Optimized management method and device for hypertension medication, medium and equipment

Abstract

The invention discloses an optimal management method and device for hypertension medication, a medium and equipment. The method comprises the following steps: acquiring initial medication data of a target object for a target blood pressure drug; collecting and analyzing physiological data of the target object in a preset time range, and generating a physiological cycle curve of the target object; adjusting a blood pressure reference curve based on the physiological cycle curve to generate a blood pressure change target curve of the target object; and optimizing the initial medication data according to a blood pressure change target curve to generate a medication optimization scheme. According to the method, the actual blood pressure state of regular change of the patient is measured according to the physiological data change condition of the patient within a certain time range, so that the actual blood pressure state serves as supplement of sphygmomanometer measurement data, when 24-hour sphygmomanometer monitoring data of the patient is difficult to obtain, targeted medicine taking suggestions can be provided for the patient, the medicine taking accuracy of the patient is improved, and the patient experience is improved. And the hypertension management individuation level of the patient is improved.

Description

Technical Field

[0001] The present invention relates to the field of health management, and particularly to an optimized management method, device, medium and equipment for hypertension medication. Background Art

[0002] Blood pressure is one of the four vital signs of the human body, and hypertension is the most common chronic non-communicable disease in humans and one of the causative factors of other chronic diseases. The main means of hypertension treatment is drug treatment, so as to keep the blood pressure of hypertensive patients at the antihypertensive standard level for a long time.

[0003] At present, there are blood pressure control drugs with different release durations. Some blood pressure control drugs can be taken once a day, and some need to be taken 2-3 times a day. When doctors issue medical orders, they usually only tell patients the daily dosage and the dosage per administration of the drug, and recommend a relatively broad time for taking the drug, such as after getting up, after meals, etc. However, there are significant differences in the daily work and rest time and activity status of different patients. Some people go to bed early and get up early, while some go to bed late and get up early. At the same time, different activity states will also cause significant differences in the peak and trough times of each person's blood pressure. A suitable medication time is required to achieve better blood pressure control. However, most patients are difficult to carry devices such as blood pressure monitors with them 24 hours a day to monitor their own blood pressure, so it is difficult to understand their daily blood pressure changes and difficult to obtain more targeted medication advice to make the drug produce better therapeutic effects. Summary of the Invention

[0004] The present invention provides an optimized management method, device, medium and equipment for hypertension medication, which solves the above-mentioned technical problems.

[0005] The first aspect of the embodiment of the present invention provides an optimized management method for hypertension medication, including the following steps:

[0006] Step 1, obtaining the initial medication data of the target object for the target blood pressure drug;

[0007] Step 2, collecting and analyzing the physiological data of the target object in a preset time range, and generating a physiological cycle curve of the target object;

[0008] Step 3, obtaining the blood pressure reference curve of the target object, and adjusting the blood pressure reference curve based on the physiological cycle curve to generate a target blood pressure change curve of the target object;

[0009] Step 4, optimizing the initial medication data according to the target blood pressure change curve to generate a medication optimization plan.

[0010] In a second aspect of the embodiments of the present invention, there is provided a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned optimized management method for hypertension medications.

[0011] In a third aspect of the embodiments of the present invention, there is provided an optimized management device for hypertension medications, including a computer-readable storage medium and a processor, and when the processor executes the computer program on the computer-readable storage medium, the steps of the above-mentioned optimized management method for hypertension medications are implemented.

[0012] In a fourth aspect of the embodiments of the present invention, there is provided an optimized management device for hypertension medications, including an acquisition module, an analysis module, an adjustment module, and a scheme generation module.

[0013] The acquisition module is used to acquire the initial medication data of the target object for the target blood pressure medication.

[0014] The analysis module is used to collect and analyze the physiological data of the target object within a preset time range and generate a physiological cycle curve of the target object.

