Behavior management method and device for diabetic patient, medium and electronic equipment

Abstract

The invention provides a behavior management method and device for a diabetic patient, a medium and electronic equipment. The method comprises the following steps: determining a target physiological parameter value of a plurality of physiological parameters in a next monitoring stage based on a physiological baseline parameter value, a physiological monitoring parameter value and a target physiological parameter value of a plurality of physiological parameters of a monitored object in the current monitoring stage; and determining constraint values of the plurality of target behavior parameters of the next monitoring stage based on the constraint values of the plurality of target behavior parameters of the current monitoring stage and the target physiological parameter values of the plurality of physiological parameters of the next monitoring stage. Constraint values of the multiple target behavior parameters in the next monitoring stage can be formulated according to body requirements, environmental changes and diagnosis and treatment effects of the monitored object in the monitoring stage, so that a doctor is more accurately assisted in diagnosis, treatment and management of diabetes mellitus, personalized and efficient medical services are provided for a patient, and the diagnosis and treatment efficiency of diabetes mellitus is improved. And scientific progress in the field of diabetes management is promoted.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent healthcare, and more particularly, to a method, apparatus, medium, and electronic device for behavior management of diabetic patients. Background Art

[0002] With the rapid advancement of population aging in China, the prevalence and incidence of diabetes in adults have increased significantly, posing an important challenge in the field of public health in China.

[0003] Like many chronic diseases, there is currently no complete cure for diabetes. Diabetic patients need to carry out continuous self-management in the long term, which involves various factors such as the rational use of drugs and lifestyle changes. It is unable to cope with the complexity and multi-factor influence of the disease and often lacks a systematic and comprehensive treatment strategy. This makes the process of diabetes treatment relatively difficult, especially for elderly patients.

[0004] Currently, the application of machine learning models in the medical field, especially in the management of chronic diseases, has demonstrated its powerful potential. Machine learning models trained with patient physiological data can classify and aggregate patient physiological data, perform pattern recognition, and conduct accurate risk assessment, providing scientific support for medical decision-making.

[0005] However, due to the different physical conditions of diabetic patients and the constantly changing living environments they are in, it is difficult to accurately guide the treatment of patients simply through machine learning models.

[0006] Therefore, the present disclosure provides a method for behavior management of diabetic patients to solve one of the above technical problems. Summary of the Invention

[0007] The purpose of the present disclosure is to provide a method, apparatus, medium, and electronic device for behavior management of diabetic patients, which can solve at least one of the above-mentioned technical problems. The specific solutions are as follows:

[0008] According to a specific embodiment of the present disclosure, in a first aspect, the present disclosure provides a method for behavior management of diabetic patients, including:

[0009] Obtaining the physiological baseline parameter values, the physiological monitoring parameter values of the last monitoring, and the target physiological parameter values of multiple physiological parameters of a monitoring object in the current monitoring stage, as well as the constraint values of multiple target behavior parameters;

[0010] Determining the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters in the current monitoring stage;

[0011] Determine the constraint values of the multiple target behavior parameters in the next monitoring stage based on the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage.

[0012] Optionally, the determining the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters in the current monitoring stage includes:

[0013] Obtain the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters in the current monitoring stage;

[0014] Determine the physiological parameter improvement values of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage;

[0015] Based on the physiological monitoring parameter values of the multiple physiological parameters in the current monitoring stage, and based on the physiological parameter improvement values of the multiple physiological parameters in the next monitoring stage, obtain the target physiological parameter values of the multiple physiological parameters in the next monitoring stage.

[0016] Optionally, the determining the physiological parameter improvement values of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage includes:

[0017] Count the number of the first physiological parameters in the current monitoring stage whose physiological parameter improvement rates are greater than or equal to the preset first physiological parameter improvement rate threshold to obtain a first quantity value;

[0018] Calculate a first percentage value of the first quantity value accounting for the quantity value of the multiple physiological parameters;

[0019] When the first percentage value is greater than or equal to the preset first percentage threshold, obtain a first expected physiological parameter improvement value of the multiple physiological parameters based on the physiological monitoring parameter values corresponding to the first physiological parameters with the minimum physiological parameter improvement rate;

[0020] Determine that the first expected physiological parameter improvement value of the multiple physiological parameters represents the physiological parameter improvement values of the multiple physiological parameters in the next monitoring stage.

[0021] Optionally, the determining the physiological parameter improvement values of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage includes:

[0022] Count the quantity of the second physiological parameters with the improvement rate of the physiological parameters in this monitoring stage being less than or equal to the preset second physiological parameter improvement rate threshold to obtain a second quantity value, where the preset second physiological parameter improvement rate threshold is less than the preset first physiological parameter improvement rate threshold;

[0023] Calculate a second percentage value of the second quantity value in the quantity value of the multiple physiological parameters;

[0024] When the second percentage value is greater than or equal to the preset second percentage threshold, obtain a second expected physiological parameter improvement value of the multiple physiological parameters based on the physiological monitoring parameter value of the second physiological parameter with the maximum physiological parameter improvement rate;

[0025] Determine that the second expected physiological parameter improvement value of the multiple physiological parameters represents the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage.

