Auxiliary intervention method and system for nutrition plan of hypertensive gestational patient

Abstract

The invention relates to the technical field of medical informatics, in particular to an auxiliary intervention method and system for a nutrition scheme of a hypertensive gestational patient. The method comprises the following steps: acquiring various indexes of a gestational hypertension patient every day; determining a corresponding difference index based on the data aggregation condition of each type of indexes; according to the difference between the change of the difference index corresponding to the same type of indexes of each patient in two adjacent days and the change condition of the difference index corresponding to the diastolic 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 indexes, calculating the pressure data of each patient; obtaining an association value between the abnormality of each type of index and each type of pressure data; and obtaining a to-be-intervened degree by combining the change condition of the difference index corresponding to the intake of each type of food of each patient in two adjacent days and the associated value, and further determining the intake of each type of food in the next day. According to the invention, the intake of different kinds of food of the gestational hypertension patient can be dynamically adjusted.

Description

Technical Field

[0001] The present invention relates to the technical field of medical informatics, and in particular to an auxiliary intervention method and system for a nutritional program of a patient with gestational hypertension. Background Art

[0002] Hypertension during pregnancy is a disease that occurs during pregnancy. When the disease is severe, it may affect the health of mother and baby. Its etiology is complex and the pathogenesis is still unclear. Reasonable eating habits are conducive to maintaining blood pressure stability, thereby preventing and controlling hypertension during pregnancy and improving perinatal conditions. Therefore, it is necessary to intervene in the nutritional regimen of different patients with hypertension during pregnancy.

[0003] When existing technologies intervene in the nutritional plan of patients with gestational hypertension, they usually make recommendations on the patient's eating habits based on the relevant data of a single physiological dimension test of a patient. However, due to differences in individual physical constitutions and the different effects of different stages of pregnancy on the patient's physical condition, the degree of demand for various nutrients in patients at different times varies; existing methods are unable to adjust the nutritional plan based on changes in 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 nutritional plan based on the changes in 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 the nutritional plan of patients with gestational hypertension. The technical scheme adopted is as follows: In a first aspect, the present invention provides a method for assisting intervention in the nutritional regimen of a patient with hypertension complicating pregnancy, the method comprising the following steps: Obtain various indicators of patients with gestational hypertension every day during the current period, including various pressure data, meal frequency and intake of different types of food, and pressure data including systolic and diastolic blood pressure; Based on the data aggregation of each type of indicator every day in the current time period for all the patients, determine the difference index corresponding to each type of indicator of each patient every day; according to the difference between the change of the difference index corresponding to the same type of indicator of each patient in two consecutive days and the change of the difference index corresponding to the diastolic blood pressure, obtain the corresponding fluctuation similarity, and select the reference day corresponding to each type of indicator of each patient; Combine the difference between the overall distribution of the difference index corresponding to each type of stress data of each patient in the current time period and the overall distribution of the difference index corresponding to each type of indicator, the number proportion of reference days and the similarity of fluctuations, and obtain the correlation value between the abnormality of each type of indicator of each patient and each type of stress data; Combine the change of the difference index corresponding to the intake of each type of food of each patient in two consecutive days, each type of stress data of each day in the current time period and the correlation value, and obtain the degree of intervention for each type of food of each patient; The level of intervention and the intake are used to determine the intake of each food category for each patient for the next day.

[0005] Preferably, the step of determining the difference index corresponding to each type of indicator of each patient every day based on the data aggregation of each type of indicator of all patients every day in the current time period includes: All patients are clustered based on the indicators to be evaluated for all patients' days to be analyzed, and the difference index corresponding to the indicators to be evaluated for the candidate patients' days to be analyzed is obtained 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 in the indicators to be evaluated between the cluster where the candidate patients are located and the center point of the corresponding cluster; The day to be analyzed is any day in the current time period, the candidate patient is any patient with gestational hypertension, and the indicator to be evaluated is any type of indicator.

[0006] Preferably, obtaining the difference index corresponding to the indicator to be evaluated for the candidate patient 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 indicator to be evaluated between the cluster where the candidate patient is located and the center point of the corresponding cluster includes: Calculating a 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 in the indicator to be evaluated between the candidate patient and the center point of the cluster to which he / she belongs and the first ratio, a difference index corresponding to the indicator to be evaluated of the candidate patient on the day to be analyzed is obtained, the first ratio is positively correlated with the difference index, and the difference in the indicator to be evaluated between the candidate patient and the center point of the cluster to which he / she belongs is negatively correlated with the difference index.

[0007] Preferably, obtaining the corresponding fluctuation similarity according to the difference between the change of the difference index corresponding to the same type of indicator of each patient on two consecutive days and the change of the difference index corresponding to the diastolic blood pressure includes: The normalized result of the difference between the difference indexes corresponding to the same type of indicators of the candidate patient on the next day and the previous day on two consecutive days is taken as the fluctuation degree of the same type of indicators of the candidate patient on two consecutive days; According to the difference between the fluctuation degree of each type of indicator of the candidate patient on two consecutive days and the fluctuation degree corresponding to the diastolic blood pressure, the fluctuation similarity degree corresponding to each type of indicator of the candidate patient on two consecutive days is calculated, and the difference between the fluctuation degree of each type of indicator and the fluctuation degree corresponding to the diastolic blood pressure is negatively correlated with the fluctuation similarity degree.