[0015] The adjustment module is used to acquire the blood pressure reference curve of the target object and adjust the blood pressure reference curve based on the physiological cycle curve to generate a target blood pressure change curve of the target object.

[0016] The scheme generation module is used to optimize the initial medication data according to the target blood pressure change curve and generate a medication optimization scheme.

[0017] The beneficial effects of the present invention are as follows: The present invention provides an optimized management method, device, medium, and equipment for hypertension medications, which measure the actual blood pressure state that changes regularly of the patient according to the change of the patient's physiological data within a certain time range, so as to supplement the measurement data of the sphygmomanometer. When it is difficult to obtain the 24-hour sphygmomanometer monitoring data of the patient, targeted medication suggestions can also be provided for the patient, promoting the accuracy of the patient's medication and improving the personalized level of the patient's hypertension management.

[0018] To make the above-mentioned objects, features, and advantages of the invention more obvious and understandable, the following specifically lists the preferred embodiments of the present invention and, in conjunction with the accompanying drawings, makes a detailed description as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the embodiments. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 It is a schematic flowchart of the optimized management method for hypertension medications provided in Embodiment 1;

[0021] Figure 2 It is a schematic structural diagram of the optimized management device for hypertension medications provided in Embodiment 2;

[0022] Figure 3 It is a schematic structural diagram of the optimized management equipment for hypertension medications provided in Embodiment 3. Detailed implementation manners

[0023] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. 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. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0024] It should be noted that if there is no conflict, the various features in the embodiments of the present invention can be combined with each other, and all are within the scope of protection of the present invention. In addition, although the functional modules are divided in the device schematic diagram and the logical sequence is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from the module division in the device or the sequence in the flowchart. Furthermore, the terms "first", "second", "third", etc. used in the present invention do not limit the data and execution order, but only distinguish the same items or similar items with basically the same functions and effects.

[0025] Figure 1 It is a schematic flowchart of an optimized management method for hypertension medications provided in Embodiment 1. As Figure 1 shown, it includes the following steps:

[0026] Step 1, obtain the initial medication data of the target object for the target blood pressure medication;

[0027] Step 2, collect and analyze the physiological data of the target object within a preset time range, and generate a physiological cycle curve of the target object;

[0028] Step 3, obtain the blood pressure reference curve of the target object, and adjust the blood pressure reference curve based on the physiological cycle curve to generate a target blood pressure change curve of the target object;

[0029] Step 4, optimize the initial medication data according to the target blood pressure change curve to generate a medication optimization plan.

[0030] The above embodiments provide an optimized management method for hypertension medications. By measuring the actual blood pressure status that regularly changes based on the physiological data changes of a patient within a certain time range, it serves as a supplement to the measurement data of a sphygmomanometer. When it is difficult to obtain the 24-hour sphygmomanometer monitoring data of a patient, targeted medication advice can also be provided to the patient, promoting the accuracy of medication use and improving the personalized level of hypertension management for the patient.

[0031] The following uses specific embodiments to elaborate on each step of the above method in detail.

[0032] Exemplarily, in one embodiment, the initial medication data includes at least one initial medication time period, such as after breakfast or after getting up, which can be obtained according to the drug usage instructions or a doctor's prescription. The corresponding medication optimization plan includes at least one more specific target medication time period after improvement, such as between 8:00 - 8:30, to improve the blood pressure control effect. It can be understood that in another embodiment, the initial medication dose can also be collected as the initial medication data through the drug usage instructions or a doctor's prescription. At this time, the medication optimization plan can also include the target medication dose for each target medication time period. Specifically, the target medication dose for each target medication time period can be the same, or a targeted medication dose can be adopted according to the blood pressure fluctuation amplitude of each target medication time period. For example, the greater the blood pressure fluctuation amplitude, the larger the proportion of the medication dose in that target medication time period, but the total daily medication dose remains unchanged.