[0026] Optionally, determining the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the multiple physiological parameters in this monitoring stage further includes:

[0027] When the second percentage value is less than the preset second percentage threshold and the first percentage value is less than the preset first percentage threshold, obtain an average physiological parameter improvement rate based on the physiological parameter improvement rate of the multiple physiological parameters;

[0028] Determine a third physiological parameter corresponding to the physiological parameter improvement rate with the smallest absolute value of the deviation value from the average physiological parameter improvement rate;

[0029] Obtain a third expected physiological parameter improvement value of the multiple physiological parameters based on the physiological monitoring parameter value of the third physiological parameter;

[0030] Determine that the third expected physiological parameter improvement value of the multiple physiological parameters represents the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage.

[0031] Optionally, determining the constraint value of the multiple target behavior parameters in the next monitoring stage based on the constraint value of the multiple target behavior parameters in this monitoring stage and the target physiological parameter value of the multiple physiological parameters in the next monitoring stage includes:

[0032] Apply the constraint value of the multiple target behavior parameters in this monitoring stage and the target physiological parameter value of the multiple physiological parameters in the next monitoring stage to the trained constraint mapping model to obtain the constraint value of the multiple target behavior parameters in the next monitoring stage.

[0033] Optionally, the multiple target behavior parameters include multiple life behavior parameters and / or multiple treatment behavior parameters.

[0034] According to a specific embodiment of the present disclosure, in a second aspect, the present disclosure provides a behavior management device for diabetic patients, including:

[0035] An acquisition unit, configured to acquire the physiological baseline parameter values, the physiological monitoring parameter values of the last monitoring, the target physiological parameter values of multiple physiological parameters of a monitoring object in the current monitoring stage, and the constraint values of multiple target behavior parameters;

[0036] A physiological determination unit, configured to determine the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological baseline parameter values, the physiological monitoring parameter values, and the target physiological parameter values of the multiple physiological parameters in the current monitoring stage;

[0037] A behavior determination unit, configured to determine the constraint values of the multiple target behavior parameters in the next monitoring stage based on the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage.

[0038] Optionally, the determining the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological baseline parameter values, the physiological monitoring parameter values, and the target physiological parameter values of the multiple physiological parameters in the current monitoring stage includes:

[0039] Obtaining the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage based on the physiological baseline parameter values, the physiological monitoring parameter values, and the target physiological parameter values of the multiple physiological parameters in the current monitoring stage;

[0040] Determining the physiological parameter improvement values of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage;

[0041] Based on the physiological monitoring parameter values of the multiple physiological parameters in the current monitoring stage, obtaining the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement values of the multiple physiological parameters in the next monitoring stage.

[0042] Optionally, the determining the physiological parameter improvement values of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage includes:

[0043] Counting the number of first physiological parameters with physiological parameter improvement rates greater than or equal to a preset first physiological parameter improvement rate threshold in the current monitoring stage to obtain a first quantity value;

[0044] Calculate a first percentage value of the first quantity value with respect to the quantity values of the plurality of physiological parameters;

[0045] When the first percentage value is greater than or equal to a preset first percentage threshold, obtain a first expected physiological parameter improvement value of the plurality of physiological parameters based on the physiological monitoring parameter value corresponding to the first physiological parameter with the minimum physiological parameter improvement rate;

[0046] Determine that the first expected physiological parameter improvement value of the plurality of physiological parameters represents the physiological parameter improvement value of the plurality of physiological parameters in the next monitoring stage.

[0047] Optionally, the determining the physiological parameter improvement value of the plurality of physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the plurality of physiological parameters in the current monitoring stage includes:

[0048] Count the quantity of second physiological parameters in the current monitoring stage whose physiological parameter improvement rate is less than or equal to a preset second physiological parameter improvement rate threshold to obtain a second quantity value, where the preset second physiological parameter improvement rate threshold is less than the preset first physiological parameter improvement rate threshold;

[0049] Calculate a second percentage value of the second quantity value with respect to the quantity values of the plurality of physiological parameters;

[0050] When the second percentage value is greater than or equal to a preset second percentage threshold, obtain a second expected physiological parameter improvement value of the plurality of physiological parameters based on the physiological monitoring parameter value corresponding to the second physiological parameter with the maximum physiological parameter improvement rate;

[0051] Determine that the second expected physiological parameter improvement value of the plurality of physiological parameters represents the physiological parameter improvement value of the plurality of physiological parameters in the next monitoring stage.

[0052] Optionally, the determining the physiological parameter improvement value of the plurality of physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the plurality of physiological parameters in the current monitoring stage further includes:

[0053] When the second percentage value is less than the preset second percentage threshold and the first percentage value is less than the preset first percentage threshold, obtain an average physiological parameter improvement rate based on the physiological parameter improvement rates of the plurality of physiological parameters;

[0054] Determine the third physiological parameter corresponding to the physiological parameter improvement rate with the smallest absolute value of the deviation from the average physiological parameter improvement rate;

[0055] Obtain a third expected physiological parameter improvement value of the plurality of physiological parameters based on the physiological monitoring parameter value of the third physiological parameter;

[0056] Determine that the third expected physiological parameter improvement value of the multiple physiological parameters characterizes the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage.