[0008] Preferably, the reference day corresponding to each type of indicator of each patient is screened, including: For the indicator to be evaluated: if the fluctuation similarity of the indicator to be evaluated of the candidate patient on two consecutive days is greater than the preset similarity threshold, the corresponding two consecutive days will be used as the reference days for the indicator to be evaluated of the candidate patient.

[0009] Preferably, the method combines the difference between the overall distribution of the difference index corresponding to each type of pressure data in the current time period of each patient and the overall distribution of the difference index corresponding to each type of indicator, the number proportion of reference days and the degree of fluctuation similarity to obtain the correlation value between the abnormality of each type of indicator of each patient and each type of pressure data, including: Calculate the first average value of the difference index corresponding to the first type of pressure data in the current time period of the candidate patient, and the second average value of the difference index corresponding to the indicator to be evaluated in the current time period of the candidate patient; calculate the minimum value of the fluctuation similarity corresponding to all adjacent reference days corresponding to the indicator 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, a correlation value between the abnormality of the candidate patient's to-be-evaluated indicator and the first type of pressure data is obtained, wherein 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.

[0010] Preferably, the step of combining the change in the difference index corresponding to the intake of each type of food of each patient in two consecutive days, each type of stress data of each day in the current time period and the associated value to obtain the degree of intervention for each type of food of each patient includes: 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 in the current time period; wherein the current day is the last day in 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; record the ratio of the correlation value between the abnormality of the candidate patient's intake of this type of food and the first type of pressure data and the third average value as the third ratio; obtain the intervention factor of this type of food for the candidate patient under the first type of pressure data 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 in the current time period and the third ratio, and the second ratio, the fluctuation degree of the intake of this type of food of the candidate patient in the last two days in the current time period and the third ratio are all positively correlated with the intervention factor; The intervention factor of this type of food under all types of stress data of the candidate patient is integrated to obtain the degree of intervention required for this type of food of the candidate patient.

[0011] Preferably, the step of comprehensively analyzing the intervention factor of the food of the candidate patient under all kinds of stress data to obtain the degree of intervention of the food of the candidate patient includes: The average value of the intervention factor of the food of the candidate patient under all kinds of stress data is determined as the degree of intervention for the food of the candidate patient.

[0012] Preferably, the method of determining the intake of each type of food for each patient the next day by using the degree to be intervened and the intake comprises: For any type of food: Calculate the sum of the constant 1 and the normalized value of the degree of intervention for the type of food of the candidate patient, where the range of the normalized value of the degree of intervention is [-1, 1]; The product of the candidate patient's intake of the type of food on the current day and the sum value is taken as the candidate patient's intake of the type of food on the next day.

[0013] In a second aspect, the present invention provides an auxiliary intervention system for a nutritional regimen of a patient with gestational hypertension, the system comprising: The data collection module is used to obtain various indicators of patients with gestational hypertension every day in the current time period, including various pressure data, meal frequency and intake of different types of food, and pressure data includes systolic blood pressure and diastolic blood pressure; A processing module, for determining the difference index corresponding to each type of indicator of each patient every day based on the data aggregation of each type of indicator of all the patients in the current time period; obtaining the corresponding fluctuation similarity according to the difference between the change of the difference index corresponding to the same type of indicator of each patient in two consecutive days and the change of the difference index corresponding to the diastolic blood pressure, and screening the reference day corresponding to each type of indicator of each patient; A calculation module is used to obtain the correlation value between the abnormality of each type of indicator and each type of pressure data of each patient by combining the difference between the overall distribution of the difference index corresponding to each type of pressure data of each patient in the current time period and the overall distribution of the difference index corresponding to each type of indicator, the quantity proportion of the reference day and the similarity of fluctuation; and obtain the degree of intervention for each type of food of each patient by combining the change of the difference index corresponding to the intake of each type of food of each patient in two consecutive days, each type of pressure data of each day in the current time period and the correlation value; The intake determination module is used to determine the intake of each type of food for each patient in the next day by using the degree of intervention and the intake.