[0033] It can be understood that the daily blood pressure change status of hypertension patients usually follows a certain physiological pattern. Most people's blood pressure has two obvious peak time periods in a day. The first peak is usually between 6 am and 10 am, and the second peak is between 4 pm and 8 pm. At night, especially from 0 am to 4 am, the blood pressure drops to the lowest point of the day, showing a blood pressure change curve of "two peaks and one valley". However, there are also some hypertension patients, especially elderly patients or those with combined cardiovascular and cerebrovascular diseases, who may have abnormal change curves. Even for the normal "two peaks and one valley" curve, it will change with different physiological states throughout the day, such as changes in the exercise state, causing the peaks and valleys to appear at different times or changing the peak and valley blood pressure values of the peaks and valleys, thus affecting the efficacy of hypertension medications. Therefore, collect and analyze the physiological data of the target object within a preset time range, such as a relatively long period of 3 months or half a year. When it is determined through this physiological data that the physiological state changes of the patient are regular, generate the physiological cycle curve and the actual blood pressure change curve of the patient.

[0034] Exemplarily, in one specific embodiment, collecting and analyzing the physiological data of the target object within a preset time range and generating the physiological cycle curve of the target object is specifically as follows:

[0035] S201: Divide 24 hours into a preset number of measurement cycles, and continuously collect the physiological data of the target object in each measurement cycle within a preset time range. For example, each 2 - 4 hours is a measurement cycle.

[0036] S202: Determine the physiological state of the target object corresponding to each measurement cycle according to the physiological data. The physiological data includes calorie consumption, average heart rate, number of exercise steps, and / or exercise distance. The categories of the physiological state include sleep state, sedentary state, light exercise state, moderate exercise state, high - intensity exercise state, etc. The specific method of judging the user state according to physiological data has cases in the related field and will not be elaborated here.

[0037] S203: Calculate the average similarity of the physiological states within the preset time range. If the average similarity is greater than the first preset threshold, execute S204; otherwise, stop the optimization management method and keep the initial medication data unchanged. It can be understood that first, obtain the target physiological state with the most repetitions in the same measurement cycle within the preset time range and the target repetition times of this target physiological state. Then, calculate the similarity of any measurement cycle as the ratio of the target repetition times to the upper limit of the corresponding repetition times within the preset time range. For example, if the preset time range is 60 days, and within these 60 days, the target user is in the sleep state 58 times and in the sedentary state 2 times between 12:00 and 03:00, then it can be determined that the target physiological state between 12:00 and 03:00 is the sleep state, the target repetition times is 58, the upper limit of the repetition times is 60, and the similarity corresponding to this measurement cycle is 58 / 60. Repeat the above steps to calculate the similarity of each measurement cycle, so as to obtain the average similarity of all measurement cycles within the preset time range. If the average similarity is greater than the first preset threshold, it means that the user is a target user with a regular life. At this time, execute step 204, obtain the target physiological state of each measurement cycle within the preset time range, and generate a physiological cycle curve showing the continuous change of the target object within 24 hours.

[0038] In a specific embodiment, step 2 may further include: judging the similarity of the physiological data corresponding to adjacent measurement cycles. When the similarity is greater than the second preset threshold, merge the adjacent measurement cycles and the corresponding physiological data. In this embodiment, calculate the similarity of each physiological data according to the change range of each physiological data in adjacent measurement cycles to measure the overall similarity. In this way, when the overall similarity of adjacent measurement cycles is greater than the second preset threshold due to too small a measurement cycle setting, merge the data of adjacent measurement cycles, thereby simplifying the process of the blood pressure medication optimization management method.

