An auxiliary intervention method and system for a nutritional plan for patients with gestational hypertension

Abstract

The present invention relates to the technical field of medical informatics, and particularly relates to an auxiliary intervention method and system for a nutritional plan for patients with gestational hypertension. The method includes: obtaining various indicators of patients with gestational hypertension every day; determining corresponding difference indexes based on the data aggregation of each type of indicator; obtaining the correlation value between the abnormality of each type of indicator and each type of pressure data according to the difference between the change in the difference index corresponding to the same type of indicator on two adjacent days of each patient and the change in the difference index corresponding to the diastolic blood pressure, and the difference between the overall distribution of the difference index corresponding to each type of pressure data of each patient and the overall distribution of the difference index corresponding to each type of indicator; obtaining the degree of intervention to be carried out in combination with the change in the difference index corresponding to the intake of each type of food on two adjacent days of each patient and the correlation value, and then determining the intake of each type of food on the next day. The present invention can dynamically adjust the intake of different types of food for patients with gestational hypertension.

Description

Technical Field

[0001] The present invention relates to the technical field of medical informatics, and particularly to an auxiliary intervention method and system for a nutrition plan for patients with gestational hypertension. Background Art

[0002] Gestational hypertension is a disease unique to pregnancy. When the disease is severe, it may affect the health of the mother and baby. Its etiology is complex and the pathogenesis is not yet clear. A reasonable diet habit is conducive to maintaining blood pressure stability, thereby preventing and controlling gestational hypertension and improving the perinatal situation. Therefore, it is necessary to intervene in the nutrition plans of different patients with gestational hypertension.

[0003] When the prior art intervenes in the nutrition plan of a patient with gestational hypertension, it usually gives suggestions on the eating habit of the patient according to the relevant data detected by a single physiological dimension of a certain patient. However, due to individual physical differences and the different impacts of different stages of pregnancy on the physical condition of the patient, the demand degrees of different patients for each nutrient component vary at different times; the existing methods cannot adjust the nutrition plan based on the changes of the physiological dimensions of patients with gestational hypertension at different times. Summary of the Invention

[0004] In order to solve the problem that the existing methods cannot timely adjust the nutrition plan based on the changes of the physiological dimensions of patients with gestational hypertension at different times, the purpose of the present invention is to provide an auxiliary intervention method and system for a nutrition plan for patients with gestational hypertension, and the specific technical solutions adopted are as follows:

[0005] In a first aspect, the present invention provides an auxiliary intervention method for a nutrition plan for patients with gestational hypertension, and the method includes the following steps:

[0006] Obtain various indicators of a patient with gestational hypertension every day during the current time period, where the indicators include various pressure data, meal frequencies, and intakes of different types of foods, and the pressure data includes systolic blood pressure and diastolic blood pressure;

[0007] Based on the data aggregation of each type of indicator of all the patients every day during the current time period, determine the difference index corresponding to each type of indicator of each patient every day; according to the difference between the change situation of the difference index corresponding to the same type of indicator of each patient on two adjacent days and the change situation of the difference index corresponding to the diastolic blood pressure, obtain the corresponding fluctuation similarity degree, and screen the reference days corresponding to each type of indicator of each patient;

[0008] Combining the differences between the overall distributions of the difference indices corresponding to each type of pressure data within the current time period for each patient and the overall distributions of the difference indices corresponding to each type of indicator, the proportion of the number of reference days, and the degree of similarity in fluctuations, the association value between the abnormality of each type of indicator and each type of pressure data for each patient is obtained; combining the change situation of the difference indices corresponding to the intake of each type of food for each patient on two adjacent days, each type of pressure data for each day within the current time period, and the association value, the degree of intervention required for each type of food for each patient is obtained;

[0009] Using the degree of intervention required and the intake amount to determine the intake amount of each type of food for each patient on the next day.

[0010] Preferably, the determining the difference index corresponding to each type of indicator for each patient every day based on the data aggregation situation of each type of indicator for all patients every day within the current time period includes:

[0011] Clustering all patients based on the indicators to be evaluated on the days to be analyzed for all patients, and obtaining the difference index corresponding to the indicators to be evaluated on the days to be analyzed for the candidate patient according to the number of patients in the cluster with the largest number of patients, the number of patients in the cluster where the candidate patient is located, and the difference in the indicators to be evaluated between the cluster where the candidate patient is located and the center point of the corresponding cluster;

[0012] The day to be analyzed is any day within the current time period, the candidate patient is any pregnant woman with gestational hypertension, and the indicator to be evaluated is any type of indicator.

[0013] Preferably, the obtaining the difference index corresponding to the indicators to be evaluated on the days to be analyzed for the candidate patient according to the number of patients in the cluster with the largest number of patients, the number of patients in the cluster where the candidate patient is located, and the difference in the indicators to be evaluated between the cluster where the candidate patient is located and the center point of the corresponding cluster includes:

[0014] Calculating the first ratio between the number of patients in the cluster with the largest number of patients and the number of patients in the cluster where the candidate patient is located;

[0015] According to the difference in the indicators to be evaluated between the candidate patient and the center point of the cluster where the candidate patient is located and the first ratio, obtaining the difference index corresponding to the indicators to be evaluated on the days to be analyzed for the candidate patient, where the first ratio has a positive correlation with the difference index, and the difference in the indicators to be evaluated between the candidate patient and the center point of the cluster where the candidate patient is located has a negative correlation with the difference index.