[0057] Optionally, determining the constraint values of the multiple target behavior parameters in the next monitoring stage based on the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage includes:

[0058] Apply the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage to a trained constraint mapping model to obtain the constraint values of the multiple target behavior parameters in the next monitoring stage.

[0059] Optionally, the multiple target behavior parameters include multiple life behavior parameters and / or multiple treatment behavior parameters.

[0060] According to a specific embodiment of the present disclosure, in a third aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, it implements the behavior management method for diabetic patients as described in any one of the above.

[0061] According to a specific embodiment of the present disclosure, in a fourth aspect, the present disclosure provides an electronic device, including: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the behavior management method for diabetic patients as described in any one of the above.

[0062] The above solution of the embodiment of the present disclosure has at least the following beneficial effects compared with the prior art:

[0063] The present disclosure provides a behavior management method, device, medium, and electronic device for diabetic patients. The present disclosure determines the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters of the monitoring object in the current monitoring stage; determines the constraint values of the multiple target behavior parameters in the next monitoring stage based on the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage. It can formulate the constraint values of the multiple target behavior parameters in the next monitoring stage according to the physical needs, environmental changes, and treatment effects of the monitoring object in the current monitoring stage, so as to more accurately assist doctors in the diagnosis, treatment, and management of diabetes, provide personalized and efficient medical services for patients, and promote scientific progress in the field of diabetes management. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 The flowchart of the behavior management method for diabetic patients according to an embodiment of the present disclosure is shown;

[0065] Figure 2 The unit block diagram of the behavior management device for diabetic patients according to an embodiment of the present disclosure is shown;

[0066] Figure 3 The schematic diagram of the connection structure of an electronic device provided according to an embodiment of the present disclosure is shown. Detailed implementation manners

[0067] In order to make the objectives, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below with reference to the accompanying drawings. Apparently, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present disclosure.

[0068] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments, and are not intended to limit the present disclosure. The singular forms "a", "the" and "said" used in the embodiments of the present disclosure and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. "Plural" generally includes at least two.

[0069] It should be understood that the term "and / or" used herein is only a kind of association relationship describing associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after.

[0070] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present disclosure to describe, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present disclosure, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0071] Depending on the context, the words "if", "when" as used herein may be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detecting (stated condition or event)" may be interpreted as "when determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)".

[0072] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a commodity or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the commodity or device comprising said element.

[0073] It should be particularly noted that symbols and / or numbers present in the specification that are not marked in the figure description are not figure reference numerals.

[0074] The optional embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0075] Embodiment 1

[0076] This is an embodiment of the behavior management method for diabetic patients provided by the present disclosure.

[0077] Below in conjunction with Figure 1 The embodiments of the present disclosure will be described in detail.

[0078] Step S101: Obtain the physiological baseline parameter values of multiple physiological parameters of the monitored object in the current monitoring stage, the physiological monitoring parameter values of the last monitoring, the target physiological parameter values, and the constraint values of multiple target behavior parameters.

[0079] In this specific embodiment, the behavior management of diabetic patients (i.e., the monitored object) is divided into multiple monitoring stages. For each monitoring stage, the constraint values of multiple target behavior parameters of the diabetic patient in the current monitoring stage are formulated based on the execution results of the target behavior parameters in the previous monitoring stage. Through a step-by-step approach, the behavior of the monitored object is managed meticulously and scientifically, enabling the diabetes of the monitored object to be effectively controlled.

[0080] The physiological parameters include: body mass parameter, fasting blood glucose level parameter, 2-hour postprandial blood glucose level parameter, TyG parameter, HbA1c parameter, cardiovascular and cerebrovascular parameters, and blood pressure parameter.

[0081] In this specific embodiment, multiple physiological parameters of the monitored object are periodically monitored in each monitoring stage to obtain the physiological monitoring parameter values of the monitored object.

[0082] The physiological baseline parameter values refer to the parameter values of the multiple physiological parameters at the beginning of each monitoring stage. When a monitoring stage ends, the physiological monitoring parameter value detected last in that monitoring stage is the physiological baseline parameter value of the next monitoring stage.

[0083] The target physiological parameter value refers to the target value for the behavior management of the monitored object in this monitoring stage.

[0084] The target behavior parameter is used to manage the behavior of the monitored object.

[0085] In some specific embodiments, the multiple target behavior parameters include multiple life behavior parameters and / or multiple treatment behavior parameters.

[0086] The multiple life behavior parameters include: eating habit parameter, exercise parameter, smoking parameter, and drinking parameter.

[0087] The multiple treatment behavior parameters include: daily medication, daily medication times for each drug, and medication time.