[0039] In a further preferred embodiment, adjust the blood pressure reference curve based on the physiological cycle curve. Specifically:

[0040] S301. Obtain the reference physiological state corresponding to each measurement cycle in the blood pressure reference curve. The blood pressure reference curve and the reference physiological state can be obtained based on big data;

[0041] S302. Determine whether the target physiological state and the corresponding reference physiological state in each measurement cycle are consistent. If they are consistent, keep the blood pressure change state in the current measurement cycle unchanged. If they are not consistent, execute S303;

[0042] S303. Query the blood pressure data table of the target object, obtain the blood pressure change state of the target object after the target physiological state lasts for the corresponding measurement cycle, and adjust the blood pressure reference curve according to the blood pressure change state. The blood pressure data table in the above embodiments includes the blood pressure change conditions in different physiological states and for different durations. It can be understood that this blood pressure data table does not need to collect the data of the target object for 24 hours, but only needs to collect the blood pressure values after different physiological states and for different durations, and the number of measurements is small. Specifically, reminder messages can be generated respectively before and after each sleep, sedentary state, mild, moderate exercise, and high-intensity exercise of the user. After receiving the reminder messages, the user can collect blood pressure information to obtain a large amount of historical data. After screening and filtering the obviously abnormal data from this historical data, the blood pressure data table can be automatically established.

[0043] Exemplarily, in a specific embodiment, adjusting the initial medication data according to the blood pressure change target curve specifically includes: obtaining the number of medication times and the onset duration of the target blood pressure drug, and selecting at least one target medication period in the blood pressure change target curve according to the number of medication times and the onset duration. The specific selection method exists in the existing technical solutions and will not be elaborated here.

[0044] The above preferred embodiment statistically analyzes the physiological data of the target patient within a certain duration, obtains the regular physiological state data of the target patient in 24 hours, and plots it into a curve, so as to optimize and suggest the initial medication data of the target patient, such as the medication period and dosage recommended by the doctor based on experience, which is more conducive to improving the control effect of the target patient on their own blood pressure.

[0045] In a preferred embodiment, the obtaining of the blood pressure reference curve of the target object is specifically as follows:

[0046] Obtain the historical blood pressure data of the target object, and generate the blood pressure reference curve according to the historical blood pressure data. The historical blood pressure data is 24-hour blood pressure data collected by an ABPM device. The ABPM device is a portable real-time blood pressure detection device, but it is relatively expensive and is generally used more when hypertensive patients need to be hospitalized for 24-hour blood pressure monitoring. If a patient has ever used an ABPM device for blood pressure monitoring, the historical blood pressure data can be used to generate the blood pressure reference curve at that historical moment and serve as the reference adjustment object in this example.

[0047] In another preferred embodiment, it is also possible to obtain target group information matching the age, gender, eating habits, etc. of the target object, and then collect 24-hour blood pressure data of the corresponding target group through big data and generate the blood pressure reference curve. In the preferred embodiment, blood pressure changes are also affected by factors such as weather. Therefore, according to weather changes, for example, when repeating the use of this optimization management method every time the season changes, first obtain the blood pressure reference curve for the current season, and then adjust the blood pressure reference curve according to the physiological cycle curve to generate a corresponding optimized medication plan.

[0048] Exemplarily, in a preferred embodiment, the optimization management method for hypertensive medication further includes: obtaining the blood pressure fluctuation amplitude corresponding to each target medication period, and generating the target medication dose for the target medication period according to the blood pressure fluctuation amplitude, so as to adjust both the medication period and the medication dose at the same time, and further improve the blood pressure control effect.

[0049] Exemplarily, in a preferred embodiment, the optimization management method for hypertensive medication further includes: collecting at least one of the diet data, disease data, and environmental data of the target object, and adjusting the optimized medication plan, so as to specifically analyze the influence degree of the user's diet intake, co-existing diseases, and environmental changes on blood pressure control, and specifically improve the blood pressure control effect of the patient.

[0050] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0051] The embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which when executed by a processor, implements the above-mentioned optimization management method for hypertensive medication.

[0052] Figure 2 It is a schematic structural diagram of the optimization management device for hypertensive medication provided in Embodiment 2, as Figure 2As shown in the figure, it includes an acquisition module 100, an analysis module 200, an adjustment module 300, and a solution generation module 400.