[0016] Preferably, the obtaining the corresponding degree of similarity in fluctuations according to the difference between the change situation of the difference indices corresponding to the same type of indicator for each patient on two adjacent days and the change situation of the difference index corresponding to the diastolic blood pressure includes:

[0017] The normalization result of the difference between the difference indices corresponding to the same type of indicators on the latter day and the former day within two adjacent days of a candidate patient is used as the fluctuation degree of the same type of indicators of the candidate patient within two adjacent days;

[0018] According to the difference between the fluctuation degree of each type of indicator of a candidate patient within two adjacent days and the fluctuation degree corresponding to the diastolic blood pressure, calculate the fluctuation similarity degree corresponding to each type of indicator of the candidate patient within two adjacent days. The difference between the fluctuation degree of each type of indicator and the fluctuation degree corresponding to the diastolic blood pressure and the fluctuation similarity degree have a negative correlation relationship.

[0019] Preferably, screening the reference days corresponding to each type of indicator of each patient includes:

[0020] For the to-be-evaluated indicator: If the fluctuation similarity degree corresponding to the to-be-evaluated indicator of the candidate patient within two adjacent days is greater than the preset similarity threshold, then the corresponding two adjacent days are used as the reference days corresponding to the to-be-evaluated indicator of the candidate patient.

[0021] Preferably, combining the difference between the overall distribution of the difference indices corresponding to each type of pressure data within the current time period of each patient and the overall distribution of the difference indices corresponding to each type of indicator, the proportion of the number of reference days, and the fluctuation similarity degree, to obtain the correlation value between the abnormality of each type of indicator of each patient and each type of pressure data, includes:

[0022] Calculate the first average value of the difference indices corresponding to the first type of pressure data within the current time period of the candidate patient, and the second average value of the difference indices corresponding to the to-be-evaluated indicator within the current time period of the candidate patient; calculate the minimum value of the fluctuation similarity degrees corresponding to all adjacent reference days corresponding to the to-be-evaluated indicator of the candidate patient;

[0023] According to the ratio between the first average value and the second average value, the proportion of the number of reference days, and the minimum value, obtain the correlation value between the abnormality of the to-be-evaluated indicator of the candidate patient and the first type of pressure data. The ratio between the first average value and the second average value, the proportion of the number of reference days, and the minimum value are all positively correlated with the correlation value;

[0024] The first type of pressure data is any type of pressure data.

[0025] Preferably, combining the change situation of the difference indices corresponding to the intake of each type of food of each patient within two adjacent days, each type of pressure data per day within the current time period, and the correlation value, to obtain the degree of intervention to be performed on each type of food of each patient, includes:

[0026] For any one type of food:

[0027] For the first type of pressure data, calculate the second ratio between the first type of pressure data of the candidate patient on the current day and the average value of the first type of pressure data of all other days except the current day within the current time period; where the current day is the last day within the current time period; calculate the third average value of the correlation values between the abnormalities of all indicators of the candidate patient and the first type of pressure data; denote the ratio between the correlation value between the abnormality of the intake of this type of food of the candidate patient and the first type of pressure data and the third average value as the third ratio; according to the second ratio, the fluctuation degree of the intake of this type of food in the last two days of the candidate patient within the current time period, and the third ratio, obtain the intervention factor of this type of food for the candidate patient under the first type of pressure data, and the second ratio, the fluctuation degree of the intake of this type of food in the last two days of the candidate patient within the current time period, and the third ratio are all positively correlated with the intervention factor;

[0028] Integrate the intervention factors of this type of food for the candidate patient under all types of pressure data to obtain the degree of intervention to be performed on this type of food for the candidate patient.

[0029] Preferably, the integrating the intervention factors of this type of food for the candidate patient under all types of pressure data to obtain the degree of intervention to be performed on this type of food for the candidate patient includes:

[0030] Determine the average value of the intervention factors of this type of food for the candidate patient under all types of pressure data as the degree of intervention to be performed on this type of food for the candidate patient.

[0031] Preferably, the using the degree of intervention to be performed and the intake to determine the intake of each type of food for each patient on the next day includes:

[0032] For any one type of food:

[0033] Calculate the sum value between 1 and the normalized value of the degree of intervention to be performed on this type of food for the candidate patient, and the value range of the normalized value of the degree of intervention to be performed is [-1, 1];

[0034] Take the product of the intake of this type of food of the candidate patient on the current day and the sum value as the intake of this type of food of the candidate patient on the next day.

[0035] In a second aspect, the present invention provides an auxiliary intervention system for a nutritional plan for pregnant women with gestational hypertension, and the system includes:

[0036] A data acquisition module, configured to obtain various indicators of a pregnant woman with gestational hypertension every day within the current time period, where the indicators include various types of pressure data, meal frequencies, and intakes of different types of food, and the pressure data includes systolic blood pressure and diastolic blood pressure;

[0037] A processing module, configured to determine a difference index corresponding to each type of index for each patient every day based on the data aggregation of each type of index for all the patients every day within the current time period; and obtain a corresponding fluctuation similarity degree according to the difference between the change situation of the difference index corresponding to the same type of index for two adjacent days of each patient and the change situation of the difference index corresponding to the diastolic blood pressure, and screen a reference day corresponding to each type of index for each patient.

[0038] A calculation module, configured to obtain an association value between the abnormality of each type of index of each patient and each type of pressure data by combining the difference between the overall distribution of the difference index corresponding to each type of pressure data of each patient within the current time period and the overall distribution of the difference index corresponding to each type of index, the proportion of the number of reference days, and the fluctuation similarity degree; and obtain the degree of intervention to be performed on each type of food of each patient by combining the change situation of the difference index corresponding to the intake of each type of food for two adjacent days of each patient, each type of pressure data for each day within the current time period, and the association value.

[0039] An intake determination module, configured to determine the intake of each type of food for the next day of each patient by using the degree of intervention to be performed and the intake.