[0088] Step S102: Determine the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters in this monitoring stage.

[0089] In some specific embodiments, the determining the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters in this monitoring stage includes:

[0090] Step S102-1: Obtain the physiological parameter improvement rates of the multiple physiological parameters in this monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters in this monitoring stage.

[0091] Optionally, the obtaining the physiological parameter improvement rates of the multiple physiological parameters in this monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters in this monitoring stage includes:

[0092] Step S102-11: Calculate the difference between the target physiological parameter value and the physiological baseline parameter value of each of the multiple physiological parameters in this monitoring stage to obtain the target improvement amplitude value of the corresponding physiological parameter in this monitoring stage, and calculate the difference between the physiological monitoring parameter value and the physiological baseline parameter value of each of the multiple physiological parameters in this monitoring stage to obtain the actual improvement amplitude value of the corresponding physiological parameter in this monitoring stage.

[0093] For example, in this monitoring stage, the physiological baseline parameter value of the body mass parameter is 72.5 kg, the target physiological parameter value of the body mass parameter is 68 kg, the target improvement amplitude value of the body mass parameter = 68 kg - 72.5 kg = -4.5 kg, the physiological monitoring parameter value of the body mass parameter is 68.5 kg, and the actual improvement amplitude value of the body mass parameter = 68.5 kg - 72.5 kg = -4 kg.

[0094] Step S102-12: Obtain the physiological parameter improvement rate of the corresponding physiological parameter in this monitoring stage based on the actual improvement amplitude value and the target improvement amplitude value of each of the multiple physiological parameters in this monitoring stage.

[0095] For example, continuing with the above example, the physiological parameter improvement rate of the body mass parameter = -4 kg / -4.5 kg = 88.89%.

[0096] Step S102-2: Determine the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the multiple physiological parameters in this monitoring stage.

[0097] In some specific embodiments, the determining the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the multiple physiological parameters in this monitoring stage includes:

[0098] Step S102-2a-1: Count the number of first physiological parameters in this monitoring stage whose physiological parameter improvement rate is greater than or equal to a preset first physiological parameter improvement rate threshold to obtain a first quantity value.

[0099] For example, if the preset first physiological parameter improvement rate threshold is 85%, and the physiological parameter improvement rate of the body mass parameter is 88.89%, the physiological parameter improvement rate of the fasting blood glucose level parameter is 92%, the physiological parameter improvement rate of the 2-hour postprandial blood glucose level parameter is 78%, the physiological parameter improvement rate of the TyG parameter is 100%, the physiological parameter improvement rate of the HbA1c parameter is 93%, and the physiological parameter improvement rate of the cardio-cerebrovascular parameter is 60%, and the physiological parameter improvement rate of the blood pressure parameter is 86%, then the body mass parameter, the fasting blood glucose level parameter, the TyG parameter, the HbA1c parameter, and the blood pressure parameter are all first physiological parameters, and the first quantity value is 5.

[0100] Step S102-2a-2: Calculate a first percentage value of the first quantity value accounting for the quantity value of the multiple physiological parameters.

[0101] For example, continuing with the above example, if the quantity value of the multiple physiological parameters is 7, then the first percentage value = 5 / 7 = 71.43%.

[0102] Step S102-2a-3: When the first percentage value is greater than or equal to the preset first percentage threshold, obtain the first expected physiological parameter improvement value of the multiple physiological parameters based on the physiological monitoring parameter value corresponding to the physiological parameter with the minimum physiological parameter improvement rate.

[0103] The first expected physiological parameter improvement value is an empirical value obtained through experiments.

[0104] For example, continuing with the above example, if the preset first percentage threshold is 70%, and the first percentage value (i.e., 71.43%) is greater than the preset first percentage threshold, it indicates that the physiological monitoring parameter values of most physiological parameters have reached or approached the expected target physiological parameter values, showing that the behavior management effect in this monitoring stage is good. Among the body mass parameter, fasting blood glucose level parameter, TyG parameter, HbA1c parameter, and blood pressure parameter, it is determined that the blood pressure parameter has the minimum physiological parameter improvement rate (i.e., 86%). By looking up the table with the physiological monitoring parameter value of the blood pressure parameter, the first expected physiological parameter improvement value of the multiple physiological parameters can be obtained. Among them, the first expected physiological parameter improvement value of the blood pressure parameter exactly matches the expected improvement target of its own physiological monitoring parameter value, while the first expected physiological parameter improvement values of the body mass parameter, fasting blood glucose level parameter, TyG parameter, and HbA1c parameter are lower than the expected improvement targets of their respective physiological monitoring parameter values, and the first expected physiological parameter improvement values of the 2-hour postprandial blood glucose level parameter and cardiovascular and cerebrovascular parameters are slightly higher than their respective expected improvement targets. Thus, reasonable target physiological parameter values can be set in the behavior management of the next monitoring stage so that the multiple physiological parameters can achieve the target physiological parameter values in the next monitoring stage.

