An intelligent management system for liquid intake of patients with urinary calculi

Abstract

The application discloses a kind of urinary calculus patient liquid intake intelligent management system, specifically related to medical health intelligent management technical field, including patient management data acquisition module, patient management data preprocessing module, liquid intake one-time management module, liquid intake secondary management module, intelligent management doctor-patient interactive module and intelligent management data storage module;The patient management data acquisition module is used to collect the multidimensional data of patient, including basic physiological data, real-time state data and diagnosis and treatment data, to obtain patient management first comprehensive data set;The application constructs the hierarchical control architecture that liquid intake one-time management and secondary management are combined, one-time management realizes basic dynamic precision control, secondary management is implemented differentiating reinforcement intervention to risk level, solve the problem that prior art management dimension is single, and the problem of insufficient pertinence, significantly improve management effectiveness.

Description

Technical Field

[0001] This invention relates to the field of intelligent medical and health management technology, specifically to an intelligent management system for fluid intake in patients with urinary tract stones. Background Technology

[0002] Urinary tract stones are a common disease in urology, with a high recurrence rate. Scientific fluid intake management is the core means to prevent stone recurrence.

[0003] Existing technologies mainly rely on manual reminders from healthcare professionals or simple mobile apps to remind patients to drink water. Their management strategies are usually based on fixed water intake thresholds, such as 2000ml per day, without fully considering individual patient differences. Some systems use a uniform reporting and reminder frequency for all patients, which cannot promptly identify the decline in compliance of high-risk patients and may lead to reminder fatigue in low-risk patients. At the same time, patients' fluid intake data is usually independent of the hospital's diagnosis and treatment system, and existing technologies cannot automatically call upon this data to generate initial management strategies.

[0004] It is worth noting that patients with urinary tract stones may also have brain diseases or neurological dysfunctions such as epilepsy, brain injury, or mood regulation disorders. These diseases may indirectly affect patients' drinking behavior and fluid balance through neuroendocrine pathways (such as the amygdala's involvement in mood and stress regulation). Epilepsy patients may experience fluid imbalance and urine volume fluctuations due to seizures or the use of antiepileptic drugs, further affecting the risk of stone formation. Therefore, relying solely on fixed water intake thresholds for reminders, without considering dynamic factors such as individual patient physiological characteristics (e.g., stone composition, renal function) and lifestyle habits (e.g., exercise intensity, work schedule), results in a lack of personalized management strategies. Furthermore, the absence of a tiered management mechanism makes it impossible to implement differentiated control based on patients' fluid intake targets and stone recurrence risk levels, leading to insufficient intervention for high-risk patients. Poor data interactivity makes it difficult for medical staff to monitor patient management in real time and adjust plans accordingly, resulting in a broken management loop. To address these issues, a multi-dimensional data fusion, tiered control architecture, and closed-loop doctor-patient data interaction intelligent management system for urinary tract stone patients is needed to provide a more scientific and efficient solution for stone prevention. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide an intelligent management system for fluid intake in patients with urinary tract stones, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent management system for fluid intake in patients with urinary tract stones, comprising: Patient management data acquisition module: used to collect multi-dimensional patient data, including basic physiological data, real-time status data and diagnosis and treatment data, to obtain the first comprehensive dataset for patient management; The patient management data preprocessing module is used to clean abnormal data from the collected first comprehensive dataset of patient management data and to standardize the motion intensity data in the real-time status data to obtain the preprocessed second comprehensive dataset of patient management data. The single-dose fluid intake management module includes a fluid intake baseline model building unit, an initial strategy generation unit, and a dynamic adjustment unit. It builds a personalized fluid intake baseline model based on the second comprehensive dataset of patient management, generates an initial management strategy, and dynamically adjusts it in real time to obtain the single-dose fluid intake management result. The secondary fluid intake management module includes a risk level assessment unit and an enhancement strategy generation unit. Based on the execution data of the primary fluid intake management results and the risk level assessment results of patients with stones, it generates enhancement strategies corresponding to different risk levels, thus obtaining the secondary fluid intake management results. Intelligent management of doctor-patient interaction module: including patient-side interaction unit and medical staff-side interaction unit, pushes the results of the first fluid intake management and the second fluid intake management to the patient end, and synchronizes the management structure and corresponding execution status to the medical staff end; Intelligent management data storage module: Used to store the entire process data of intelligent management of patients with urinary tract stones, and feed it back to the intelligent management doctor-patient interaction module for human-computer interaction.