[0040] The present invention has at least the following beneficial effects:

[0041] The present invention takes into account that there are differences in eating habits among different patients with gestational hypertension. For example, there are certain differences in the amount of food intake, daily meal frequency, and dietary preferences, resulting in differences in the nutritional needs of different patients. Therefore, based on the data aggregation of each type of index for all patients with gestational hypertension every day within the current time period, the difference situation of each type of index between each patient and other patients is evaluated, and the corresponding difference index is obtained. Then, according to the difference between the change situation of the difference index corresponding to the same type of index for two adjacent days of each patient and the change situation of the difference index corresponding to the diastolic blood pressure, the fluctuation similarity degree is obtained, and the reference day corresponding to each type of index for each patient is screened. Further, by combining the difference between the overall distribution of the difference index corresponding to each type of pressure data of each patient within the current time period and the overall distribution of the difference index corresponding to each type of index, the proportion of the number of reference days, and the fluctuation similarity degree, the influence degree of the change in eating habits on blood pressure is analyzed, and by combining the change situation of the difference index corresponding to the intake of each type of food for two adjacent days of each patient, the degree of intervention to be performed on each type of food of each patient is obtained, and then the intake of each type of food for the next day of each patient with gestational hypertension is determined. The present invention adjusts the nutritional plan of the patient based on the individual characteristics of the patient with gestational hypertension and the changes in their own eating habits, and dynamically intervenes in the nutritional plan of the patient in a targeted manner according to the influence degree of each index of the eating habits on blood pressure, completing the dynamic adjustment of the intake of different types of food for patients with gestational hypertension, and improving the effectiveness of the intervention of the nutritional plan for patients with gestational hypertension. Brief Description of the Drawings

[0042] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0043] Figure 1 It is a flowchart of an auxiliary intervention method for a nutritional plan for pregnant women with gestational hypertension provided by an embodiment of the present invention.

[0044] Figure 2 It is a structural block diagram of an auxiliary intervention system for a nutritional plan for pregnant women with gestational hypertension provided by an embodiment of the present invention. Detailed Embodiments

[0045] To further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following will provide a detailed description of an auxiliary intervention method and system for a nutritional plan for pregnant women with gestational hypertension proposed according to the present invention in combination with the drawings and preferred embodiments.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0047] The following will specifically describe the specific solutions of an auxiliary intervention method and system for a nutritional plan for pregnant women with gestational hypertension provided by the present invention in combination with the drawings.

[0048] An embodiment of an auxiliary intervention method for a nutritional plan for pregnant women with gestational hypertension:

[0049] The specific scenario targeted by this embodiment is: during the process of auxiliary intervention treatment for pregnant women with gestational hypertension, analyze the impact of changes in a certain index in their eating habits on blood pressure in combination with the dining situation of pregnant women with gestational hypertension, so as to dynamically adjust the nutritional intake of pregnant women with gestational hypertension.

[0050] This embodiment proposes an auxiliary intervention method for a nutritional plan for pregnant women with gestational hypertension. As Figure 1 shown, an auxiliary intervention method for a nutritional plan for pregnant women with gestational hypertension in this embodiment includes the following steps:

[0051] Step S1, obtain various indicators of pregnant women with gestational hypertension every day during the current time period, where the indicators include various pressure data, dining frequencies, and intakes of different types of foods, and the pressure data includes systolic blood pressure and diastolic blood pressure.

[0052] First, for multiple patients with gestational hypertension, before these patients have meals, obtain the weight of each type of food they are about to consume. According to the intake of each type of food for each meal of each patient, calculate the daily intake of each type of food for each patient during the current time period. The types of food include meat, vegetables, fruits, starches, etc. In specific applications, the implementer sets according to the specific situation. The number of patients with gestational hypertension is set according to the specific situation. In this embodiment, the number of patients with gestational hypertension is 100. In specific applications, the implementer can set according to the specific situation. Then, count the daily meal frequency of each patient during the current time period, and use an electronic blood pressure monitor to collect the blood pressure data of each patient at a fixed time every day. The blood pressure data includes systolic blood pressure and diastolic blood pressure. The current time period is a set of all historical moments whose time interval from the current moment is less than or equal to a preset duration. In this embodiment, the preset duration is 30 days. In specific applications, the implementer can set according to the specific situation.

[0053] Respectively take the systolic blood pressure, diastolic blood pressure, meal frequency, and the intake of each type of food as one type of index, that is, the various types of indexes of multiple patients with gestational hypertension every day during the current time period are collected.

[0054] Step S2: Based on the data aggregation situation of each type of index of all the patients every day during the current time period, determine the difference index corresponding to each type of index for each patient every day; according to the difference between the change situation of the difference index corresponding to the same type of index for each patient in two adjacent days and the change situation of the difference index corresponding to the diastolic blood pressure, obtain the corresponding fluctuation similarity degree, and screen the reference days corresponding to each type of index for each patient.

[0055] Since there are differences in eating habits among different individuals, for example, the meal amounts of different patients per meal are different, the daily meal frequencies are different, the dietary preferences are different, and the proportion of the intake of different types of food per meal is different, resulting in differences in the nutritional needs of different patients. Therefore, by comparing the differences in the diet-related data of each patient with the data of the other patients, the characteristic dimensions of the eating habits of a single patient are obtained.

[0056] Next, take one day during the current time period, one patient among all the patients with gestational hypertension, and one type of index among all the indexes as an example for illustration.

[0057] Specifically, record any day during the current time period as the day to be analyzed, record any patient with gestational hypertension among all the patients with gestational hypertension as the candidate patient, and record any type of index as the index to be evaluated.

[0058] Cluster all patients based on the evaluation indicators to be analyzed for all patients on the days to be analyzed, and obtain multiple clusters. In this embodiment, the ISODATA algorithm is used for clustering, the initial number of categories is set to 3, the maximum number of iterations is 5, and the initial number of samples in each category , where N is the number of patients, is the floor symbol; the ISODATA algorithm is a prior art and will not be elaborated here.

[0059] Analyze the differences between each type of index of a single patient and those of the other patients. If the number of patients in the cluster where the current patient is located is small, and the corresponding indexes of the current patient and the other patients in the cluster are not similar, then the difference index of this index between the current patient and the other patients is large.