[0053] The acquisition module 100 is used to acquire the initial medication data of the target object for the target blood pressure drug.

[0054] The analysis module 200 is used to collect and analyze the physiological data of the target object within a preset time range, and generate a physiological cycle curve of the target object.

[0055] The adjustment module 300 is used to obtain the blood pressure reference curve of the target object, and adjust the blood pressure reference curve based on the physiological cycle curve to generate a target curve of blood pressure change of the target object.

[0056] The solution generation module 400 is used to optimize the initial medication data according to the target curve of blood pressure change, and generate a medication optimization plan.

[0057] The above embodiments provide an optimized management device for hypertension medication, which measures the actual blood pressure change state of a patient according to the change of the patient's physiological data within a certain time range. Even if it is difficult to obtain the 24-hour blood pressure monitoring data of the patient, targeted medication advice can be provided for the patient, improving the blood pressure control effect of the patient.

[0058] In a preferred embodiment, the analysis module 200 specifically includes a collection unit, a first judgment unit, a second judgment unit, and a curve generation module.

[0059] The collection unit is used to divide 24 hours into a preset number of measurement cycles, and continuously collect the physiological data of the target object in each measurement cycle within the preset time range.

[0060] The first judgment unit is used to judge the physiological state of the target object corresponding to each measurement cycle according to the physiological data. The physiological state includes a sleep state, a sedentary state, a light exercise state, a moderate exercise state, and a high-intensity exercise state.

[0061] The second judgment unit is used to calculate the average similarity of the physiological states within the preset time range. If the average similarity is greater than a first preset threshold, the curve generation module is driven; otherwise, the optimized management method is stopped, and the initial medication data remains unchanged.

[0062] The curve generation module is used to obtain the target physiological state of each measurement cycle within the preset time range, and generate a physiological cycle curve of the target object that continuously changes within 24 hours. The target physiological state is the physiological state with the most repeated times corresponding to the measurement cycle.

[0063] In a preferred embodiment, the analysis module 200 further includes a data merging unit, which is configured to determine the similarity of the physiological data corresponding to adjacent measurement periods. When the similarity is greater than a second preset threshold, the adjacent measurement periods and the corresponding physiological data are merged.

[0064] In a preferred embodiment, the adjustment module 300 specifically includes a first acquisition unit, a second acquisition unit, a third judgment unit, and an adjustment unit.

[0065] The first acquisition unit is configured to acquire the blood pressure reference curve of the target object.

[0066] The second acquisition unit is configured to acquire the reference physiological state corresponding to each measurement period in the blood pressure reference curve.

[0067] The third judgment unit is configured to judge whether the target physiological state and the corresponding reference physiological state of each measurement period are consistent. If they are consistent, the blood pressure change state of the current measurement period remains unchanged. If they are not consistent, the adjustment unit is driven.

[0068] The adjustment unit is configured to query the blood pressure data table of the target object, acquire the blood pressure change state of the target object after continuously corresponding to the measurement period with the target physiological state, and adjust the blood pressure reference curve according to the blood pressure change state.

[0069] In a preferred embodiment, the first acquisition unit is specifically configured to acquire the historical blood pressure data of the target object and generate the blood pressure reference curve according to the historical blood pressure data, where the historical blood pressure data is 24-hour blood pressure data collected by an ABPM device; or is configured to acquire the target group information matching the target object and generate the blood pressure reference curve according to the 24-hour blood pressure data of the corresponding target group.

[0070] In a preferred embodiment, the solution generation module 400 is specifically configured to acquire the number of medication times and the onset duration of the target blood pressure drug, and select at least one target medication period in the target blood pressure change curve.

[0071] In a preferred embodiment, the solution generation module 400 is further configured to acquire the blood pressure fluctuation amplitude corresponding to each target medication period and generate the target medication dose for each target medication period.