[0014] The present invention has at least the following beneficial effects: The present invention takes into account the differences in dietary habits of different patients with gestational hypertension, such as the amount of meals, daily meal frequency, and dietary preferences, which make the nutritional needs of different patients different. Therefore, based on the data aggregation of each type of indicator every day in the current time period of all patients with gestational hypertension, the difference between each patient and other patients in each type of indicator is evaluated, and the corresponding difference index is obtained. Then, according to the difference between the change of the difference index corresponding to the same type of indicator of each patient in two consecutive days and the change of the difference index corresponding to the diastolic pressure, the fluctuation similarity is obtained, and the reference day corresponding to each type of indicator of each patient is screened. The overall distribution of the difference index corresponding to each type of pressure data in the current time period of each patient is further combined with the difference index corresponding to each type of indicator. The differences in the overall distribution of the index, the proportion of the number of reference days and the similarity of fluctuations were analyzed to analyze the impact of changes in their eating habits on blood pressure, and combined with the changes in the difference index corresponding to the intake of each type of food for each patient on two consecutive days, the degree of intervention 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. The present invention adjusts the patient's nutritional plan based on the individual characteristics of the patient with gestational hypertension and the changes in her own eating habits, and conducts targeted dynamic intervention on the patient's nutritional plan according to the degree of influence of various indicators of eating habits on blood pressure, completes the dynamic adjustment of the intake of different types of food in patients with gestational hypertension, and improves the effectiveness of nutritional plan intervention for patients with gestational hypertension. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A flowchart of an auxiliary intervention method for a nutritional program for patients with gestational hypertension provided by an embodiment of the present invention; Figure 2 This is a structural block diagram of an auxiliary intervention system for a nutritional program for patients with gestational hypertension provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the auxiliary intervention method and system for the nutritional program of patients with gestational hypertension proposed by the present invention are described in detail as follows in combination with the accompanying drawings and preferred embodiments.

[0018] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0019] The specific scheme of the auxiliary intervention method and system for the nutritional program of patients with gestational hypertension provided by the present invention is described in detail below with reference to the accompanying drawings.

[0020] An auxiliary intervention method embodiment of a nutritional program for patients with gestational hypertension: The specific scenario targeted by this embodiment is: in the process of auxiliary intervention treatment for patients with hypertension during pregnancy, the impact of changes in a certain indicator in their eating habits on blood pressure is analyzed in combination with the dining situation of the patients during pregnancy, so as to dynamically adjust the nutritional intake of the patients during pregnancy.

[0021] This embodiment proposes an auxiliary intervention method for the nutritional program of patients with hypertension during pregnancy, such as Figure 1 As shown, the auxiliary intervention method of a nutritional program for patients with gestational hypertension in this embodiment includes the following steps: Step S1, obtaining various indicators of the patient with gestational hypertension every day in the current time period, wherein the indicators include various pressure data, meal frequency and intake of different types of food, and the pressure data include systolic pressure and diastolic pressure.

[0022] First, for multiple patients with gestational hypertension, the weight of each type of food to be ingested by these patients before they eat is obtained, and the intake of each type of food per patient per meal is calculated according to the intake of each type of food per patient per day in the current time period; the types of food include meat, vegetables, fruits, starch, etc., and in specific applications, the implementer sets it 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 it according to the specific situation. Then, the frequency of meals per patient per day in the current time period is counted, and the blood pressure data of each patient is collected at a fixed time every day using an electronic blood pressure meter. The blood pressure data includes systolic pressure and diastolic pressure. The current time period is a set of all historical moments whose time interval with the current moment is less than or equal to the preset time length. In this embodiment, the preset time length is 30 days. In specific applications, the implementer can set it according to the specific situation.

[0023] Systolic blood pressure, diastolic blood pressure, meal frequency and intake of each type of food were each taken as a category of indicators, that is, various indicators were collected every day from multiple patients with gestational hypertension in the current time period.

[0024] Step S2, based on the data aggregation of each type of indicator every day in the current time period for all the patients, determine the difference index corresponding to each type of indicator of each patient every day; according to the difference between the change of the difference index corresponding to the same type of indicator of each patient in two consecutive days and the change of the difference index corresponding to the diastolic blood pressure, obtain the corresponding fluctuation similarity, and screen the reference day corresponding to each type of indicator of each patient.

[0025] Due to differences in eating habits among individuals, for example, different patients have different meal sizes, different daily meal frequencies, and different dietary preferences. As a result, the proportion of different types of food intake in each meal varies, which leads to differences in nutritional needs among different patients. Therefore, the characteristic dimensions of a single patient's eating habits are obtained by comparing the differences in diet-related data between each patient and other patients.

[0026] Next, take one day in the current time period, one patient among all patients with gestational hypertension, and one category of indicators among all indicators as an example for explanation.

[0027] Specifically, any day in the current time period is recorded as a day to be analyzed, any patient with gestational hypertension among all patients with gestational hypertension is recorded as a candidate patient, and any type of index is marked as an index to be evaluated.

[0028] All patients are clustered based on their indicators to be analyzed and evaluated to obtain multiple clusters. In this embodiment, the ISODATA algorithm is used for clustering, and the initial number of categories is set to 3, the maximum number of iterations is set to 5, and the number of initial samples per category is set to , where N is the number of patients, The ISODATA algorithm is a prior art and will not be described in detail here.

[0029] Analyze the difference between each type of indicator of a single patient and each type of indicator of other patients. If the number of patients in the cluster where the current patient is located is small, and the corresponding indicators of the current patient and other patients in the cluster are not similar, then the difference index of the indicator between the current patient and other patients is large.