[0060] Based on the above characteristics, calculate the first ratio between the number of patients in the cluster with the largest number of patients and the number of patients in the cluster where the candidate patient is located; according to the difference between the evaluation indicators of the candidate patient and the center point of its cluster and the first ratio, obtain the difference index corresponding to the evaluation indicators of the candidate patient on the days to be analyzed. The first ratio and the difference index are in a positive correlation relationship, and the difference between the evaluation indicators of the candidate patient and the center point of its cluster and the difference index are in a negative correlation relationship.

[0061] Among them, the positive correlation relationship means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. It can be an additive relationship, a multiplicative relationship, etc., which is determined by the actual application; the negative correlation relationship means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtractive relationship, a divisive relationship, etc., which is determined by the actual application.

[0062] In this embodiment, a specific calculation formula for the difference index is given. The difference index corresponding to the j-th type of index of the i-th patient on the k-th day can be expressed as:

[0063]

[0064] Among them, represents the difference index corresponding to the j-th type of index of the i-th patient on the k-th day, represents the number of patients in the cluster with the largest number of patients in the clustering result based on the j-th type of index of all patients on the k-th day, represents the number of patients in the cluster where the i-th patient is located in the clustering result based on the j-th type of index of all patients on the k-th day, represents the difference between the j-th type of index of the i-th patient and the center point of its cluster in the clustering result based on the j-th type of index of all patients on the k-th day, represents a preset first adjustment parameter.

[0065] In this embodiment, a preset adjustment parameter is introduced into the calculation formula of the difference index to prevent the denominator from being zero. The preset adjustment parameter in this embodiment is 0.01. In specific applications, the implementer can set it according to specific circumstances. In this embodiment, the calculation method for the difference between the same indicators is as follows: Take the absolute value of the difference between them as their difference. It represents the first ratio. The larger the first ratio, the fewer the number of patients in the cluster where the \(i\)-th patient is located. When the number of patients in the cluster where the \(i\)-th patient is located is fewer and the difference between the \(j\)-th type of indicator between the \(i\)-th patient and the center point of the cluster where the \(i\)-th patient is located is larger, it indicates that the difference between the \(i\)-th patient and other patients in the \(j\)-th type of indicator on the \(k\)-th day is larger, that is, the difference index corresponding to the \(j\)-th type of indicator of the \(i\)-th patient on the \(k\)-th day is larger.

[0066] Changes in the eating habits of patients with gestational hypertension will have a certain impact on the patients' blood pressure. For example, an increase in the amount of food intake and the frequency of meals may cause the patients' blood pressure to rise, and a large change in the intake proportion of a certain food may affect the blood pressure, etc., which is not conducive to maintaining the stability of the patients' blood pressure. Due to the individual physiological differences of different patients, the degree of influence of changes in eating habits on blood pressure varies among different patients. Therefore, it is necessary to analyze the influence degree of a single dimension on the patient's own blood pressure based on the historical data of the eating habits of a single patient. If a change in a certain indicator can cause a change in blood pressure, for example, when a change in the intake proportion of meat in the patient's diet structure can cause the blood pressure to have a similar fluctuation, the degree of association between this indicator and blood pressure fluctuation is greater.

[0067] Therefore, take the normalization result of the difference between the difference indices corresponding to the same type of indicator on the day after and the day before in two adjacent days within the current time period of the candidate patient as the fluctuation degree of the same type of indicator of the candidate patient in two adjacent days; within the current time period, each type of indicator of the candidate patient corresponds to a fluctuation degree for every two adjacent days. Calculate the fluctuation similarity degree corresponding to each type of indicator of the candidate patient in two adjacent days according to the difference between the fluctuation degree of each type of indicator of the candidate patient in two adjacent days and the fluctuation degree corresponding to the diastolic blood pressure. The difference between the fluctuation degree of each type of indicator and the fluctuation degree corresponding to the diastolic blood pressure has a negative correlation with the fluctuation similarity degree.

[0068] Among them, the negative correlation relationship means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by the actual application.

[0069] In this embodiment, a specific calculation formula for the fluctuation similarity degree is given. The fluctuation similarity degree corresponding to the \(j\)-th type of indicator of the \(i\)-th patient on the \((k - 1)\)-th day and the \(k\)-th day can be expressed as:

[0070]

[0071] Among them, represents the degree of fluctuation similarity corresponding to the j-th type of index of the i-th patient on the (k - 1)-th day and the k-th day, represents the degree of fluctuation of the j-th type of index of the i-th patient on the (k - 1)-th day and the k-th day, represents the degree of fluctuation of the diastolic blood pressure of the i-th patient on the (k - 1)-th day and the k-th day, and sigmoid( ) represents the normalization function, represents a preset second adjustment parameter, represents the absolute value symbol.

[0072] Introducing a preset second adjustment parameter in the degree of fluctuation similarity is to prevent the denominator from being zero. In this embodiment, the preset second adjustment parameter is 0.01. In specific applications, the implementer can set it according to specific circumstances. represents the difference between the degree of fluctuation of the j-th type of index of the i-th patient on the (k - 1)-th day and the k-th day and the degree of fluctuation of the diastolic blood pressure. The smaller this value is, the smaller the difference between the two, and the greater the degree of fluctuation similarity corresponding to the j-th type of index of the i-th patient on the (k - 1)-th day and the k-th day.

[0073] For the index to be evaluated: If the degree of fluctuation similarity corresponding to the index to be evaluated of the candidate patient on two adjacent days is greater than the preset similarity threshold, then the corresponding two adjacent days are used as the reference days corresponding to the index to be evaluated of the candidate patient. In this embodiment, the preset similarity threshold is 0.5. In specific applications, the implementer can set it according to specific circumstances.

[0074] By using the method provided in this embodiment, multiple reference days corresponding to each type of index of each patient are obtained.