[0072] In another preferred embodiment, the solution generation module 400 is further configured to collect the diet data, disease data, and / or environmental data of the target object and adjust the medication optimization solution.

[0073] It should be noted that the foregoing explanatory description of the embodiments of the optimization management method for hypertension medications also applies to the optimization management device for hypertension medications in the above embodiments, and will not be elaborated here.

[0074] An embodiment of the present invention also provides an optimization management device for hypertension medications, including a computer-readable storage medium and a processor. When the processor executes a computer program on the computer-readable storage medium, the steps of the above-described optimization management method for hypertension medications are implemented.

[0075] Figure 3 FIG. is a schematic structural diagram of the optimization management device for hypertension medications provided in Embodiment 3 of the present invention. As Figure 3 shown, the optimization management device 8 for hypertension medications in this embodiment includes: a processor 80, a readable storage medium 81, and a computer program 82 stored in the readable storage medium 81 and executable on the processor 80. When the processor 80 executes the computer program 82, the steps in the above-described method embodiments are implemented, for example Figure 1 the steps shown. Alternatively, when the processor 80 executes the computer program 82, the functions of each module in the above-described device embodiments are implemented, for example Figure 2 the functions of the module shown.

[0076] Exemplarily, the computer program 82 can be divided into one or more modules. The one or more modules are stored in the readable storage medium 81 and executed by the processor 80 to complete the present invention. The one or more modules can be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program 82 in the optimization management device 8 for hypertension medications.

[0077] The optimization management device 8 for hypertension medications may include, but is not limited to, a processor 80 and a readable storage medium 81. Those skilled in the art can understand that Figure 3 this is merely an example of the optimization management device 8 for hypertension medications and does not constitute a limitation on the optimization management device 8 for hypertension medications. It may include more or fewer components than shown in the figure, or combine certain components, or have different components. For example, the optimization management device for hypertension medications may further include a power supply scheme generation module, an arithmetic processing module, input / output devices, a network access device, a bus, etc.

[0078] The so-called processor 80 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0079] The readable storage medium 81 may be an internal storage unit of the hypertension medication optimization management device 8, such as the hard disk or memory of the hypertension medication optimization management device 8. The readable storage medium 81 may also be an external storage device of the hypertension medication optimization management device 8, such as a plug-in hard disk equipped on the hypertension medication optimization management device 8, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the readable storage medium 81 may also include both the internal storage unit and the external storage device of the hypertension medication optimization management device 8. The readable storage medium 81 is used to store the computer program and other programs and data required by the hypertension medication optimization management device. The readable storage medium 81 may also be used to temporarily store data that has been output or is to be output.

[0080] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules as needed, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiments may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiments and will not be elaborated here.

[0081] In the above embodiments, the descriptions of the various embodiments have their own emphases. For parts not described or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0082] Those of ordinary skill in the art can realize that the units and method steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0083] In the embodiments provided by the present invention, it should be understood that the disclosed device / terminal device and method can be implemented in other ways. For example, the device / terminal device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical or other forms.

[0084] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0085] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0086] The present invention is not limited only to what is described in the specification and embodiments. Therefore, for those skilled in the art, additional advantages and modifications can be easily achieved. Therefore, without departing from the spirit and scope of the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details, representative devices and the illustrated examples shown and described here.

Claims

1. A method for optimizing the management of hypertension medication, characterized in that: The following steps are involved: Step 1, obtaining the initial medication data of the target subject for the target blood pressure medication; Step 2, collecting and analyzing the physiological data of the target object within a preset time range to generate a physiological cycle curve of the target object; Step 3, obtaining a blood pressure reference curve of the target object, and adjusting the blood pressure reference curve based on the physiological cycle curve to generate a blood pressure change target curve of the target object; Step 4: Optimize the initial medication data according to the blood pressure change target curve to generate an optimized medication plan.

