia stage, target treatment site, target gender, target weight and target age;

[0175] The target medication amount acquisition module 103 is used to confirm the receipt of the medication sharing instruction from the medication sharing unit, acquire a first medication amount set based on the medication sharing instruction and target patient information, wherein the first medication amount set includes a plurality of first medication amounts, and acquire the target medication amount based on the first medication amount set and the target data set;

[0176] The patient monitoring module 104 is used to obtain the target anesthetic drug according to the target dosage, confirm that the target anesthetic drug is injected into the target patient, and perform a monitoring operation on the target patient after the injection of the target anesthetic drug based on a preset monitoring frequency to obtain a monitoring indicator range set and a monitoring stage;

[0177] Determining whether the monitoring stage is the anesthesia stage;

[0178] If the monitoring stage is different from the anesthesia stage, updated anesthetic drugs are obtained using the monitoring stage and the monitoring indicator range set, and intelligent drug administration to the target patient is achieved based on the updated anesthetic drugs.

[0179] In detail, each module in the intelligent drug administration control system 100 based on the depth monitoring of anesthesia physiological indicators in the embodiment of the present invention is used in the same manner as described above. Figure 1The intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators described in the present invention has the same technical means and can produce the same technical effects, so it will not be repeated here.

[0180] like Figure 3 , which is a schematic diagram of the structure of an electronic device for implementing an intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators provided by an embodiment of the present invention.

[0181] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as an intelligent drug administration control method program based on depth monitoring of anesthesia physiological indicators.

[0182] Wherein, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. The memory 11 may be an internal storage unit of the electronic device 1 in some embodiments, such as a mobile hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 1. Further, the memory 11 also includes an internal storage unit of the electronic device 1 and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the intelligent drug administration control method program based on the depth monitoring of anesthesia physiological indicators, but also can be used to temporarily store data that has been output or is to be output.

[0183] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (such as an intelligent drug administration control method program based on depth monitoring of anesthesia physiological indicators, etc.), and calls data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

[0184] The bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 may be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0185] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0186] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management system, so that the power management system can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0187] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0188] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0189] The intelligent drug administration control method program based on the depth monitoring of anesthesia physiological indicators stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0190] receiving an intelligent medication instruction, and identifying an intelligent monitoring system and a target patient based on the intelligent medication instruction, wherein the intelligent monitoring system includes a medication sharing unit, a data collection unit, and a data processing unit;

[0191] Acquire target patient information based on the target patient, confirm receipt of a data collection instruction from a data collection unit, acquire a historical data set using the data collection instruction, wherein the historical data set includes a plurality of historical data, acquire a target data set based on the data processing unit, the target patient information and the historical data set, wherein the target data set includes a plurality of target data, wherein the target patient information includes anesthesia stage, target treatment site, target gender, target weight and target age;

[0192] Confirming receipt of a medication sharing instruction from a medication sharing unit, acquiring a first medication dosage set based on the medication sharing instruction and target patient information, wherein the first medication dosage set includes a plurality of first medication dosages, and acquiring a target medication dosage based on the first medication dosage set and a target data set;

[0193] Acquire a target anesthetic drug according to the target dosage, confirm that the target anesthetic drug is injected into the target patient, and then perform a monitoring operation on the target patient after the injection of the target anesthetic drug based on a preset monitoring frequency to obtain a monitoring indicator range set and a monitoring stage;

[0194] Determining whether the monitoring stage is the anesthesia stage;

[0195] If the monitoring stage is different from the anesthesia stage, updated anesthetic drugs are obtained using the monitoring stage and the monitoring indicator range set, and intelligent drug administration to the target patient is achieved based on the updated anesthetic drugs.