[0075] Step S3: Combine the difference between the overall distribution of the difference index corresponding to each type of pressure data of each patient within the current time period and the overall distribution of the difference index corresponding to each type of index, the proportion of the number of reference days, and the degree of fluctuation similarity to obtain the association value between the abnormality of each type of index of each patient and each type of pressure data; Combine the change situation of the difference index corresponding to the intake of each type of food of each patient on two adjacent days, each type of pressure data of each day within the current time period, and the association value to obtain the degree of intervention to be performed on each type of food of each patient.

[0076] For a patient, if there are multiple moments of similar fluctuations between a certain type of index and the pressure data, and the degree of similarity is relatively high, it indicates that the correlation between this type of index and the pressure data is relatively high; if the degree of abnormality of the pressure data corresponding to the moment of similar fluctuation is relatively small, it is considered that the possibility of the change in the proportion of food intake causing the abnormality of the current patient's pressure data is relatively small.

[0077] Next, taking any type of pressure data as an example for illustration, the method provided in this embodiment can be used to process another type of pressure data.

[0078] Specifically, any type of pressure data is denoted as the first type of pressure data. Calculate the first average value of the difference index corresponding to the first type of pressure data within the current time period of the candidate patient, and the second average value of the difference index corresponding to the index to be evaluated within the current time period of the candidate patient. Calculate the minimum value of the fluctuation similarity degree corresponding to all adjacent reference days of the index to be evaluated of the candidate patient. According to the ratio between the first average value and the second average value, the proportion of the number of reference days, and the minimum value, obtain the correlation value between the abnormality of the index to be evaluated of the candidate patient and the first type of pressure data. The ratio between the first average value and the second average value, the proportion of the number of reference days, and the minimum value are all positively correlated with the correlation value.

[0079] Among them, the positive correlation means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. It can be an additive relationship, a multiplicative relationship, etc., which is determined by the actual application.

[0080] In this embodiment, a specific calculation formula for the correlation value is given. The correlation value between the abnormality of the j-th type of index of the i-th patient and the m-th type of pressure data can be expressed as:

[0081]

[0082] Among them, represents the correlation value between the abnormality of the j-th type of index of the i-th patient and the m-th type of pressure data; represents the average value of the difference index corresponding to the m-th type of pressure data for all days within the current time period of the i-th patient, that is, the first average value; represents the average value of the difference index corresponding to the j-th type of index for all days within the current time period of the i-th patient, that is, the second average value; represents the number of reference days of the j-th type of index of the i-th patient, R represents the number of days within the current time period, represents the minimum value of the fluctuation similarity degree corresponding to all reference days of the j-th type of index of the i-th patient.

[0083] represents the proportion of the number of reference days of the j-th type of index of the i-th patient. The larger this proportion, the longer the fluctuation similarity duration between the j-th type of index and the m-th type of pressure data of the i-th patient. When the value of is larger, the proportion of the number of reference days of the j-th type of index of the i-th patient is larger, and the minimum value of the fluctuation similarity degree corresponding to all reference days of the j-th type of index of the i-th patient is larger, it indicates that the correlation between the j-th type of index and the m-th type of pressure data of the i-th patient is stronger, that is, the correlation value between the abnormality of the j-th type of index and the m-th type of pressure data of the i-th patient is larger.

[0084] The above steps obtained the correlation values between the abnormalities of each type of index and each type of pressure data based on the historical eating habits of a certain patient with gestational hypertension, which were used to reflect the possibility that the change of a single eating habit-related index leads to blood pressure abnormalities. Next, the degree to which the eating habits of the patient need to be intervened in the current state was obtained by combining the index data obtained after the patient's daily meals.

[0085] If the higher the possibility that the change of a certain index of a patient leads to blood pressure abnormalities, and the degree of abnormality of this index obtained after the patient's meal on the current day is greater than that of the previous day compared with other patients, and the current blood pressure of the patient is higher than the patient's own historical value, it means that the greater the degree to which the patient's nutritional plan in this dimension needs to be intervened in the current state.

[0086] For any type of food:

[0087] For the first type of pressure data, calculate the second ratio between the first type of pressure data of the candidate patient on the current day and the average value of the first type of pressure data of all other days except the current day within the current time period; where the current day is the last day within the current time period; calculate the third average value of the correlation values between the abnormalities of all the candidate patient's indexes and the first type of pressure data; the ratio of the correlation value between the abnormality of the intake of this type of food of the candidate patient and the first type of pressure data to the third average value is denoted as the third ratio; according to the second ratio, the fluctuation degree of the intake of this type of food of the candidate patient in the last two days within the current time period, and the third ratio, the intervention factor of this type of food of the candidate patient under the first type of pressure data is obtained, and the second ratio, the fluctuation degree of the intake of this type of food of the candidate patient in the last two days within the current time period, and the third ratio are all positively correlated with the intervention factor.

[0088] Among them, the positive correlation means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. It can be an additive relationship, a multiplicative relationship, etc., which is determined by the actual application.

[0089] In this embodiment, the specific calculation formula of the intervention factor is given. The intervention factor of the t-th type of food of the i-th patient under the m-th type of pressure data can be expressed as:

[0090]

[0091] Among them, represents the intervention factor of the t-th type of food of the i-th patient under the m-th type of pressure data, represents the m-th type of pressure data of the i-th patient on the current day, represents the average value of the m-th type of pressure data of all other days except the current day within the current time period of the i-th patient, Represents the correlation value between the abnormality of the intake of the t-th type of food of the i-th patient and the m-th type of stress data. Represents the third average value of the correlation value between the abnormalities of all indicators of the i-th patient and the m-th type of stress data. Represents the degree of fluctuation of the intake of the t-th type of food in the last two days within the current time period of the i-th patient.