[0007] The technical effects and advantages of this invention are as follows: 1. This invention constructs a hierarchical control architecture that combines primary and secondary management of liquid intake. Primary management achieves basic dynamic and precise control, while secondary management implements differentiated and enhanced intervention based on risk level. This solves the problems of single management dimension and insufficient targeting in existing technologies, and significantly improves management effectiveness. 2. This invention integrates personalized physiological data of the patient's stone composition and creatinine value (a kidney function test indicator) to construct a personalized fluid intake benchmark model; at the same time, it adjusts the model by using dynamic data of exercise intensity score and ambient temperature to achieve full-dimensional personalized customization of management strategies, overcoming the limitations of existing technologies based on fixed threshold management. 3. This invention constructs a data interaction closed loop through the hospital diagnosis and treatment system interface and doctor-patient interaction module, realizing seamless connection between patient management data and diagnosis and treatment data, which facilitates real-time intervention and adjustment by medical staff. It solves the problems of data disconnect and management loop breakage in existing technologies, and enables doctor-patient communication to be based on the same factual data, thereby improving follow-up efficiency and the accuracy of intervention. Attached Figure Description

[0008] Figure 1This is a schematic diagram of the overall process of the present invention.

[0009] Figure 2 This is a flowchart illustrating the liquid intake management module of the present invention.

[0010] Figure 3 This is a flowchart illustrating the secondary liquid intake management module of the present invention. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] Please see Figure 1 As shown, the present invention provides an intelligent management system for fluid intake in patients with urinary tract stones, including a patient management data acquisition module, a patient management data preprocessing module, a primary fluid intake management module, a secondary fluid intake management module, an intelligent management doctor-patient interaction module, and an intelligent management data storage module. The patient management data acquisition module is connected to the patient management data preprocessing module, the primary fluid intake management module is connected to both the patient management data preprocessing module and the secondary fluid intake management module, and the intelligent management doctor-patient interaction module is connected to both the secondary fluid intake management module and the intelligent management data storage module.

[0013] Patient management data acquisition module: used to collect multi-dimensional patient data, including basic physiological data, real-time status data and diagnosis and treatment data, to obtain the first comprehensive dataset for patient management; In this embodiment, the basic physiological data include age, gender, height, weight, stone composition results, and creatinine value as a renal function test indicator; real-time status data includes fluid intake, urine output, exercise intensity data, and ambient temperature; diagnostic data includes stone composition, creatinine value, and the number of stone recurrences in the past 3 years; and the exercise intensity data includes exercise acceleration sequence and heart rate sequence.

[0014] This embodiment requires specific explanation of the stone composition results. i=1,2,...,n The component of the stone in the i-th patient is coded, and k is the type of stone component (e.g., k=1 for calcium oxalate stone, k=2 for uric acid stone, etc.).

[0015] This embodiment specifically describes the data acquisition module, which includes a smart terminal (mobile app, smartwatch), smart detection devices (smart water cup, urine analyzer), and a hospital diagnostic system interface. The smart water cup has a built-in weight sensor and beverage recognition module, which can collect the beverage type and intake volume in real time. The urine analyzer connects to the smart terminal via Bluetooth and automatically uploads urine data. The hospital diagnostic system interface has multi-factor authentication (such as medical staff employee ID + dynamic password + device binding, etc.). Before data interaction, sensitive patient information has been de-identified (such as hiding the ID number and de-identifying the name as "Zhang ×"). Only the core diagnostic and treatment data required for management (such as stone composition, recurrence history, current fluid intake treatment plan, etc.) is transmitted. Data interaction with the hospital's electronic medical record system is achieved through the HL7 protocol to obtain patient diagnostic and treatment data.