[0030] Based on the above characteristics, a 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 is calculated; according to the difference in the indicator to be evaluated between the candidate patient and the center point of the cluster to which he / she belongs and the first ratio, a difference index corresponding to the indicator to be evaluated of the candidate patient to be analyzed is obtained, the first ratio is positively correlated with the difference index, and the difference in the indicator to be evaluated between the candidate patient and the center point of the cluster to which he / she belongs is negatively correlated with the difference index.

[0031] Among them, a 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 actual application; a negative correlation 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 division relationship, etc., which is determined by actual application.

[0032] In this embodiment, a specific calculation formula of the difference index is given, and the difference index corresponding to the j-th indicator of the i-th patient on the k-th day can be expressed as: in, represents the difference index corresponding to the j-th indicator of the i-th patient on the k-th day, It represents the number of patients in the cluster with the largest number of patients in the clustering results based on the j-th category index of all patients on the k-th day. It represents the number of patients in the cluster where the i-th patient belongs in the clustering result based on the j-th indicator of all patients on the k-th day. It represents the difference of the j-th index between the i-th patient and the center point of his cluster in the clustering result based on the j-th index of all patients on the k-th day. Indicates the preset first adjustment parameter.

[0033] The preset adjustment parameter is introduced into the calculation formula of the difference index in this embodiment to prevent the denominator from being 0. 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 of the difference between the same indicators is: the absolute value of the difference between them is taken as their difference. It represents the first ratio. The larger the first ratio is, the smaller the number of patients in the cluster where the ith patient is located. When the number of patients in the cluster where the ith patient is located is smaller and the difference in the jth index between the ith patient and the center point of the cluster where the ith patient is located is larger, it means that the difference between the jth index of the ith patient and other patients on the kth day is larger, that is, the difference index corresponding to the jth index of the ith patient on the kth day is larger.

[0034] Changes in the eating habits of patients with gestational hypertension will have a certain impact on their blood pressure. For example, an increase in the amount and frequency of meals may cause an increase in the patient's blood pressure, and a large change in the proportion of a certain food intake may affect the blood pressure, which is not conducive to maintaining the stability of the patient's blood pressure. Due to individual physiological differences among different patients, the degree of impact of changes in eating habits on blood pressure varies among different patients. Therefore, it is necessary to analyze the degree of impact of a single dimension on their own blood pressure based on the historical data of a single patient's eating habits. If a change in a certain indicator can cause a change in blood pressure, for example, a change in the proportion of meat food intake in a patient's diet can cause blood pressure to fluctuate in a similar manner, the greater the correlation between this indicator and blood pressure fluctuations.

[0035] Therefore, the normalized result of the difference between the difference indexes corresponding to the same type of indicators on the next day and the previous day of the two consecutive days in the current time period of the candidate patient is used as the fluctuation degree of the same type of indicators on the two consecutive days of the candidate patient; in the current time period, each type of indicator of the candidate patient corresponds to a fluctuation degree on each of the two consecutive days. According to the difference between the fluctuation degree of each type of indicator on the two consecutive days of the candidate patient and the fluctuation degree corresponding to the diastolic pressure, the fluctuation similarity degree corresponding to each type of indicator on the two consecutive days of the candidate patient is calculated, and the difference between the fluctuation degree of each type of indicator and the fluctuation degree corresponding to the diastolic pressure is negatively correlated with the fluctuation similarity degree.

[0036] 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 practical applications.

[0037] In this embodiment, a specific calculation formula for the degree of fluctuation similarity is given. The degree of fluctuation similarity corresponding to the j-th indicator of the i-th patient on the k-1th day and the kth day can be expressed as: in, It indicates the similarity of the fluctuations of the j-th indicator on the k-1th day and the kth day of the i-th patient. It indicates the fluctuation degree of the j-th indicator of the i-th patient on the k-1 day and the k-th day. represents the fluctuation degree of diastolic blood pressure between the k-1 day and the k day of the i-th patient, sigmoid ( ) represents the normalization function, Indicates the preset second adjustment parameter. Indicates the absolute value sign.

[0038] The purpose of introducing the preset second adjustment parameter in the fluctuation similarity is to prevent the denominator from being 0. In this embodiment, the preset second adjustment parameter is 0.01. In specific applications, the implementer can set it according to specific circumstances. It represents the difference between the fluctuation degree of the j-th indicator on the k-1 day and the k-th day and the fluctuation degree of the diastolic blood pressure of the i-th patient. The smaller the value, the smaller the difference between the two, and the greater the similarity of the fluctuation corresponding to the j-th indicator on the k-1 day and the k-th day of the i-th patient.

[0039] For the indicator to be evaluated: if the fluctuation similarity of the indicator to be evaluated of the candidate patient on two consecutive days is greater than the preset similarity threshold, the corresponding two consecutive days are used as the reference days for the indicator to be evaluated of the candidate patient. In this embodiment, the preset similarity threshold is 0.5, and in specific applications, the implementer can set it according to the specific situation.

[0040] By using the method provided in this embodiment, multiple reference days corresponding to each type of indicator of each patient are obtained.