[0105] Step S102-2a-4: Determine that the first expected physiological parameter improvement value of the multiple physiological parameters represents the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage.

[0106] In some other specific embodiments, the determining the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the multiple physiological parameters in this monitoring stage includes:

[0107] Step S102-2b-1: Count the number of second physiological parameters whose physiological parameter improvement rate in this monitoring stage is less than or equal to the preset second physiological parameter improvement rate threshold to obtain a second quantity value.

[0108] Wherein, the preset second physiological parameter improvement rate threshold is less than the preset first physiological parameter improvement rate threshold.

[0109] For example, the preset threshold for the improvement rate of the second physiological parameter is 35%. If the improvement rate of the physiological parameter of the body mass parameter is 88.89%, the improvement rate of the physiological parameter of the fasting blood glucose level parameter is 27%, the improvement rate of the physiological parameter of the 2-hour postprandial blood glucose level parameter is 32%, the improvement rate of the physiological parameter of the TyG parameter is 19%, the improvement rate of the physiological parameter of the HbA1c parameter is 21%, the improvement rate of the physiological parameter of the cardio-cerebrovascular parameter is 69%, and the improvement rate of the physiological parameter of the blood pressure parameter is 12%, then the fasting blood glucose level parameter, the 2-hour postprandial blood glucose level parameter, the TyG parameter, the HbA1c parameter, and the blood pressure parameter are all second physiological parameters, and the second numerical value is 5.

[0110] Step S102-2b-2, calculate a second percentage value of the second numerical value accounting for the numerical values of the multiple physiological parameters.

[0111] For example, continuing with the above example, if the numerical value of the multiple physiological parameters is 7, then the second percentage value = 5 / 7 = 71.43%.

[0112] Step S102-2b-3, when the second percentage value is greater than or equal to a preset second percentage threshold, obtain a second expected improvement value of the multiple physiological parameters based on the physiological monitoring parameter value corresponding to the second physiological parameter with the maximum physiological parameter improvement rate.

[0113] The second expected improvement value of the physiological parameter is an empirical value obtained through experiments.

[0114] For example, continuing with the above example, if the preset second percentage threshold is 70% and the second percentage value (i.e., 71.43%) is greater than the preset second percentage threshold, it indicates that the physiological monitoring parameter values of most physiological parameters cannot reach or approach the target physiological parameter values, and the behavior management effect in this monitoring stage is not good. Among the fasting blood glucose level parameter, the 2-hour postprandial blood glucose level parameter, the TyG parameter, the HbA1c parameter, and the blood pressure parameter, it is determined that the 2-hour postprandial blood glucose level parameter has the maximum physiological parameter improvement rate (i.e., 32%). By looking up the table with the physiological monitoring parameter value of the 2-hour postprandial blood glucose level parameter, the second expected improvement value of the multiple physiological parameters can be obtained. Among them, the second expected improvement value of the 2-hour postprandial blood glucose level parameter exactly matches the expected improvement target of its own physiological monitoring parameter value, while the second expected improvement values of the fasting blood glucose level parameter, the TyG parameter, the HbA1c parameter, and the blood pressure parameter are higher than the expected improvement targets of their respective physiological monitoring parameter values, and the second expected improvement values of the body mass parameter and the cardio-cerebrovascular parameter are lower than their respective expected improvement targets. Thus, reasonable target physiological parameter values can be set in the behavior management of the next monitoring stage so that the multiple physiological parameters can achieve the target physiological parameter values in the next monitoring stage.

[0115] Step S102-2b-4, determine that the second expected physiological parameter improvement value of the multiple physiological parameters characterizes the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage.

[0116] In some other specific embodiments, the determining of the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the multiple physiological parameters in the current monitoring stage further includes:

[0117] Step S102-2c-1, when the second percentage value is less than a preset second percentage threshold and the first percentage value is less than a preset first percentage threshold, obtain an average physiological parameter improvement rate based on the physiological parameter improvement rate of the multiple physiological parameters.

[0118] If the behavior management effect in the current monitoring stage is neither good (i.e., the first percentage value is less than the preset first percentage threshold) nor poor (i.e., the second percentage value is less than the preset second percentage threshold), then obtain an average physiological parameter improvement rate.

[0119] Step S102-2c-2, determine the third physiological parameter corresponding to the physiological parameter improvement rate with the smallest absolute value of the deviation from the average physiological parameter improvement rate.

[0120] Step S102-2c-3, obtain the third expected physiological parameter improvement value of the multiple physiological parameters based on the physiological monitoring parameter value of the third physiological parameter.

[0121] For example, by looking up a table with the physiological monitoring parameter value of the third physiological parameter, the third expected physiological parameter improvement value of the multiple physiological parameters can be obtained, where the third expected physiological parameter improvement value of the third physiological parameter exactly matches the expected improvement target of its own physiological monitoring parameter value, while the third expected physiological parameter improvement values of other physiological parameters are either higher or lower than their respective expected improvement targets, so that reasonable target physiological parameter values can be set in the behavior management in the next monitoring stage, so that the multiple physiological parameters can achieve the target physiological parameter values in the next monitoring stage.