2. The method for optimizing management of hypertension medication according to claim 1, characterized in that: Collect and analyze the target object's physiological data within a preset time range to generate the target object's physiological cycle curve, specifically: S201, dividing 24 hours into a preset number of measurement cycles, and continuously collecting physiological data of the target object in each measurement cycle within a preset time range; S202, determining the physiological state of the target object corresponding to each measurement period according to the physiological data, wherein the physiological state includes a sleeping state, a sedentary state, a light exercise state, a moderate exercise state, and a high-intensity exercise state; S203, calculating the average similarity of the physiological state within the preset time range, if the average similarity is greater than a first preset threshold, executing S204, otherwise stopping the optimization management method and keeping the initial medication data unchanged; S204, obtaining the target physiological state of each measurement cycle within the preset time range, and generating a physiological cycle curve of the target object that changes continuously over 24 hours, wherein the target physiological state is the physiological state with the largest number of repetitions corresponding to the measurement cycle.

3. The method for optimizing management of hypertension medication according to claim 1, characterized in that: The blood pressure reference curve is adjusted based on the physiological cycle curve, specifically: S301, obtaining a reference physiological state corresponding to each measurement cycle in the blood pressure reference curve; S302, determining whether the target physiological state of each measurement cycle is consistent with the corresponding reference physiological state, if they are consistent, keeping the blood pressure change state of the current measurement cycle unchanged, if they are inconsistent, executing S303; S303, querying the blood pressure data table of the target object, obtaining the blood pressure change state of the target object after the target physiological state continues to correspond to the measurement period, and adjusting the blood pressure reference curve according to the blood pressure change state.

4. The method for optimizing management of hypertension medication according to claim 3, characterized in that: The method of obtaining the blood pressure reference curve of the target object is specifically as follows: Acquire historical blood pressure data of the target subject, and generate the blood pressure reference curve according to the historical blood pressure data, wherein the historical blood pressure data is 24-hour blood pressure data collected by using an ABPM device; Alternatively, target group information matching the target object is obtained, and the blood pressure reference curve is generated according to the 24-hour blood pressure data of the corresponding target group.

5. The method for optimizing management of hypertension medication according to any one of claims 1 to 4, characterized in that: The initial medication data is adjusted according to the blood pressure change target curve, specifically: The number of times the target blood pressure drug is taken and the duration of its effect are obtained, and at least one target medication period is selected from the target blood pressure change curve according to the number of times the drug is taken and the duration of its effect.

6. The method for optimizing management of hypertension medication according to claim 5, characterized in that: The method further includes: obtaining a blood pressure fluctuation amplitude corresponding to each target medication period, and generating a target medication dosage for the target medication period according to the blood pressure fluctuation amplitude.

7. The method for optimizing management of hypertension medication according to claim 5, characterized in that: The method further includes: collecting at least one of the target object's dietary data, disease data, and environmental data, and adjusting the medication optimization plan.

8. An optimized management device for hypertension medication, characterized in that: It includes acquisition module, analysis module, adjustment module and solution generation module. The acquisition module is used to acquire the initial medication data of the target subject for the target blood pressure medication; The analysis module is used to collect and analyze the physiological data of the target object within a preset time range to generate a physiological cycle curve of the target object; The adjustment module is used to obtain a blood pressure reference curve of the target object, and adjust the blood pressure reference curve based on the physiological cycle curve to generate a blood pressure change target curve of the target object; The solution generation module is used to optimize the initial medication data according to the blood pressure change target curve to generate an optimized medication solution.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for optimizing the management of hypertension medication as described in any one of claims 1 to 7 is implemented.

10. An optimized management device for hypertension medication, comprising a computer-readable storage medium and a processor, characterized in that: When the processor executes the computer program on the computer-readable storage medium, the processor implements the steps of the method for optimizing management of hypertension medication according to any one of claims 1 to 7.

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