[0041] Step S3, combining the difference between the overall distribution of the difference index corresponding to each type of pressure data in the current time period of each patient and the overall distribution of the difference index corresponding to each type of indicator, the number proportion of reference days and the degree of fluctuation similarity, to obtain the correlation value between the abnormality of each type of indicator of each patient and each type of pressure data; combining the change of the difference index corresponding to the intake of each type of food of each patient in two consecutive days, each type of pressure data every day in the current time period and the said correlation value, to obtain the degree of intervention for each type of food of each patient.

[0042] For a patient, if a certain type of indicator and pressure data have multiple similar fluctuation moments, and the similarity is high, it means that the correlation between this type of indicator and the pressure data is high; if the abnormality of the pressure data corresponding to the similar fluctuation moments is small, it is believed that the change in the proportion of food intake is less likely to cause abnormal pressure data of the current patient.

[0043] Next, any type of pressure data is used as an example for description. Another type of pressure data may be processed using the method provided in this embodiment.

[0044] Specifically, any type of pressure data is recorded as the first type of pressure data, and the first average value of the difference index corresponding to the first type of pressure data in the current time period of the candidate patient and the second average value of the difference index corresponding to the indicator to be evaluated in the current time period of the candidate patient are calculated; the minimum value of the fluctuation similarity corresponding to all adjacent reference days corresponding to the indicator to be evaluated of the candidate patient is calculated. 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, the correlation value between the abnormality of the indicator to be evaluated of the candidate patient and the first type of pressure data is obtained, and 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.

[0045] 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 practical applications.

[0046] In this embodiment, a specific calculation formula for the correlation value is given, and the correlation value between the abnormality of the j-th indicator of the i-th patient and the m-th pressure data can be expressed as: in, represents the correlation value between the abnormality of the jth indicator of the i-th patient and the m-th pressure data; represents the average value of the difference index corresponding to the m-th type of pressure data of all days in 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 indicator of all days in the current time period of the i-th patient, that is, the second average value; represents the number of reference days corresponding to the jth indicator of the ith patient, R represents the number of days in the current time period, It represents the minimum value of the fluctuation similarity of all reference days corresponding to the j-th indicator of the i-th patient.

[0047] It represents the proportion of reference days corresponding to the j-th indicator of the i-th patient. The larger the proportion, the longer the fluctuation of the j-th indicator of the i-th patient and the m-th pressure data is similar. The larger the value of , the larger the proportion of reference days corresponding to the j-th indicator of the ith patient, and the larger the minimum value of the fluctuation similarity corresponding to all reference days corresponding to the j-th indicator of the ith patient, the stronger the correlation between the j-th indicator of the ith patient and the m-th pressure data, that is, the greater the correlation value between the abnormality of the j-th indicator of the ith patient and the m-th pressure data.

[0048] The above steps obtain the correlation value between the abnormality of each type of indicator and each type of pressure data based on the historical eating habits of a patient with gestational hypertension, which is used to reflect the possibility that changes in a single eating habit-related indicator may lead to abnormal blood pressure. Next, the indicator data obtained after the patient's daily meals are combined to obtain the degree to which the patient's eating habits need to be intervened in the current state.

[0049] If the change in a certain indicator of the patient leads to a higher possibility of abnormal blood pressure, and the degree of abnormality of the indicator obtained after the meal on that day is greater than that of the previous day relative to that of other patients, and the current blood pressure of the patient is higher relative to its historical value, then it means that the degree to which the patient's nutritional plan in this dimension needs to be intervened in the current state is greater.

[0050] For any type of food: For the first category of pressure data, calculate the second ratio between the first category pressure data of the candidate patient on that day and the average value of the first category pressure data of all other days in the current time period except that day; where the today is the last day in 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 category of pressure data; record the ratio of the correlation value between the abnormality of the candidate patient's intake of this type of food and the first category of pressure data and the third average value as the third ratio; obtain the intervention factor of this type of food for the candidate patient under the first category of pressure data based on the second ratio, the fluctuation degree of the candidate patient's intake of this type of food in the last two days in the current time period and the third ratio, and the second ratio, the fluctuation degree of the candidate patient's intake of this type of food in the last two days in the current time period and the third ratio are all positively correlated with the intervention factor.

[0051] 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 practical applications.

[0052] In this embodiment, a specific calculation formula of the intervention factor is given. The intervention factor of the t-th type of food for the i-th patient under the m-th type of stress data can be expressed as: in, represents the intervention factor of the t-th type of food for the i-th patient under the m-th type of stress data, represents the mth type of pressure data of the i-th patient on that day, represents the average value of the mth type of pressure data of the i-th patient in the current time period on all days except the current day. represents the correlation value between the abnormal intake of the t-th type of food of the ith patient and the m-th type of pressure data, represents the third average value of the correlation value between the abnormality of all indicators of the i-th patient and the m-th type of pressure data, It indicates the fluctuation degree of the intake of the tth type of food in the last two days of the i-th patient in the current time period.