[0122] Step S102-2c-4, determine that the third expected physiological parameter improvement value of the multiple physiological parameters characterizes the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage.

[0123] Step S102-3, based on the physiological monitoring parameter values of the multiple physiological parameters in the current monitoring stage, obtain the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage.

[0124] For example, if the physiological monitoring parameter value of the body mass parameter is 68.5 kg and the improvement value of the physiological parameter of the body mass parameter in the next monitoring stage is -0.5 kg, then the target physiological parameter value of the body mass parameter in the next monitoring stage = 68.5 kg - 0.5 kg = 68 kg.

[0125] Step S103: Determine the constraint values of the multiple target behavior parameters in the next monitoring stage based on the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage.

[0126] For example, the constraint value of the eating habit parameter is 4 meals a day and the food intake per meal.

[0127] In some specific embodiments, the determining the constraint values of the multiple target behavior parameters in the next monitoring stage based on the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage includes:

[0128] Apply the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage to a trained constraint mapping model to obtain the constraint values of the multiple target behavior parameters in the next monitoring stage.

[0129] Optionally, the constraint mapping model is an XGBoost model.

[0130] The XGBoost model is an optimized distributed gradient boosting library. The XGBoost model is an improvement of the gradient boosting algorithm. When solving the extreme value of the loss function, the Newton method is used, and the loss function is Taylor-expanded to the second order. In addition, a regularization term is added to the loss function. The objective function during training consists of two parts. The first part is the loss of the gradient boosting algorithm, and the second part is the regularization term. The XGBoost model analyzes the constraint values of the multiple target behavior parameters of the monitored object in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage, and can efficiently, flexibly and portably provide more detailed data support for doctors, provide an effective individualized treatment plan, and improve the accuracy of the prediction model.

[0131] In the embodiments of the present disclosure, the target physiological parameter values of the multiple physiological parameters in the next monitoring stage are determined based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters of the monitoring object in the current monitoring stage; the constraint values of the multiple target behavior parameters in the next monitoring stage are determined based on the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage. It is possible to formulate the constraint values of the multiple target behavior parameters in the next monitoring stage according to the physical needs, environmental changes, and treatment effects of the monitoring object in the current monitoring stage, so as to more accurately assist doctors in the diagnosis, treatment, and management of diabetes, provide personalized and efficient medical services for patients, and promote scientific progress in the field of diabetes management.

[0132] Embodiment 2

[0133] The present disclosure also provides a device embodiment that continues from the above embodiments, which is used to implement the method steps described in the above embodiments. The interpretation of the same name meaning is the same as that in the above embodiments, and it has the same technical effects as the above embodiments, so it will not be elaborated here.

[0134] As Figure 2 shown, the present disclosure provides a behavior management device 200 for diabetic patients, including:

[0135] An acquisition unit 201, configured to acquire the physiological baseline parameter values, the physiological monitoring parameter values of the last monitoring, and the target physiological parameter values of the multiple physiological parameters of the monitoring object in the current monitoring stage, as well as the constraint values of the multiple target behavior parameters;

[0136] A physiological determination unit 202, configured to determine the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters in the current monitoring stage;

[0137] A behavior determination unit 203, configured to determine the constraint values of the multiple target behavior parameters in the next monitoring stage based on the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage.

[0138] Optionally, the determining the target physiological parameter values of the multiple physiological parameters in the next monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters in the current monitoring stage includes:

[0139] Obtaining the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters in the current monitoring stage;

[0140] Determine the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the multiple physiological parameters in the current monitoring stage;

[0141] Based on the physiological monitoring parameter values of the multiple physiological parameters in the current monitoring stage, and based on the physiological parameter improvement values of the multiple physiological parameters in the next monitoring stage, obtain the target physiological parameter values of the multiple physiological parameters in the next monitoring stage.

[0142] Optionally, the determining the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the multiple physiological parameters in the current monitoring stage includes:

[0143] Count the number of first physiological parameters in the current monitoring stage whose physiological parameter improvement rate is greater than or equal to a preset first physiological parameter improvement rate threshold to obtain a first quantity value;

[0144] Calculate a first percentage value of the first quantity value in the quantity value of the multiple physiological parameters;

[0145] When the first percentage value is greater than or equal to a preset first percentage threshold, obtain a first expected physiological parameter improvement value of the multiple physiological parameters based on the physiological monitoring parameter values of the first physiological parameters with the minimum physiological parameter improvement rate;

[0146] Determine that the first expected physiological parameter improvement value of the multiple physiological parameters represents the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage.