[0016] The patient management data preprocessing module is used to clean abnormal data from the collected first comprehensive dataset of patient management data and to standardize the motion intensity data in the real-time status data to obtain the preprocessed second comprehensive dataset of patient management data. In this embodiment, it should be specifically noted that abnormal data in the first comprehensive dataset for patient management refers to data that does not conform to the actual situation, such as an incorrectly entered height of 3m; Standardization processing of exercise intensity data: obtaining the target patient's exercise acceleration sequence and heart rate sequence within the time window T; calculating the mean percentage of heart rate reserve corresponding to the heart rate sequence. Calculate the composite activity intensity index AI of the acceleration sequence, and finally... The weighted geometric mean of the AI ​​is calculated and normalized to a preset score range to obtain the motion intensity score SC within the time window [tT, t], where SC∈[0,10]. , Average heart rate within the time window Subtract the target patient's resting heart rate The difference (obtainable by monitoring morning heart rate or historical lowest value) and the target patient's maximum heart rate The ratio obtained by subtracting the difference in resting heart rate is... Within the time window, N sets of raw triaxial acceleration data are collected using intelligent acceleration acquisition devices (such as smartwatches, wearable devices, etc.). Calculate the acceleration modulus for each sampling point. The acceleration magnitude sequence was obtained by sorting the data according to the time series. Take the value at the 75th position. acceleration variance and zero crossing rate (Calculate the number of times the numerical value changes after subtracting the mean from the acceleration modulus sequence, and then divide by the time length.) , and Collect all data from the target patient over the past N1 days (e.g., 7 days, 30 days, etc.). The median of the values ​​is obtained Similarly, we can obtain and , Weighted by heart rate F is the fitness coefficient, which is obtained by comparing the target patient's historical median heart rate reserve percentage (AI) over the past N1 days with the decimal value of the historical median heart rate reserve percentage. Using physical fitness coefficient as a reference, and K as an adjustment parameter, the system optimizes through population data regression to maximize the intensity score SC output by the system, thus minimizing the overall prediction error. This is the globally optimal parameter. And K.

[0017] Please see Figure 2 As shown, the fluid intake management module includes a fluid intake baseline model building unit, an initial strategy generation unit, and a dynamic adjustment unit. It builds a personalized fluid intake baseline model based on the second comprehensive dataset of patient management, generates an initial management strategy, and dynamically adjusts it in real time to obtain the fluid intake management result. The baseline model construction unit includes the following steps: A1: First, based on the target patient's input age (a), gender (g), height (h), and weight (w), obtain the basal metabolic rate (BMR) (a,g,h,w) (e.g., 1786.5 kcal / day), and calculate the basal fluid intake requirement. , =BMR(a,g,h,w)×[1.2+1×(1+exp(-0.8( , The historical average exercise intensity score SC is used, and K1 is the unit conversion factor, which converts energy metabolism requirements into units of fluid intake (such as mL, L, etc.), usually set based on the medical experience that 1 mL of water is needed for every 1 kcal of energy consumed. In this embodiment, it is important to note that the basal metabolic rate (BMR) refers to the minimum energy required for the human body to maintain life in a conscious, resting, and fasting state. It can be estimated using a recognized empirical formula based on the patient's input age, gender, height, and weight. For males: BMR (kcal / day) = 10 × weight (kg) + 6.25 × height (cm) - 5 × age (years) + 5; for females: BMR (kcal / day) = 10 × weight (kg) + 6.25 × height (cm) - 5 × age (years) - 161.