[0092] Represents the second ratio. The larger the second ratio, the higher the m-th type of stress data of the i-th patient relative to its own historical value. Represents the third ratio. The larger the third ratio, the higher the possibility that the change in the intake of the t-th type of food of the i-th patient causes the abnormality of the m-th type of stress data. When the second ratio is larger, the degree of fluctuation of the intake of the t-th type of food in the last two days within the current time period of the i-th patient is larger, and the third ratio is larger, it indicates that the possibility that the abnormality of the intake of the t-th type of food of the i-th patient causes the abnormality of the m-th type of stress data is higher, that is, the intervention factor of the t-th type of food for the i-th patient under the m-th type of stress data is larger.

[0093] By using the above method, the intervention factor of each type of food for each candidate patient under each type of stress data can be obtained.

[0094] For any type of food: By synthesizing the intervention factors of this type of food for the candidate patient under all types of stress data, the degree of intervention to be performed on this type of food for the candidate patient is obtained. Specifically, the average value of the intervention factors of this type of food for the candidate patient under all types of stress data is determined as the degree of intervention to be performed on this type of food for the candidate patient, that is, the average value of the intervention factors of this type of food for the candidate patient under all types of systolic blood pressure and diastolic blood pressure is used as the degree of intervention to be performed on this type of food for the candidate patient.

[0095] By using the above method, the degree of intervention to be performed on each type of food for each gestational hypertension patient can be obtained.

[0096] Step S4: Determine the intake of each type of food for each patient on the next day by using the degree of intervention to be performed and the said intake.

[0097] In this embodiment, the degree of intervention to be performed on each type of food for each gestational hypertension patient is obtained in step S3. The greater the degree of intervention to be performed, the greater the degree to which the intake of the corresponding type of food needs to be increased on the next day. Next, the intake of each type of food will be dynamically adjusted based on the degree of intervention to be performed to obtain the intake of each type of food for the patient on the next day.

[0098] For any kind of food: Calculate the sum value between the constant 1 and the normalized value of the degree of intervention to be performed on this kind of food for the candidate patient, where the value range of the normalized value of the degree of intervention to be performed is [-1, 1]; Multiply the intake of this kind of food by the candidate patient on the current day by the sum value to obtain the intake of this kind of food by the candidate patient on the next day.

[0099] In this embodiment, the intake of the t-th kind of food by the i-th patient on the next day can be expressed as:

[0100]

[0101] Among them, represents the intake of the t-th kind of food by the i-th patient on the next day, represents the intake of the t-th kind of food by the i-th patient on the current day, represents the degree of intervention to be performed on the t-th kind of food by the i-th patient, and premnmx( ) represents the normalization function.

[0102] represents the normalized value of the degree of intervention to be performed on the t-th kind of food by the i-th patient, and its value range is [-1, 1].

[0103] By using the above method, the intake of each kind of food by each pregnant woman with hypertensive disorder complicating pregnancy on the next day can be obtained.

[0104] Thus far, by using the method provided in this embodiment, the dynamic adjustment of the intakes of different kinds of food by pregnant women with hypertensive disorder complicating pregnancy has been completed.

[0105] In this embodiment, considering the differences in eating habits among different patients with gestational hypertension, such as differences in meal quantity, daily meal frequency, and dietary preferences, the nutritional requirements of different patients vary. Therefore, based on the data aggregation of each type of indicator for all patients with gestational hypertension on a daily basis during the current period, the differences in each type of indicator between each patient and other patients were evaluated, and the corresponding difference indices were obtained. Then, based on the difference between the change in the difference index corresponding to the same type of indicator for two adjacent days of each patient and the change in the difference index corresponding to diastolic blood pressure, the degree of fluctuation similarity was obtained, and the reference days corresponding to each type of indicator for each patient were selected. Further, by combining the difference between the overall distribution of the difference indices corresponding to each type of pressure data and the overall distribution of the difference indices corresponding to each type of indicator for each patient during the current period, the proportion of the number of reference days, and the degree of fluctuation similarity, the impact of changes in their eating habits on blood pressure was analyzed. By combining the change in the difference index corresponding to the intake of each type of food for two adjacent days of each patient, the degree of intervention required for each type of food for each patient was obtained, and then the intake of each type of food for each patient with gestational hypertension on the next day was determined. This embodiment adjusts the nutritional plan of patients based on the individual characteristics of patients with gestational hypertension and the changes in their own eating habits, and dynamically intervenes in the nutritional plan of the patient in a targeted manner according to the impact of each indicator of eating habits on blood pressure, completing the dynamic adjustment of the intake of different types of food for patients with gestational hypertension and improving the effectiveness of the intervention of the nutritional plan for patients with gestational hypertension.

[0106] An embodiment of an auxiliary intervention system for the nutritional plan of patients with gestational hypertension:

[0107] Refer to Figure 2 , which shows the structural block diagram of the auxiliary intervention system for the nutritional plan of patients with gestational hypertension provided by an embodiment of the present invention. The system may include a data acquisition module, a processing module, a calculation module, and an intake determination module.

[0108] Among them, the data acquisition module is used to obtain various indicators of patients with gestational hypertension on a daily basis during the current period, where the indicators include various pressure data, meal frequency, and the intake of different types of food, and the pressure data includes systolic blood pressure and diastolic blood pressure;

[0109] The processing module is used to determine the difference index corresponding to each type of indicator for each patient every day based on the data aggregation of each type of indicator for all the patients on a daily basis during the current period; based on the difference between the change in the difference index corresponding to the same type of indicator for two adjacent days of each patient and the change in the difference index corresponding to diastolic blood pressure, obtain the corresponding degree of fluctuation similarity, and select the reference days corresponding to each type of indicator for each patient;

[0110] A calculation module, configured to obtain the association value between the abnormality of each type of index and each type of pressure data for each patient by combining the difference between the overall distribution of the difference index corresponding to each type of pressure data within the current time period for each patient and the overall distribution of the difference index corresponding to each type of index, the proportion of the number of reference days, and the degree of fluctuation similarity; and obtain the degree of intervention to be performed on each type of food for each patient by combining the change situation of the difference index corresponding to the intake of each type of food for two adjacent days for each patient, each type of pressure data for each day within the current time period, and the association value.