[0147] Optionally, the determining the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the multiple physiological parameters in the current monitoring stage includes:

[0148] Count the number of second physiological parameters in the current monitoring stage whose physiological parameter improvement rate is less than or equal to a preset second physiological parameter improvement rate threshold to obtain a second quantity value, where the preset second physiological parameter improvement rate threshold is less than the preset first physiological parameter improvement rate threshold;

[0149] Calculate a second percentage value of the second quantity value in the quantity value of the multiple physiological parameters;

[0150] When the second percentage value is greater than or equal to a preset second percentage threshold, obtain a second expected physiological parameter improvement value of the multiple physiological parameters based on the physiological monitoring parameter values of the second physiological parameters with the maximum physiological parameter improvement rate;

[0151] Determine that the second expected physiological parameter improvement value of the multiple physiological parameters characterizes the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage.

[0152] Optionally, the determining the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rate of the multiple physiological parameters in the current monitoring stage further includes:

[0153] When the second percentage value is less than a preset second percentage threshold and the first percentage value is less than a preset first percentage threshold, obtain an average physiological parameter improvement rate based on the physiological parameter improvement rates of the multiple physiological parameters;

[0154] Determine the third physiological parameter corresponding to the physiological parameter improvement rate with the smallest absolute value of the deviation value from the average physiological parameter improvement rate;

[0155] Obtain the third expected physiological parameter improvement value of the multiple physiological parameters based on the physiological monitoring parameter value of the third physiological parameter;

[0156] Determine that the third expected physiological parameter improvement value of the multiple physiological parameters characterizes the physiological parameter improvement value of the multiple physiological parameters in the next monitoring stage.

[0157] Optionally, the determining the constraint values of the multiple target behavior parameters in the next monitoring stage based on the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage includes:

[0158] Apply the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage to a trained constraint mapping model to obtain the constraint values of the multiple target behavior parameters in the next monitoring stage.

[0159] Optionally, the multiple target behavior parameters include multiple life behavior parameters and / or multiple treatment behavior parameters.

[0160] In an embodiment of the present disclosure, the target physiological parameter values of the multiple physiological parameters in the next monitoring stage are determined based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values of the multiple physiological parameters of the monitoring object in the current monitoring stage; and the constraint values of the multiple target behavior parameters in the next monitoring stage are determined based on the constraint values of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values of the multiple physiological parameters in the next monitoring stage. It is possible to formulate the constraint values of the multiple target behavior parameters in the next monitoring stage according to the physical needs, environmental changes, and treatment effects of the monitoring object in the current monitoring stage, thereby more accurately assisting doctors in the diagnosis, treatment, and management of diabetes, providing personalized and efficient medical services for patients, and promoting scientific progress in the field of diabetes management.

[0161] Embodiment 3

[0162] As Figure 3 shown, this embodiment provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method steps as described in the above embodiment.

[0163] Embodiment 4

[0164] An embodiment of the present disclosure provides a non-volatile computer storage medium, which stores computer-executable instructions that can execute the method steps as described in the above embodiment.

[0165] Embodiment 5

[0166] Next, refer to Figure 3 , which shows a schematic structural diagram of an electronic device suitable for implementing the embodiments of the present disclosure. The terminal device in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The electronic device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present disclosure.

[0167] As Figure 3As shown, the electronic device may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 301, which may perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage device 308 into the random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0168] Generally, the following devices may be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 305 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 308 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 309. The communication device 309 may allow the electronic device to communicate with other devices wirelessly or wiredly to exchange data. Although Figure 3 an electronic device with various devices is shown, it should be understood that it is not required to implement or have all the shown devices. Instead, more or fewer devices may be implemented or had.

[0169] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart may be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above functions defined in the method of the embodiment of the present disclosure are executed.

[0170] It should be noted that the above-mentioned computer-readable medium in the present disclosure may be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present disclosure, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium, and this computer-readable signal medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0171] The above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or it may exist separately and not be assembled into the electronic device.

[0172] The computer program code for performing the operations of the present disclosure may be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include object-oriented programming languages - such as Java, Smalltalk, C++, and also include conventional procedural programming languages - such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network - including a local area network (LAN) or a wide area network (WAN) - or may be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0173] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0174] The units described in the embodiments of the present disclosure can be implemented in software or in hardware. Among them, the name of the unit does not constitute a limitation to the unit itself in some cases.

[0175] Finally, it should be noted that the embodiments in this specification are described in a progressive manner, and the key points of each embodiment are the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other. For the systems or devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0176] The above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them; although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A behavior management method for diabetic patients, characterized in that: include: Obtaining physiological baseline parameter values ​​of multiple physiological parameters of the monitored object in the current monitoring phase, physiological monitoring parameter values ​​and target physiological parameter values ​​of the last monitoring, and constraint values ​​of multiple target behavioral parameters; Determine target physiological parameter values ​​of the multiple physiological parameters in the next monitoring stage based on the physiological baseline parameter values, physiological monitoring parameter values ​​and target physiological parameter values ​​of the multiple physiological parameters in the current monitoring stage; The constraint values ​​of the multiple target behavior parameters in the next monitoring stage are determined based on the constraint values ​​of the multiple target behavior parameters in the present monitoring stage and the target physiological parameter values ​​of the multiple physiological parameters in the next monitoring stage.