[0196] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0197] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or system that can carry the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0198] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0199] receiving an intelligent medication instruction, and identifying an intelligent monitoring system and a target patient based on the intelligent medication instruction, wherein the intelligent monitoring system includes a medication sharing unit, a data collection unit, and a data processing unit;

[0200] Acquire target patient information based on the target patient, confirm receipt of a data collection instruction from a data collection unit, acquire a historical data set using the data collection instruction, wherein the historical data set includes a plurality of historical data, acquire a target data set based on the data processing unit, the target patient information and the historical data set, wherein the target data set includes a plurality of target data, wherein the target patient information includes anesthesia stage, target treatment site, target gender, target weight and target age;

[0201] Confirming receipt of a medication sharing instruction from a medication sharing unit, acquiring a first medication dosage set based on the medication sharing instruction and target patient information, wherein the first medication dosage set includes a plurality of first medication dosages, and acquiring a target medication dosage based on the first medication dosage set and a target data set;

[0202] Acquire a target anesthetic drug according to the target dosage, confirm that the target anesthetic drug is injected into the target patient, and then perform a monitoring operation on the target patient after the injection of the target anesthetic drug based on a preset monitoring frequency to obtain a monitoring indicator range set and a monitoring stage;

[0203] Determining whether the monitoring stage is the anesthesia stage;

[0204] If the monitoring stage is different from the anesthesia stage, updated anesthetic drugs are obtained using the monitoring stage and the monitoring indicator range set, and intelligent drug administration to the target patient is achieved based on the updated anesthetic drugs.

[0205] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only illustrative, and actual implementation may have other division methods.

[0206] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0207] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0208] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0209] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators, characterized in that: The method comprises: receiving an intelligent medication instruction, and identifying an intelligent monitoring system and a target patient based on the intelligent medication instruction, wherein the intelligent monitoring system includes a medication sharing unit, a data collection unit, and a data processing unit; Acquire target patient information based on the target patient, confirm receipt of a data collection instruction from a data collection unit, acquire a historical data set using the data collection instruction, wherein the historical data set includes a plurality of historical data, acquire a target data set based on the data processing unit, the target patient information and the historical data set, wherein the target data set includes a plurality of target data, wherein the target patient information includes anesthesia stage, target treatment site, target gender, target weight and target age; Confirming receipt of a medication sharing instruction from a medication sharing unit, acquiring a first medication dosage set based on the medication sharing instruction and target patient information, wherein the first medication dosage set includes a plurality of first medication dosages, and acquiring a target medication dosage based on the first medication dosage set and a target data set; Acquire a target anesthetic drug according to the target dosage, confirm that the target anesthetic drug is injected into the target patient, and then perform a monitoring operation on the target patient after the injection of the target anesthetic drug based on a preset monitoring frequency to obtain a monitoring indicator range set and a monitoring stage; Determining whether the monitoring stage is the anesthesia stage; If the monitoring stage is different from the anesthesia stage, updated anesthetic drugs are obtained using the monitoring stage and the monitoring indicator range set, and intelligent drug administration to the target patient is achieved based on the updated anesthetic drugs.

2. The intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators according to claim 1, characterized in that: The step of acquiring a target data set based on the data processing unit, target patient information and historical data sets includes: The following operations are performed on the historical data in the historical data set: Acquiring historical information based on the historical data, wherein the historical information includes a reference treatment site, a reference age, a reference gender, a reference weight, a reference stage, an anesthetic dosage, and a set of monitored physiological indicator ranges, wherein the set of monitored physiological indicator ranges includes a blood oxygen saturation range, a heart rate range, a blood pressure range, and a respiratory rate range; Performing an identification operation on the historical data using the historical information to obtain identification information, and summarizing the identification information to obtain an identification information set; The identification information set is filtered using the target patient information to obtain an initial information set, wherein the initial information set includes a plurality of initial information, and the reference treatment site, reference gender, and reference stage corresponding to the initial information are the same as the target treatment site, target gender, and anesthesia stage of the target patient information; A target data set is obtained using the data processing unit and the initial information set.

3. The intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators as claimed in claim 2, characterized in that: The method of obtaining a target data set by using a data processing unit and an initial information set includes: The following operations are performed on the initial information in the initial information set: The reference assessment value is calculated based on the reference age and reference weight corresponding to the initial information, and the calculation formula is as follows: C=αY+βT Among them, C represents the reference evaluation value, α and β are preset coefficients, Y represents the reference age, and T represents the reference weight; Calculating a target evaluation value using the target age and target weight corresponding to the target patient information, summarizing the reference evaluation values ​​to obtain a reference evaluation value set, constructing a screening relationship using the target evaluation values, and obtaining an updated information set based on the screening relationship and the reference evaluation value set; A target data set is acquired according to the update information set and the data processing unit.