[0018] A2: Then, based on the results of the stone composition, the basic fluid input requirement V is determined. baseAfter correction, the target patient's single intelligent fluid management intake V is obtained. sto V sto =V base ×(1+η(k i ))+V off (k i ), η(k) i ) represents the incremental coefficient for the stone type of the i-th patient, where stone types include calcium stones, uric acid stones, and cystine stones. off (k i ) represents the baseline offset for fluid intake. Calcium stones include calcium oxalate stones and calcium phosphate stones. If the stone is composed of calcium, then 0.1 ≤ η(k) i )≤0.15 and V off (k i If the stone composition is uric acid, then 0.05 ≤ η(k) = 0. i )≤0.1 and V off (k i If η(k) = 0, and the stone is composed of cystine, then η(k) = 0. i =0, ignore the basic liquid demand V base V off (k i Set a maximum fixed value (e.g., 3500 mL), V off (k i )>V base ; A3: If the target patient has non-cystine stones, and the renal function test indicator is creatinine (Cr), for males, if Cr ≥ 180 μmol / L, the patient's daily safe upper limit for fluid intake is V. max =1500mL, if 120≤Cr<180μmol / L, then V max =2000mL, if 90≤Cr<120μmol / L, then V max =2500mL, if Cr < 90μmol / L, then V max There are no mandatory restrictions; for women, if Cr ≥ 150 μmol / L, then V max =1500mL, if 100≤Cr<150μmol / L, then V max =2000mL, if 80≤Cr<100μmol / L, then V max =2500mL, if Cr < 80μmol / L, then V max No mandatory restrictions; the final target baseline value V for daily fluid intake of the target patient is obtained. tb V tb =min(V sto V max), thus obtaining a personalized fluid intake baseline model; if the target patient has cystine stones, if V sto ≤V max Then V tb =min(V sto V max If V sto >V max If this occurs, an early warning will be issued, alerting both the patient and medical staff that the patient has cystine stones, triggering the medical intervention mechanism, and requesting the doctor to intervene urgently to adjust the treatment plan. It should be specifically noted in this embodiment that women generally have lower creatinine levels than men, resulting in a lower physiological baseline value for their serum creatinine. The kidney function assessment standards for women are more stringent, and the same creatinine value may mean a more severe decline in kidney function in women. The higher the serum creatinine (Cr) value, the more severe the kidney function impairment, and the lower the safe upper limit for daily fluid intake should be set.

[0019] The initial strategy generation unit, for patients with non-cystine stones, first divides the day into M-1 fixed time periods and 1 flexible time period (e.g., 1 hour after breakfast, 1 hour after lunch, 1 hour after dinner, and 2 hours before bedtime, 4 fixed time periods), and allocates the intake ratio of each time period according to a preset proportion. (For example, 20% for breakfast and 25% for lunch) to obtain the fluid intake target for each time period. , , j∈M, The target baseline for daily fluid intake , Let η(i,1) be the personalized adjustment coefficient for the i-th target patient at the j-th time period. For example, if the patient habitually drinks less water after breakfast, then η(i,1) = -0.05. For patients with cystine stones, a uniform distribution algorithm is used. The system mandates even intake throughout the day; then, based on the stone composition determined by the benchmark model construction unit, it matches the corresponding liquid intake varieties to generate a personalized liquid intake recommendation list, which includes stone composition, daily liquid intake target benchmark value, intake at each time period, and liquid intake varieties. This embodiment requires a specific explanation: the flexible time slots differ from the four fixed intake periods, such as one hour after breakfast, one hour after lunch, one hour after dinner, and two hours before bedtime. It allows patients to consume fluids at other suitable times throughout the day, excluding critical periods. The types of fluids are mapped to a built-in system table corresponding to the composition of the stones. When selecting fluids, recommendations are made based on the definitions in the table. For example, if the target patient has calcium stones, lemonade / citrus drinks are recommended; if the stones are uric acid stones, low-sugar alkaline drinks (such as baking soda water) are recommended; and if the stones are cystine stones, a cystine-specific management strategy is activated: medical alkalizing agents (such as potassium citrate solution and sodium bicarbonate solution) are placed at the highest mandatory recommendation level, while natural alkalizing drinks (such as unsweetened lemonade) are secondary recommendations.