[0053] It represents the second ratio. The larger the second ratio is, the higher the pressure data of the mth category of the i-th patient is relative to its own historical value. Represents the third ratio. The larger the third ratio is, the higher the possibility that the change in the intake of the tth type of food of the i-th patient leads to abnormality in the m-th type of pressure data. When the second ratio is larger, the fluctuation degree of the intake of the tth type of food of the i-th patient in the last two days of the current time period is larger, and the third ratio is larger, it means that the abnormal intake of the tth type of food of the i-th patient leads to abnormality in the m-th type of pressure data. The higher the possibility that the abnormality of the tth type of food intake of the i-th patient leads to abnormality in the m-th type of pressure data, that is, the greater the intervention factor of the tth type of food of the i-th patient under the m-th type of pressure data.

[0054] By using the above method, the intervention factor of each type of food under each type of stress data of the candidate patient can be obtained.

[0055] For any type of food: the intervention factor of this type of food under all types of pressure data of the candidate patient is comprehensively considered to obtain the degree of intervention for this type of food of the candidate patient. Specifically, the average value of the intervention factor of this type of food under all types of pressure data of the candidate patient is determined as the degree of intervention for this type of food of the candidate patient. That is to say, the average value of the intervention factor of this type of food and the diastolic blood pressure of the candidate patient under all types of systolic blood pressure is used as the degree of intervention for this type of food of the candidate patient.

[0056] By using the above method, the degree of intervention required for each type of food for each patient with gestational hypertension can be obtained.

[0057] Step S4, determining the intake of each type of food for each patient for the next day using the degree to be intervened and the intake.

[0058] In step S3, the present embodiment obtains the degree of intervention for each type of food of each patient with gestational hypertension. The greater the degree of intervention, the greater the degree to which the intake of the corresponding type of food needs to be increased the next day. Next, the intake of each type of food is dynamically adjusted based on the degree of intervention to obtain the intake of each type of food of the patient the next day.

[0059] For any type of food: calculate the sum of the constant 1 and the normalized value of the degree of intervention for this type of food of the candidate patient, where the range of the normalized value of the degree of intervention is [-1, 1]; take the product of the candidate patient's intake of this type of food on that day and the sum as the candidate patient's intake of this type of food on the next day.

[0060] In this embodiment, the intake of the t-th type of food for the i-th patient on the next day can be expressed as: in, represents the intake of the tth type of food by the i-th patient on the next day, represents the intake of the tth type of food by the i-th patient on that day, represents the degree of intervention for the t-th type of food of the ith patient, and premnmx( ) represents the normalization function.

[0061] It represents the normalized value of the degree of intervention for the t-th type of food of the ith patient, and its value range is [-1, 1].

[0062] By using the above method, the intake of each type of food for each patient with gestational hypertension in the next day can be obtained.

[0063] Thus, the method provided in this embodiment has been used to dynamically adjust the intake of different types of food for patients with gestational hypertension.

[0064] This embodiment takes into account the differences in dietary habits of different patients with gestational hypertension, such as the amount of meals, daily meal frequency, and dietary preferences, which lead to differences in nutritional needs of different patients. Therefore, based on the data aggregation of each type of indicator every day in the current time period of all patients with gestational hypertension, the difference between each patient and other patients in each type of indicator is evaluated to obtain the corresponding difference index. Then, based on the difference between the change of the difference index corresponding to the same type of indicator of each patient in two consecutive days and the change of the difference index corresponding to the diastolic pressure, the degree of fluctuation similarity is obtained, and the reference day corresponding to each type of indicator of each patient is screened. The overall distribution of the difference index corresponding to each type of pressure data of each patient in the current time period is further combined with the difference index corresponding to each type of indicator. The differences in the overall distribution of the index, the proportion of the number of reference days and the similarity of fluctuations are used to analyze the impact of changes in their eating habits on blood pressure, and combined with the changes in the difference index corresponding to the intake of each type of food for each patient on two consecutive days, the degree of intervention for each type of food for each patient is obtained, and then the intake of each type of food for each patient with gestational hypertension on the next day is determined. This embodiment adjusts the patient's nutritional plan based on the individual characteristics of the patient with gestational hypertension and the changes in her own eating habits, and conducts targeted dynamic intervention on the patient's nutritional plan according to the degree of impact of various indicators of eating habits on blood pressure, completes the dynamic adjustment of the intake of different types of food for patients with gestational hypertension, and improves the effectiveness of nutritional plan intervention for patients with gestational hypertension.

[0065] An auxiliary intervention system embodiment of a nutritional program for patients with gestational hypertension: See also Figure 2 , which shows a structural block diagram of an auxiliary intervention system for a nutritional regimen for 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.