4. The intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators as claimed in claim 3, characterized in that: The step of obtaining an update information set based on the screening relationship and the reference evaluation value set includes: The screening relation is as follows: S=(γm,δm) Wherein, S represents the screening relationship, m represents the target evaluation value, and γ and δ are both preset coefficients; The following operations are performed on the reference evaluation values ​​in the reference evaluation value set: If the reference evaluation value meets the screening relationship, the initial information corresponding to the reference evaluation value is retained; otherwise, the initial information corresponding to the reference evaluation value is discarded; The retained initial information is aggregated to obtain an updated information set.

5. The intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators according to claim 4, characterized in that: The step of obtaining a target data set according to the update information set and the data processing unit includes: Confirming receipt of a data optimization instruction from a data processing unit, and acquiring a reference physiological indicator range set based on the data optimization instruction, wherein the reference physiological indicator range set includes a reference blood oxygen saturation range, a reference heart rate range, a reference blood pressure range, and a reference respiratory rate range; Perform the following operations on the update information in the update information set: If it is confirmed that the blood oxygen saturation range, heart rate range, blood pressure range and respiratory rate range in the monitored physiological indicator range set corresponding to the updated information are subsets of the reference blood oxygen saturation range, reference heart rate range, reference blood pressure range and reference respiratory rate range in the reference physiological indicator range set, the updated information is retained; otherwise, the updated information is discarded, the retained updated information is summarized, and the target data set is obtained.

6. The intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators according to claim 5, characterized in that: The step of obtaining a reference physiological indicator range set based on the data optimization instruction includes: Based on the target patient information and the data optimization instruction, a plurality of initial physiological indicator range sets are identified, wherein the initial physiological indicator range set includes an initial blood oxygen saturation range, an initial heart rate range, an initial blood pressure range, and an initial respiratory rate range; The following operations are performed on an initial physiological indicator range set in the multiple initial physiological indicator range sets: Mapping the initial blood oxygen saturation range corresponding to the initial physiological indicator range set to a pre-constructed indicator coordinate system to obtain a mapping range, and dividing the mapping range into one or more initial divided ranges according to the number of initial physiological indicator range sets in the multiple initial physiological indicator range sets corresponding to the mapping range; The reference extraction value is calculated based on the preset reliability coefficient. The calculation formula is as follows: R = τk Wherein, R represents the reference extraction value, τ is the reliability coefficient, and k represents a total of k initial physiological index range sets; Using the reference extraction value, extract one or more first division ranges from one or more initial division ranges, wherein the number of initial physiological indicator range sets corresponding to the first division ranges is greater than or equal to the reference extraction value; Acquire one or more second partition ranges based on the one or more first partition ranges, wherein the second partition range is composed of one or more continuous first partition ranges; Obtain a third range value using the one or more second divided ranges, and calculate one or more range ratios based on the one or more second divided ranges and the third range value, wherein the range ratios correspond to the second ranges one-to-one; Sorting the range ratios in one or more range ratios in order from large to small to obtain an initial range ratio sequence, and identifying a target range ratio sequence in the initial range ratio sequence using a preset range ratio threshold, wherein the range ratios in the target range ratio sequence are all greater than or equal to the range ratio threshold; The reference range ratios are sequentially extracted from the target range ratio sequence, and the following operations are performed on the extracted reference range ratios: Based on the reference range ratio, a hysteresis range ratio is identified in the target range ratio sequence, wherein the hysteresis range ratio is a range ratio located adjacent to the reference range ratio in the target range ratio sequence and lags behind the reference range ratio; The proportion interval is obtained by using the reference range proportion and the hysteresis range proportion. If the proportion interval is less than or equal to a preset interval threshold, a fitting proportion range is obtained based on the reference range proportion and the hysteresis range proportion, wherein the minimum value and the maximum value corresponding to the fitting proportion range are respectively the minimum value corresponding to the reference range proportion or the minimum value corresponding to the hysteresis range proportion and the maximum value corresponding to the reference range proportion or the maximum value corresponding to the hysteresis range proportion; Based on the fitting ratio range, a reference blood oxygen saturation range is obtained, and a reference heart rate range, a reference blood pressure range and a reference respiratory rate range are obtained respectively. The reference blood oxygen saturation range, the reference heart rate range, the reference blood pressure range and the reference respiratory rate range are summarized to obtain a reference physiological indicator range set.