[0020] The dynamic adjustment unit includes the following steps: B1: First, assume the current time t is within time period j, then calculate the time period from the next time period j+1 to the last time period j of the day. end The remaining original total fluid intake target value V re It is obtained by summing the remaining fluid intake at each stage; then based on the target patient's exercise intensity score (SC) and ambient temperature (T). env Calculate the motion adjustment coefficient η(SC) and the temperature adjustment coefficient η(T) respectively. env ), and merge to obtain the global adjustment coefficient η (global); when SC > SC th At that time, η(SC) = 0.08 + k SC ×[SC-SC th ], otherwise η(SC)=0; when T env >T th At that time, η(T) env )=0.05+k T ×[T env -T th Otherwise η(T) env )=0,T th and SC th These are the threshold values ​​for the exercise intensity score (e.g., 7) and the ambient temperature threshold (e.g., 32°C), respectively. SC and k T These are the exercise intensity adjustment coefficient (e.g., 0.005) and the temperature adjustment coefficient (e.g., 0.001), respectively, with units of 1 / ℃. η(global) = (1 + η(SC)) × (1 + η(T)) env ))-1; This yields the adjusted target value V for remaining total fluid intake. adj V adj =V re×(1+η(global)), and according to the original fluid intake target V for each time period j Allocated to each remaining time period V adj,j V adj,j =V j ×V adj / V re ; B2: First, if the actual fluid intake V in the j-th time period... act <Completion rate threshold η1×V j Then calculate the insufficient amount V def =V j -V act Then calculate the base weight W for each remaining time period. sy,j W sy,j The remaining original intake target value for time j and the remaining original total fluid intake target value V are used to determine the intake target value for time j. re The ratio is obtained by introducing a time decay factor d. sy,j d sy,j =exp(-λ(j sy -j-1)), j sy For the remaining j-th time period, λ is a preset attenuation intensity parameter; the larger the value, the faster the weight attenuates with increasing delay interval. Next, the final comprehensive weight W for the remaining j-th time period is obtained. fin,j Through the remaining j-th time period W sy,j and d sy,j The product of W and all remaining time periods sy,j and d sy,j The ratio of the sum of the products is obtained; then the intake recovery amount ΔV for the remaining time periods is calculated. sy,j ΔV sy,j =λ1×V def ×W fin,j λ1 is the preset total compensation ratio (e.g., 0.5); conversely, if V act ≥Completion rate threshold η1×V j Then, there is no need to calculate the insufficient amount, and the final fluid intake target V for each remaining time period can be obtained. fin,j =min(V adj,j +ΔV sy,j ,η2×V j ), where η2 is the maximum upward adjustment ratio for a single time period (e.g., η2=1.5); finally, the results of one fluid intake management are obtained, including the stone composition, the dynamically adjusted daily fluid intake target value, the intake of each time period, and the types of fluids consumed. The daily fluid intake target value is obtained by summing the fluid intake of each time period without adjustment and the final fluid intake of the remaining time periods. Please see Figure 3As shown, the secondary fluid intake management module includes a risk level assessment unit and an enhancement strategy generation unit. Based on the execution data of the primary fluid intake management results and the risk level assessment results of the stone patients, it generates enhancement strategies corresponding to different risk levels to obtain the secondary fluid intake management results. The risk level assessment unit includes the following steps: C1: Based on the target daily fluid intake value in the single fluid intake management result of the target patient. and actual value Calculate the management cycle compliance rate R1(i). T1 is the period duration (e.g., if the period is 7 days, then T1=7), and I is an indicator function that takes the value 1 if the condition is met, and 0 otherwise. The total daily fluid intake is used as the reference. Based on the number of stone recurrences (n) in the past 3 years, the risk coefficient R²(i) for the history of stone disease is calculated. If n ≥ 2, then R²(i) = 1; otherwise, R²(i) = 0. Simultaneously, the urine output of the target patient over the past N1 days is recorded, and the average urine output is obtained. Calculate the physiological stability risk coefficient R3(i). , The median of historical urine volume is the number of historical days greater than 2 × N1 days (e.g., N1=7, urine volume over 30 historical days). For indicator functions, when hour, =1, otherwise =0; C2: Based on the management cycle target achievement rate R1(i), the risk coefficient of kidney stone history R2(i), and the risk coefficient of physiological stability R3(i), the risk level assessment result R4(i) of the target patient is calculated. If R1(i)≥0.8 and R2(i)=0 and R3(i)≤0.3, it is judged as low risk, R4(i)=3. If 60≤R1(i)<0.8 or R2(i)=1 or 0.3≤R3(i)<0.5, it is judged as medium risk, triggering an early warning, R4(i)=2. If R1(i)<0.6 and R2(i)=1, or R3(i)>0.5, it is judged as high risk, triggering an early warning, R4(i)=1. In this embodiment, it should be specifically noted that the number of stone recurrences refers to the number of times a patient experiences clinical symptoms due to the re-formation of urinary tract stones, or the number of times a new stone is diagnosed / residual.