[0066] The data collection module is used to obtain various indicators of patients with gestational hypertension every day in the current time period, including various pressure data, meal frequency and intake of different types of food, and pressure data including systolic and diastolic blood pressure; A processing module, for determining the difference index corresponding to each type of indicator of each patient every day based on the data aggregation of each type of indicator of all the patients in the current time period; obtaining the corresponding fluctuation similarity according to the difference between the change of the difference index corresponding to the same type of indicator of each patient in two consecutive days and the change of the difference index corresponding to the diastolic blood pressure, and screening the reference day corresponding to each type of indicator of each patient; A calculation module is used to obtain the correlation value between the abnormality of each type of indicator and each type of pressure data of each patient by combining the difference between the overall distribution of the difference index corresponding to each type of pressure data of each patient in the current time period and the overall distribution of the difference index corresponding to each type of indicator, the quantity proportion of the reference day and the similarity of fluctuation; and obtain the degree of intervention for each type of food of each patient by combining the change of the difference index corresponding to the intake of each type of food of each patient in two consecutive days, each type of pressure data of each day in the current time period and the correlation value; The intake determination module is used to determine the intake of each type of food for each patient in the next day by using the degree of intervention and the intake.

[0067] It should be understood that Figure 2 The structural block diagram of the auxiliary intervention system for the nutritional program of patients with hypertension during pregnancy and its modules shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by 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-mentioned method and system can be implemented using computer executable instructions and / or included in a processor control code, for example, such as 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. Such code is provided on the 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 of this specification can not only be implemented by hardware circuits such as ultra-large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software (for example, firmware).

[0068] For more details about the above modules, please refer to other places in this manual and will not be repeated here.

[0069] In other embodiments, an auxiliary intervention device for the nutritional regimen of patients with gestational hypertension is also provided, comprising 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 welding control method applied to the pulse welding machine. The device can be specifically a chip, a component or a module, and the chip may 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 regimen of patients with gestational hypertension provided in the above embodiment.

[0070] In other embodiments, a computer program product is also provided. When the computer program product is run on a computer, the computer is caused to execute the above-mentioned related steps to implement the auxiliary intervention method for the nutritional regimen of patients with gestational hypertension provided in the above-mentioned embodiment.

[0071] In other embodiments, a computer-readable storage medium is also provided, in which a computer program code is stored. When the computer program code is executed on a computer, the computer executes the above-mentioned related method steps to implement the auxiliary intervention method for the nutritional regimen of patients with gestational hypertension provided in the above-mentioned embodiment.

[0072] 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 that can be achieved can refer to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0073] It should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for assisting intervention in the nutritional regimen of patients with gestational hypertension, characterized in that: The method comprises the following steps: Obtain various indicators of patients with gestational hypertension every day during the current period, including various pressure data, meal frequency and intake of different types of food, and pressure data including systolic and diastolic blood pressure; Based on the data aggregation of each type of indicator every day in the current time period for all the patients, determine the difference index corresponding to each type of indicator of each patient every day; according to the difference between the change of the difference index corresponding to the same type of indicator of each patient in two consecutive days and the change of the difference index corresponding to the diastolic blood pressure, obtain the corresponding fluctuation similarity, and select the reference day corresponding to each type of indicator of each patient; Combine the difference between the overall distribution of the difference index corresponding to each type of stress data of each patient in the current time period and the overall distribution of the difference index corresponding to each type of indicator, the number proportion of reference days and the similarity of fluctuations, and obtain the correlation value between the abnormality of each type of indicator of each patient and each type of stress data; Combine the change of the difference index corresponding to the intake of each type of food of each patient in two consecutive days, each type of stress data of each day in the current time period and the correlation value, and obtain the degree of intervention for each type of food of each patient; The level of intervention and the intake are used to determine the intake of each food category for each patient for the next day.

2. The method for auxiliary intervention of the nutritional program of patients with gestational hypertension according to claim 1, characterized in that: The step of determining the difference index corresponding to each type of indicator of each patient every day based on the data aggregation of each type of indicator of all patients in the current time period every day includes: All patients are clustered based on the indicators to be evaluated for all patients' days to be analyzed, and the difference index corresponding to the indicators to be evaluated for the candidate patients' days to be analyzed is obtained 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 in the indicators to be evaluated between the cluster where the candidate patients are located and the center point of the corresponding cluster; The day to be analyzed is any day in the current time period, the candidate patient is any patient with gestational hypertension, and the indicator to be evaluated is any type of indicator.

3. The auxiliary intervention method for the nutritional regimen of a patient with gestational hypertension according to claim 2, characterized in that: The method of obtaining the difference index corresponding to the candidate patient's to-be-analyzed to-be-evaluated index according to the number of patients in the cluster with the largest number of patients, the number of patients in the candidate patient's cluster, and the difference between the candidate patient's cluster and the center point of the corresponding cluster in the to-be-evaluated index, comprises: Calculating a 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 in the indicator to be evaluated between the candidate patient and the center point of the cluster to which he / she belongs and the first ratio, a difference index corresponding to the indicator to be evaluated of the candidate patient on the day to be analyzed is obtained, the first ratio is positively correlated with the difference index, and the difference in the indicator to be evaluated between the candidate patient and the center point of the cluster to which he / she belongs is negatively correlated with the difference index.