[0111] An intake determination module, configured to determine the intake of each type of food for the next day for each patient by using the degree of intervention to be performed and the intake.

[0112] It should be understood that Figure 2 The structural block diagram of the auxiliary intervention system for the nutritional plan of pregnant women with gestational hypertension and its modules shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented through hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art can understand that the above methods and systems can be implemented using computer-executable instructions and / or included in processor control code. For example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules in this specification can be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips and transistors, or programmable hardware devices such as field programmable gate arrays and programmable logic devices, but also by software executed by various types of processors, or by a combination of the above hardware circuits and software (for example, firmware).

[0113] For more details about the above-mentioned various modules, reference can be made to other parts of this specification, and no further elaboration will be provided here.

[0114] In other embodiments, an auxiliary intervention device for the nutritional plan of pregnant women with gestational hypertension is further provided, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes the above-mentioned welding control method applied to the pulse welding machine. The device can specifically be a chip, component, or module. The chip can include a connected processor and a memory; wherein, the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute the auxiliary intervention method for the nutritional plan of pregnant women with gestational hypertension provided in the above embodiments.

[0115] In other embodiments, a computer program product is further provided. When the computer program product runs on a computer, it causes the computer to execute the above - related steps to implement the auxiliary intervention method for the nutritional plan of pregnant women with hypertensive disorders of pregnancy provided in the above - mentioned embodiments.

[0116] In other embodiments, a computer - readable storage medium is further provided. The computer - readable storage medium stores computer program code. When the computer program code runs on a computer, it causes the computer to execute the above - related method steps to implement the auxiliary intervention method for the nutritional plan of pregnant women with hypertensive disorders of pregnancy provided in the above - mentioned embodiments.

[0117] Among them, the provided system, electronic device, computer program product, and computer - readable storage medium are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can refer to the beneficial effects in the corresponding methods provided above, and will not be elaborated here.

[0118] It should be noted that the above - mentioned are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An auxiliary intervention method for the nutritional plan of patients with gestational hypertension, characterized in that, The method includes the following steps: Obtain various indicators of patients with gestational hypertension every day during the current period, where the indicators include various pressure data, meal frequencies, and intakes of different types of food, and the pressure data includes systolic blood pressure and diastolic blood pressure; Based on the data aggregation of each type of indicator of all the patients every day during the current period, determine the difference index corresponding to each type of indicator for each patient every day; according to the difference between the change situation of the difference index corresponding to the same type of indicator of each patient on two adjacent days and the change situation of the difference index corresponding to the diastolic blood pressure, obtain the corresponding fluctuation similarity degree, and screen the reference days corresponding to each type of indicator for each patient; Combine the difference between the overall distribution of the difference index corresponding to each type of pressure data of each patient during the current period and the overall distribution of the difference index corresponding to each type of indicator, the proportion of the number of reference days, and the fluctuation similarity degree to obtain the correlation value between the abnormal situation of each type of indicator and each type of pressure data for each patient; combine the change situation of the difference index corresponding to the intake of each type of food of each patient on two adjacent days, each type of pressure data every day during the current period, and the correlation value to obtain the degree of intervention to be carried out for each type of food for each patient; Use the degree of intervention to be carried out and the intake to determine the intake of each type of food for each patient on the next day; The determining the difference index corresponding to each type of indicator for each patient every day based on the data aggregation of each type of indicator of all the patients every day during the current period includes: Cluster all the patients based on the indicators to be evaluated on the days to be analyzed for all the patients, and obtain the difference index corresponding to the indicators to be evaluated on the days to be analyzed for the candidate patients according to the number of patients in the cluster with the largest number of patients, the number of patients in the cluster where the candidate patients are located, and the difference of the indicators to be evaluated between the cluster where the candidate patients are located and the center point of the corresponding cluster; The days to be analyzed are any days during the current period, the candidate patients are any patients with gestational hypertension, and the indicators to be evaluated are any type of indicator.

2. The auxiliary intervention method for the nutritional regimen of patients with gestational hypertension according to claim 1, characterized in that, The obtaining the difference index corresponding to the indicators to be evaluated on the days to be analyzed for the candidate patients according to the number of patients in the cluster with the largest number of patients, the number of patients in the cluster where the candidate patients are located, and the difference of the indicators to be evaluated between the cluster where the candidate patients are located and the center point of the corresponding cluster includes: Calculate the first ratio between the number of patients in the cluster with the largest number of patients and the number of patients in the cluster where the candidate patients are located; According to the difference of the indicators to be evaluated between the candidate patients and the center point of the cluster where they are located and the first ratio, obtain the difference index corresponding to the indicators to be evaluated on the days to be analyzed for the candidate patients, the first ratio has a positive correlation with the difference index, and the difference of the indicators to be evaluated between the candidate patients and the center point of the cluster where they are located has a negative correlation with the difference index.

3. The auxiliary intervention method for the nutritional regimen of pregnant women with gestational hypertension according to claim 1, wherein, The obtaining the corresponding fluctuation similarity degree according to the difference between the change situation of the difference index corresponding to the same type of indicator of each patient on two adjacent days and the change situation of the difference index corresponding to the diastolic blood pressure includes: Take the normalized result of the difference between the difference index corresponding to the same type of indicator of the candidate patient on the later day and the previous day among two adjacent days as the fluctuation degree of the same type of indicator of the candidate patient on two adjacent days; Calculate the fluctuation similarity degree corresponding to each type of index for two adjacent days of a candidate patient based on the difference between the fluctuation degree of each type of index and the corresponding fluctuation degree of diastolic blood pressure for two adjacent days of the candidate patient. There is a negative correlation between the difference between the fluctuation degree of each type of index and the corresponding fluctuation degree of diastolic blood pressure and the fluctuation similarity degree.