[0021] The enhancement strategy generation unit first generates an intelligent management report every 14 days based on the target patient's risk level assessment result R4(i). If R4(i) = 3, an intelligent management report is generated every 7 days. If R4(i) = 2, an intelligent management report is generated every 7 days. The management cycle compliance rate R1(i) is set to ≥ 0.8 or the physiological stability risk coefficient R3(i) ≤ 0.3, and prevention science popularization knowledge corresponding to the stone components is pushed. If R4(i) = 1, an intelligent management report is generated every day. The patient's fluid intake data and physiological stability risk coefficient are synchronized with medical staff daily, and medical intervention mechanisms are triggered, such as online follow-up every 3 days, and offline follow-up suggestions are generated when necessary. The intelligent management report includes stone components, total daily fluid intake, intake at different times, types of fluids, and risk level. Finally, the secondary management results of fluid intake are obtained, including risk level and enhancement strategies corresponding to different risk levels. The intelligent management patient-medical interaction module includes a patient-side interaction unit and a medical staff-side interaction unit. It pushes the results of the first and second fluid intake management sessions to the patient's end, while simultaneously synchronizing the management results and corresponding execution status to the medical staff's end. The patient-side interaction unit uses a visual interface to display the results of the first fluid intake management session, the corresponding intake amount and fluid type, and the execution status of the second fluid intake management session. The medical staff-side interaction unit uses a visual interface to display management data and the execution status of the target patients, and uses a dashboard to display the overall management status of the managed patients, including the proportion of patients at each risk level, statistics on management cycle compliance rates, statistics on the risk coefficient of kidney stone history, statistics on the risk coefficient of physiological stability, medical staff intervention early warning functions, and one-click distribution of adjusted fluid intake management results. This embodiment requires specific explanation of the statistics in the management cycle target achievement rate statistics, stone disease history risk coefficient statistics, and physiological stability risk coefficient statistics, including but not limited to the total number of patients, average value statistics, variance statistics, etc.; for example, the patient interface includes today's intake progress bar, targets for each time period, and a recommended list of liquid intake varieties, etc.

[0022] Intelligent management data storage module: Used to store the entire process data of intelligent management of patients with urinary tract stones, and feed it back to the intelligent management doctor-patient interaction module for human-computer interaction.

[0023] Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other. In conclusion, 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 spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent management system for fluid intake in patients with urinary tract stones, characterized in that: include: Patient management data acquisition module: used to collect multi-dimensional patient data, including basic physiological data, real-time status data and diagnosis and treatment data, to obtain the first comprehensive dataset for patient management; The patient management data preprocessing module is used to clean abnormal data from the collected first comprehensive dataset of patient management data and to standardize the motion intensity data in the real-time status data to obtain the preprocessed second comprehensive dataset of patient management data. The single-dose fluid intake management module includes a fluid intake baseline model building unit, an initial strategy generation unit, and a dynamic adjustment unit. It builds a personalized fluid intake baseline model based on the second comprehensive dataset of patient management, generates an initial management strategy, and dynamically adjusts it in real time to obtain the single-dose fluid intake management result. The secondary fluid intake management module includes a risk level assessment unit and an enhancement strategy generation unit. Based on the execution data of the primary fluid intake management results and the risk level assessment results of patients with stones, it generates enhancement strategies corresponding to different risk levels, thus obtaining the secondary fluid intake management results. Intelligent management of doctor-patient interaction module: including patient-side interaction unit and medical staff-side interaction unit, pushes the results of the first fluid intake management and the second fluid intake management to the patient end, and synchronizes the management structure and corresponding execution status to the medical staff end; Intelligent management data storage module: Used to store the entire process data of intelligent management of patients with urinary tract stones, and feed it back to the intelligent management doctor-patient interaction module for human-computer interaction.

2. The intelligent fluid intake management system for patients with urinary tract stones according to claim 1, characterized in that: The exercise intensity data standardization process is as follows: The exercise intensity score is configured to: obtain the target patient's exercise acceleration sequence and heart rate sequence within the time window T; calculate the mean heart rate reserve percentage μ(HRR) corresponding to the heart rate sequence; calculate the composite activity intensity index AI of the acceleration sequence; and finally, by taking a weighted geometric average of μ(HRR) and AI and normalizing it to a preset score range, obtain the exercise intensity score SC within the time window [tT, t], where SC∈[0,10].