4. The method for auxiliary intervention of the nutritional program of a patient with gestational hypertension according to claim 2, characterized in that: The corresponding fluctuation similarity degree is obtained according to the difference between the change of the difference index corresponding to the same type of indicator of each patient on two consecutive days and the change of the difference index corresponding to the diastolic blood pressure, including: The normalized result of the difference between the difference indexes corresponding to the same type of indicators of the candidate patient on the next day and the previous day on two consecutive days is taken as the fluctuation degree of the same type of indicators of the candidate patient on two consecutive days; According to the difference between the fluctuation degree of each type of indicator of the candidate patient on two consecutive days and the fluctuation degree corresponding to the diastolic blood pressure, the fluctuation similarity degree corresponding to each type of indicator of the candidate patient on two consecutive days is calculated, and the difference between the fluctuation degree of each type of indicator and the fluctuation degree corresponding to the diastolic blood pressure is negatively correlated with the fluctuation similarity degree.

5. The method for auxiliary intervention of the nutritional program of patients with gestational hypertension according to claim 4, characterized in that: Screen the reference days corresponding to each type of indicator for each patient, including: For the indicator to be evaluated: if the fluctuation similarity of the indicator to be evaluated of the candidate patient on two consecutive days is greater than the preset similarity threshold, the corresponding two consecutive days will be used as the reference days for the indicator to be evaluated of the candidate patient.

6. The method for auxiliary intervention of the nutritional program of patients with gestational hypertension according to claim 5, characterized in that: The method combines the difference between the overall distribution of the difference index corresponding to each type of pressure data of each patient in the current time period and the overall distribution of the difference index corresponding to each type of indicator, the number proportion of reference days and the degree of fluctuation similarity to obtain the correlation value between the abnormality of each type of indicator of each patient and each type of pressure data, including: Calculate the first average value of the difference index corresponding to the first type of pressure data in the current time period of the candidate patient, and the second average value of the difference index corresponding to the indicator to be evaluated in the current time period of the candidate patient; calculate the minimum value of the fluctuation similarity corresponding to all adjacent reference days corresponding to the indicator 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, a correlation value between the abnormality of the candidate patient's to-be-evaluated indicator and the first type of pressure data is obtained, wherein 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.

7. The method for assisting intervention in the nutritional regimen of a patient with gestational hypertension according to claim 6, characterized in that: The step of combining the change in the difference index corresponding to the intake of each type of food of each patient in two consecutive days, each type of stress data of each day in the current time period and the associated value to obtain the degree of intervention for each type of food of each patient includes: 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 in the current time period; wherein the current day is the last day in 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; record the ratio of the correlation value between the abnormality of the candidate patient's intake of this type of food and the first type of pressure data and the third average value as the third ratio; obtain the intervention factor of this type of food for the candidate patient under the first type of pressure data 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 in the current time period and the third ratio, and the second ratio, the fluctuation degree of the intake of this type of food of the candidate patient in the last two days in the current time period and the third ratio are all positively correlated with the intervention factor; The intervention factor of this type of food under all types of stress data of the candidate patient is integrated to obtain the degree of intervention required for this type of food of the candidate patient.

8. The method for auxiliary intervention of the nutritional program of patients with gestational hypertension according to claim 7, characterized in that: The intervention factor of the food of the candidate patient under all kinds of stress data is synthesized to obtain the degree of intervention of the food of the candidate patient, including: The average value of the intervention factor of the food of the candidate patient under all kinds of stress data is determined as the degree of intervention for the food of the candidate patient.

9. The method for auxiliary intervention of the nutritional program of patients with gestational hypertension according to claim 7, characterized in that: The method of determining the intake of each type of food for each patient on the next day by using the degree to be intervened and the intake includes: For any type of food: Calculate the sum of the constant 1 and the normalized value of the degree of intervention for the type of food of the candidate patient, where the range of the normalized value of the degree of intervention is [-1, 1]; The product of the candidate patient's intake of the type of food on the current day and the sum value is taken as the candidate patient's intake of the type of food on the next day.

10. An auxiliary intervention system for the nutritional regimen of patients with gestational hypertension, characterized in that: The system includes: The data collection module is used to obtain various indicators of patients with gestational hypertension every day in the current time period, including various pressure data, meal frequency and intake of different types of food, and pressure data includes systolic blood pressure and diastolic blood pressure; A processing module, for determining the difference index corresponding to each type of indicator of each patient every day based on the data aggregation of each type of indicator of all the patients in the current time period; obtaining the corresponding fluctuation similarity according to the difference between the change of the difference index corresponding to the same type of indicator of each patient in two consecutive days and the change of the difference index corresponding to the diastolic blood pressure, and screening the reference day corresponding to each type of indicator of each patient; A calculation module is used to obtain the correlation value between the abnormality of each type of indicator and each type of pressure data of each patient by combining the difference between the overall distribution of the difference index corresponding to each type of pressure data of each patient in the current time period and the overall distribution of the difference index corresponding to each type of indicator, the quantity proportion of the reference day and the similarity of fluctuation; and obtain the degree of intervention for each type of food of each patient by combining the change of the difference index corresponding to the intake of each type of food of each patient in two consecutive days, each type of pressure data of each day in the current time period and the correlation value; The intake determination module is used to determine the intake of each type of food for each patient in the next day by using the degree of intervention and the intake.

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