7. The intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators according to claim 6, characterized in that: The obtaining of a first medication dosage set based on the medication sharing instruction and the target patient information includes: The medication sharing instruction is used to identify multiple data transmission groups, wherein the data transmission group includes a data transmission end and a data receiving end, and an encryption parameter is calculated based on the target patient information, and the calculation formula is as follows: J=random{[T f(Y) ]} Where J represents the encryption parameter, {} represents taking a prime number, [] represents taking an integer, f(Y) represents the processing function of the target age, and random represents taking a random number; The decryption parameters are calculated using the encryption parameters. The calculation formula is as follows: X=random{[J T +arctan(J)]} Where X represents the decryption parameter; Obtaining a public key and a private key according to encryption parameters and decryption parameters, performing encryption operations on target patient information based on the public key, and obtaining encrypted information; The following operations are performed on each of the multiple data transmission groups: The data transmission end is used to send the encrypted information and the private key to the data receiving end, confirm the reception of the first medication instruction sent back from the data receiving end, parse the first medication instruction, obtain reference parameters, wherein the reference parameters include a reference medication amount and a reference number of surgeries, summarize the reference parameters, obtain a reference parameter set, and calculate the first medication amount set based on the reference parameter set.

8. The intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators according to claim 7, characterized in that: The first dosage set is calculated based on the reference parameter set, and the calculation formula is as follows: Among them, D U represents the Uth first dosage in the first dosage set, I U represents the number of reference surgeries corresponding to the Uth reference parameter in the reference parameter set, S represents the total number of S reference parameters in the reference parameter set, and I Q represents the number of reference surgeries corresponding to the Qth reference parameter in the reference parameter set, H U Represents the reference dosage corresponding to the Uth reference parameter in the reference parameter set.

9. The intelligent drug administration control method based on deep monitoring of anesthesia physiological indicators according to claim 8, characterized in that: The target dosage is obtained based on the first dosage set and the target data set, and the calculation formula is as follows: Wherein, L represents the target dosage, ω is the preset coefficient, r j represents the preset j-th target drug administration coefficient, p j represents the amount of anesthetic agent corresponding to the j-th target data in the target data set, and b represents that there are b target data in the target data set.

10. An intelligent drug delivery control system based on deep monitoring of anesthesia physiological indicators, characterized in that: The system comprises: An intelligent medication environment confirmation module, used to receive an intelligent medication instruction, and confirm an intelligent monitoring system and a target patient based on the intelligent medication instruction, wherein the intelligent monitoring system includes a medication sharing unit, a data collection unit, and a data processing unit; A historical data screening module, used to obtain target patient information based on the target patient, confirm receiving a data collection instruction from a data collection unit, obtain a historical data set using the data collection instruction, wherein the historical data set includes a plurality of historical data, and obtain a target data set based on the data processing unit, the target patient information and the historical data set, wherein the target data set includes a plurality of target data, wherein the target patient information includes anesthesia stage, target treatment site, target gender, target weight and target age; a target medication amount acquisition module, configured to confirm receipt of a medication sharing instruction from a medication sharing unit, acquire a first medication amount set based on the medication sharing instruction and target patient information, wherein the first medication amount set includes a plurality of first medication amounts, and acquire a target medication amount based on the first medication amount set and a target data set; A patient monitoring module is used to obtain a target anesthetic drug according to the target dosage, confirm that the target anesthetic drug is injected into the target patient, and perform a monitoring operation on the target patient after the injection of the target anesthetic drug based on a preset monitoring frequency to obtain a monitoring indicator range set and a monitoring stage; Determining whether the monitoring stage is the anesthesia stage; If the monitoring stage is different from the anesthesia stage, updated anesthetic drugs are obtained using the monitoring stage and the monitoring indicator range set, and intelligent drug administration to the target patient is achieved based on the updated anesthetic drugs.

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