3. The intelligent fluid intake management system for patients with urinary tract stones according to claim 1, characterized in that: The benchmark model construction unit includes: A1: First, based on the target patient's input age (a), gender (g), height (h), and weight (w), obtain the basal metabolic rate (BMR) (a,g,h,w), and calculate the basal fluid requirement (V). base V base =BMR(a,g,h,w)×[1.2+1×(1+exp(-0.8(μ(SC)-5)) -1 ]×K1,μ(SC) is the historical average exercise intensity score SC, and K1 is the unit conversion factor, which converts energy metabolic demand into units of fluid intake; A2: Then, based on the results of the stone composition, the basic fluid requirement V is determined. base After correction, the target patient's single intelligent fluid management intake V is obtained. sto V sto =V base ×(1+η(k i ))+V off (k i ), η(k) i ) represents the incremental coefficient for the stone type of the i-th patient, where stone types include calcium stones, uric acid stones, and cystine stones. off (k i ) represents the baseline offset for fluid intake. Calcium stones include calcium oxalate stones and calcium phosphate stones. If the stone is composed of calcium, then 0.1 ≤ η(k) i )≤0.15 and V off (k i If the stone composition is uric acid, then 0.05 ≤ η(k) = 0. i )≤0.1 and V off (k i If η(k) = 0, and the stone is composed of cystine, then η(k) = 0. i =0, ignore the basic liquid demand V base V off (k i Set the maximum fixed value, V off (k i )>V base ; A3: If the target patient has non-cystine stones, and the renal function test indicator is creatinine (Cr), for males, if Cr ≥ 180 μmol / L, the patient's daily safe upper limit for fluid intake is V. max =1500mL, if 120≤Cr<180μmol / L, then V max =2000mL, if 90≤Cr<120μmol / L, then V max =2500mL, if Cr < 90μmol / L, then V max There are no mandatory restrictions; for women, if Cr ≥ 150 μmol / L, then V max =1500mL, if 100≤Cr<150μmol / L, then V max =2000mL, if 80≤Cr<100μmol / L, then V max =2500mL, if Cr < 80μmol / L, then V max No mandatory restrictions; the final target baseline value V for daily fluid intake of the target patient is obtained. tb V tb =min(V sto V max ), thus obtaining a personalized fluid intake baseline model; if the target patient has cystine stones, if V sto ≤V max Then V tb =min(V sto V max If V sto >V max If the condition is detected, an early warning will be issued, alerting both the patient and healthcare staff that the patient has cystine stones, triggering a healthcare intervention mechanism.

4. The intelligent fluid intake management system for patients with urinary tract stones according to claim 1, characterized in that: The initial strategy generation unit, for non-cystine stone patients, first divides the day into M-1 fixed time periods and 1 flexible time period, and allocates the intake ratio w for each time period according to a preset proportion. j The target fluid intake V for each time period was obtained. j V j =V tb ×w j ×(1+η(i,j)), j∈M, V tb The target baseline value for daily fluid intake V tb η(i,j) is the personalized adjustment coefficient for the i-th target patient at the j-th time period; For patients with cystine stones, a uniform allocation algorithm V is used. j =V tb / M, forcing uniform intake throughout the day; then, based on the stone composition determined by the benchmark model construction unit, matching the corresponding liquid intake varieties of the stone composition, generating a personalized liquid intake recommendation list, the list includes stone composition, daily liquid intake target benchmark value, intake at each time period, and liquid intake varieties.

5. The intelligent fluid intake management system for patients with urinary tract stones according to claim 1, characterized in that: The dynamic adjustment unit includes: first, assuming the current time t is in time period j, calculating the time from the next time period j+1 to the last time period j of the day. end The remaining original total fluid intake target value V re It is obtained by summing the remaining fluid intake at each stage; then based on the target patient's exercise intensity score (SC) and ambient temperature (T). env Calculate the motion adjustment coefficient η(SC) and the temperature adjustment coefficient η(T) respectively. env ), and merge to obtain the global adjustment coefficient η (global); when SC > SC th At that time, η(SC) = 0.08 + k SC ×[SC-SC th ], otherwise η(SC)=0; when T env >T th At that time, η(T) env )=0.05+k T ×[T env -T th Otherwise η(T) env )=0,T th and SC th These are the threshold values ​​for exercise intensity score and ambient temperature, respectively, k SC and k T These are the exercise intensity adjustment coefficient and the temperature adjustment coefficient, respectively, with units of 1 / ℃. η(global) = (1 + η(SC)) × (1 + η(T)) env ))-1; This yields the adjusted target value V for remaining total fluid intake. adj V adj =V re ×(1+η(global)), and according to the original fluid intake target V for each time period j Allocated to each remaining time period V adj,j V adj,j =V j ×V adj / V re .