4. An auxiliary intervention method for a nutritional regimen for patients with gestational hypertension according to claim 3, characterized in that Screen the reference days corresponding to each type of index for each patient, including: For the index to be evaluated: If the fluctuation similarity degree corresponding to the index to be evaluated for two adjacent days of a candidate patient is greater than a preset similarity threshold, then the corresponding two adjacent days are used as the reference days corresponding to the index to be evaluated for the candidate patient.

5. An auxiliary intervention method for a nutritional regimen for patients with gestational hypertension according to claim 4, characterized in that, Combining the difference between the overall distribution of the difference index corresponding to each type of pressure data and the overall distribution of the difference index corresponding to each type of index within the current time period of each patient, the proportion of the number of reference days, and the fluctuation similarity degree, to obtain the correlation value between the abnormal condition of each type of index and each type of pressure data for each patient, including: Calculate the first average value of the difference index corresponding to the first type of pressure data within the current time period of the candidate patient, and the second average value of the difference index corresponding to the index to be evaluated within the current time period of the candidate patient; calculate the minimum value of the fluctuation similarity degree corresponding to all adjacent reference days corresponding to the index to be evaluated for the candidate patient; Based on the ratio between the first average value and the second average value, the proportion of the number of reference days, and the minimum value, obtain the correlation value between the abnormal condition of the index to be evaluated for the candidate patient and the first type of pressure data. The ratio between the first average value and the second average value, the proportion of the number of reference days, and the minimum value are all positively correlated with the correlation value; The first type of pressure data is any type of pressure data.

6. The auxiliary intervention method for the nutritional regimen of patients with gestational hypertension according to claim 5, characterized in that, Combining the change situation of the difference index corresponding to the intake of each type of food for two adjacent days of each patient, each type of pressure data for each day within the current time period, and the correlation value, to obtain the degree of intervention required for each type of food for each patient, including: For any type of food: For the first type of pressure data, calculate the second ratio between the first type of pressure data of the candidate patient on the current day and the average value of the first type of pressure data of all other days except the current day within the current time period; where the current day is the last day within the current time period; calculate the third average value of the correlation value between the abnormal condition of all the indexes of the candidate patient and the first type of pressure data; denote the ratio of the correlation value between the abnormal condition of the intake of this type of food of the candidate patient and the first type of pressure data and the third average value as the third ratio; based on the second ratio, the fluctuation degree of the intake of this type of food for the last two days within the current time period of the candidate patient, and the third ratio, obtain the intervention factor of this type of food for the candidate patient under the first type of pressure data. The second ratio, the fluctuation degree of the intake of this type of food for the last two days within the current time period of the candidate patient, and the third ratio are all positively correlated with the intervention factor; Integrate the intervention factors of this type of food for the candidate patient under all types of pressure data to obtain the degree of intervention required for this type of food for the candidate patient.

7. An auxiliary intervention method for a nutritional regimen for patients with gestational hypertension according to claim 6, characterized in that, The intervention factor of this type of food for the comprehensive candidate patients under all types of stress data is obtained to determine the degree of intervention required for this type of food for the candidate patients, including: The average value of the intervention factor of this type of food for the candidate patients under all types of stress data is determined as the degree of intervention required for this type of food for the candidate patients.

8. An auxiliary intervention method for a nutritional regimen for patients with gestational hypertension according to claim 6, characterized in that, The determination of the intake of each type of food for each patient on the next day by using the degree of intervention required and the intake includes: For any one type of food: Calculate the sum value between 1 and the normalized value of the intervention factor of this type of food for the candidate patients, and the value range of the normalized value of the intervention factor is [-1, 1]; The product of the intake of this type of food for the candidate patients on the current day and the sum value is used as the intake of this type of food for the candidate patients on the next day.

9. An auxiliary intervention system for a nutritional plan for patients with gestational hypertension, the system being used to execute the method described in claim 1, characterized in that, The system includes: A data acquisition module, which is used to obtain various indicators of pregnant women with gestational hypertension every day during the current time period, where the indicators include various types of stress data, meal frequencies, and intakes of different types of food, and the stress data includes systolic blood pressure and diastolic blood pressure; A processing module, which is used to determine the difference index corresponding to each type of indicator for each patient every day based on the data aggregation of each type of indicator for all patients during the current time period; obtain the corresponding fluctuation similarity degree according to the difference between the change situation of the difference index corresponding to the same type of indicator for each patient in two adjacent days and the change situation of the difference index corresponding to the diastolic blood pressure, and screen the reference days corresponding to each type of indicator for each patient; A calculation module, which is used to obtain the correlation value between the abnormal situation of each type of indicator and each type of stress data for each patient by combining the difference between the overall distribution of the difference index corresponding to each type of stress data and the overall distribution of the difference index corresponding to each type of indicator for each patient during the current time period, the proportion of the number of reference days, and the fluctuation similarity degree; obtain the degree of intervention required for each type of food for each patient by combining the change situation of the difference index corresponding to the intake of each type of food for each patient in two adjacent days, each type of stress data every day during the current time period, and the correlation value; An intake determination module, which is used to determine the intake of each type of food for each patient on the next day by using the degree of intervention required and the intake; The processing module is specifically used for: clustering all patients based on the evaluation indicators to be analyzed for all patients on the day to be analyzed, and obtaining the difference index corresponding to the evaluation indicators to be analyzed for the candidate patients on the day to be analyzed according to the number of patients in the cluster with the largest number of patients, the number of patients in the cluster where the candidate patient is located, and the difference in the evaluation indicators between the cluster where the candidate patient is located and the center point of the corresponding cluster; the day to be analyzed is any day during the current time period, the candidate patient is any pregnant woman with gestational hypertension, and the evaluation indicator is any type of indicator.

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