2. The method according to claim 1, characterized in that: The step of determining target physiological parameter values ​​of the multiple physiological parameters in the next monitoring phase based on the physiological baseline parameter values, physiological monitoring parameter values, and target physiological parameter values ​​of the multiple physiological parameters in the current monitoring phase includes: Obtaining physiological parameter improvement rates of the multiple physiological parameters in the present monitoring phase based on the physiological baseline parameter values, physiological monitoring parameter values ​​and target physiological parameter values ​​of the multiple physiological parameters in the present monitoring phase; Determining the physiological parameter improvement values ​​of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage; Based on the physiological monitoring parameter values ​​of the multiple physiological parameters in the present monitoring stage and based on the physiological parameter improvement values ​​of the multiple physiological parameters in the next monitoring stage, target physiological parameter values ​​of the multiple physiological parameters in the next monitoring stage are obtained.

3. The method according to claim 2, characterized in that The determining the physiological parameter improvement values ​​of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage includes: Performing quantitative statistics on the first physiological parameter whose improvement rate of the physiological parameter in the present monitoring stage is greater than or equal to a preset first physiological parameter improvement rate threshold value to obtain a first quantitative value; Calculating a first percentage value of the first quantity value to the quantity values ​​of the plurality of physiological parameters; When the first percentage value is greater than or equal to a preset first percentage threshold, obtaining a first expected physiological parameter improvement value of the multiple physiological parameters based on the physiological monitoring parameter value corresponding to the first physiological parameter of the minimum physiological parameter improvement rate; Determining first expected physiological parameter improvement values ​​of the plurality of physiological parameters represents physiological parameter improvement values ​​of the plurality of physiological parameters in the next monitoring stage.

4. The method according to claim 3, characterized in that The determining the physiological parameter improvement values ​​of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage includes: Performing quantitative statistics on the second physiological parameter whose improvement rate of the physiological parameter in the present monitoring stage is less than or equal to a preset second physiological parameter improvement rate threshold to obtain a second quantitative value, wherein the preset second physiological parameter improvement rate threshold is less than the preset first physiological parameter improvement rate threshold; Calculating a second percentage value of the second quantity value to the quantity values ​​of the plurality of physiological parameters; When the second percentage value is greater than or equal to a preset second percentage threshold, obtaining a second expected physiological parameter improvement value of the multiple physiological parameters based on the physiological monitoring parameter value corresponding to the second physiological parameter with the maximum physiological parameter improvement rate; Determining second expected physiological parameter improvement values ​​of the plurality of physiological parameters represents physiological parameter improvement values ​​of the plurality of physiological parameters in the next monitoring stage.

5. The method according to claim 4, characterized in that The determining of the physiological parameter improvement values ​​of the multiple physiological parameters in the next monitoring stage based on the physiological parameter improvement rates of the multiple physiological parameters in the current monitoring stage further includes: When the second percentage value is less than a preset second percentage threshold, and the first percentage value is less than a preset first percentage threshold, obtaining an average physiological parameter improvement rate based on the physiological parameter improvement rates of the multiple physiological parameters; Determine a third physiological parameter corresponding to a physiological parameter improvement rate having a minimum absolute value of a deviation from the average physiological parameter improvement rate; obtaining a third expected physiological parameter improvement value of the plurality of physiological parameters based on the physiological monitoring parameter value of the third physiological parameter; Determining third expected physiological parameter improvement values ​​of the plurality of physiological parameters represents the physiological parameter improvement values ​​of the plurality of physiological parameters in the next monitoring stage.

6. The method according to claim 1, characterized in that The determining the constraint values ​​of the multiple target behavior parameters in the next monitoring stage based on the constraint values ​​of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values ​​of the multiple physiological parameters in the next monitoring stage includes: The constraint values ​​of the multiple target behavior parameters of the present monitoring stage and the target physiological parameter values ​​of the multiple physiological parameters of the next monitoring stage are applied to the trained constraint mapping model to obtain the constraint values ​​of the multiple target behavior parameters of the next monitoring stage.

7. The method according to claim 1, characterized in that The multiple target behavior parameters include multiple life behavior parameters and / or multiple treatment behavior parameters.

8. A behavior management device for diabetic patients, characterized in that: include: An acquisition unit, used to acquire physiological baseline parameter values ​​of multiple physiological parameters of the monitored object in the current monitoring phase, physiological monitoring parameter values ​​and target physiological parameter values ​​of the last monitoring, and constraint values ​​of multiple target behavior parameters; a physiological determination unit, configured to determine target physiological parameter values ​​of the multiple physiological parameters in a next monitoring phase based on the physiological baseline parameter values, the physiological monitoring parameter values ​​and the target physiological parameter values ​​of the multiple physiological parameters in the current monitoring phase; A behavior determination unit is used to determine the constraint values ​​of the multiple target behavior parameters in the next monitoring stage based on the constraint values ​​of the multiple target behavior parameters in the current monitoring stage and the target physiological parameter values ​​of the multiple physiological parameters in the next monitoring stage.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method as claimed in any one of claims 1 to 7.

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