6. The intelligent fluid intake management system for patients with urinary tract stones according to claim 5, characterized in that: The dynamic adjustment unit further includes: firstly, if the actual liquid intake V in the j-th time period... act <Completion rate threshold η1×V j Then calculate the insufficient amount V def =V j -V act Then calculate the base weight W for each remaining time period. sy,j W sy,j The remaining original intake target value for time j and the remaining original total fluid intake target value V are used to determine the intake target value for time j. re The ratio is obtained by introducing a time decay factor d. sy,j d sy,j =exp(-λ(j sy -j-1)), j sy Let λ be the preset attenuation intensity parameter for the remaining j-th time period; then, obtain the final comprehensive weight W for the remaining j-th time period. fin,j Through the remaining j-th time period W sy,j and d sy,j The product of W and all remaining time periods sy,j and d sy,j The ratio of the sum of the products is obtained; then the intake recovery amount ΔV for the remaining time periods is calculated. sy,j ΔV sy,j =λ1×V def ×W fin,j λ1 is the preset total compensation ratio; conversely, if V act ≥Completion rate threshold η1×V j Then, there is no need to calculate the insufficient amount, and the final fluid intake target V for each remaining time period can be obtained. fin,j =min(V adj,j +ΔV sy,j ,η2×V j ), where η2 is the maximum upward adjustment ratio in a single time period; finally, the results of a single fluid intake management are obtained, including the composition of stones, the dynamically adjusted target value of daily fluid intake, the intake in each time period, and the types of fluids consumed.

7. The intelligent fluid intake management system for patients with urinary tract stones according to claim 1, characterized in that: The risk level assessment unit includes: C1: Target daily fluid intake V based on the outcome of a single fluid intake management session for the target patient. tar (i,d) and the actual value V act (i,d), calculate the management cycle achievement rate R1(i); based on the number of stone recurrences n in the past 3 years, calculate the stone history risk coefficient R2(i). If n≥2, then R2(i)=1, otherwise R2(i)=0; at the same time, record the urine output of the target patient in the past N1 days, obtain the average urine output μ(LL), and calculate the physiological stability risk coefficient R3(i), R3(i)=(|μ(LL)-LL) mid | / LL mid )×I ab LL mid The median historical urine volume, with a historical duration greater than 2 × N1 days, I ab As an indicator function, when |μ(LL)-LL mid | / LL mid When I > 0.3, ab If it is 1, otherwise I ab =0; C2: Based on the management cycle target achievement rate R1(i), the risk coefficient of kidney stone history R2(i), and the risk coefficient of physiological stability R3(i), the risk level assessment result R4(i) of the target patient is calculated. If R1(i)≥0.8 and R2(i)=0 and R3(i)≤0.3, it is judged as low risk, R4(i)=3. If 60≤R1(i)<0.8 or R2(i)=1 or 0.3≤R3(i)<0.5, it is judged as medium risk, triggering an early warning, R4(i)=2. If R1(i)<0.6 and R2(i)=1, or R3(i)>0.5, it is judged as high risk, triggering an early warning, R4(i)=1.

8. The intelligent fluid intake management system for patients with urinary tract stones according to claim 1, characterized in that: The reinforcement strategy generation unit first generates an intelligent management report every 14 days based on the target patient's risk level assessment result R4(i). If R4(i) = 3, an intelligent management report is generated every 7 days. If R4(i) = 2, an intelligent management report is generated every 7 days. The management cycle achievement rate R1(i) is set to ≥ 0.8 or the physiological stability risk coefficient R3(i) ≤ 0.3, and prevention science popularization knowledge corresponding to the stone components is pushed. If R4(i) = 1, an intelligent management report is generated every day. The patient's fluid intake data and physiological stability risk coefficient are synchronized with medical staff daily, and the medical staff intervention mechanism is triggered. The intelligent management report includes stone components, total daily fluid intake, intake at different times, types of fluid intake, and risk level. Finally, the secondary management results of fluid intake are obtained, including the risk level and reinforcement strategies corresponding to different risk levels.

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