A method and system for nutritional intervention in a sarcopenic patient

Abstract

The application provides a method and system for nutritional intervention of sarcopenia patients, and relates to the technical field of health data management. The method comprises the following steps: collecting multi-modal data of the patient, the multi-modal data comprising basic information of the patient, human body composition data, clinical phenotype data, nutritional assessment data, biochemical index data, muscle function data and exercise preference data; determining the nutritional status, risk factors and intervention direction of the patient based on the multi-modal data; generating an individualized nutritional plan based on the intervention direction, the quantity-quality-time balance mechanism and the nutritional intervention mechanism; wherein the nutritional intervention mechanism comprises an intake mechanism, a nutritional quality mechanism and an eating time mechanism, the intake mechanism is used to determine the total energy intake and a nutritional formula, the nutritional formula comprises the types and quantities of food materials and cooking methods, the nutritional quality mechanism is used to determine the nutritional preparation that needs to be supplemented, and the eating time mechanism is used to determine the daily meal time distribution and the cooperation timing with the exercise plan.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of health data management, and in particular to a nutritional intervention method and system for sarcopenia patients. BACKGROUND

[0002] Sarcopenia is a syndrome associated with aging, characterized by a comprehensive decline in skeletal muscle mass, strength and function, with a high prevalence in the elderly population, and is an important risk factor for falls, disability and even death. At present, the effective management of sarcopenia mainly relies on comprehensive nutritional and exercise intervention.

[0003] However, the related clinical intervention method has obvious limitations. First, the evaluation means is fragmented, and the key data of the patient, such as body composition, muscle function, biochemical indicators, etc., are scattered in different departments or recording media, and there is a lack of unified and efficient integrated analysis tools, making it difficult to form a comprehensive individual condition assessment. Second, the generation of intervention programs is heavily dependent on human experience and lacks data-driven, which cannot achieve precise quantification based on individual differences, resulting in poor targeting, poor executability and limited intervention effect of the program.

[0004] Therefore, there is an urgent need for a highly individualized nutritional intervention program for sarcopenia to meet the complex and individualized health needs of sarcopenia patients. SUMMARY

[0005] In view of the above problems, the embodiments of the present application provide a nutritional intervention method and system for sarcopenia patients in order to overcome the above problems or at least partially solve the above problems.

[0006] In a first aspect, the embodiments of the present application disclose a nutritional intervention method for sarcopenia patients, the method comprising:

[0007] collecting multi-modal data of the patient, the multi-modal data comprising patient basic information, body composition data, clinical phenotype data, nutritional assessment data, biochemical indicator data, muscle function data and exercise preference data;

[0008] determining a nutritional status, risk factors and intervention direction of the patient based on the multi-modal data, the intervention direction being an intervention target after comprehensively considering the nutritional status and the risk factors;

[0009] generating an individualized nutritional program according to a quantity-quality-time balance mechanism and a nutritional intervention mechanism based on the intervention direction;

[0010] The nutrition intervention mechanism includes an intake mechanism, a nutrition quality mechanism, and an eating time mechanism. The intake mechanism is used to determine total energy intake and a nutrition formula, the nutrition formula including types and quantities of food materials and a cooking method. The nutrition quality mechanism is used to determine a nutrition preparation that needs to be supplemented. The eating time mechanism is used to determine a daily meal time distribution and a matching timing with a movement scheme.

[0011] Optionally, based on the multi-modal data, a nutrition status of the patient is determined, including:

[0012] According to the muscle mass and fat distribution in the human body composition data, a basal metabolic demand parameter is established as a benchmark for energy calculation.

[0013] According to the 24-hour dietary review in the nutrition assessment data, actual total energy intake is calculated.

[0014] According to the age, physical activity consumption in the patient basic information, the basal metabolic demand parameter, and food thermal effect, total energy consumption of the patient is determined, and in combination with the human body composition data and a preset weight control target, a daily meal energy target value is determined. The physical activity consumption is calculated based on metabolic equivalent values corresponding to activity duration and intensity reflected by the movement preference data. The food thermal effect is calculated according to the actual total energy intake at a preset ratio.

[0015] The actual total energy intake and the daily meal energy target value are compared to obtain a total energy intake deviation.

[0016] Macro-nutrient intake weights are obtained through the 24-hour dietary review, and the macro-nutrient intake weights are converted into energy contribution values. Energy supply ratios of each macro-nutrient are calculated, and the energy supply ratios of each macro-nutrient are compared with preset target energy supply ratios to obtain macro-nutrient energy supply ratio deviations. The macro-nutrients include carbohydrates, fats, and proteins.

[0017] Based on the basal metabolic demand parameter, the macro-nutrient energy supply ratio deviation, the implicit malnutrition, and the protein assimilation capacity, the nutrition status is comprehensively determined, and a nutrition status subtyping conclusion representing specific nutrition problems is output.

[0018] Optionally, based on the multi-modal data, a risk factor of the patient is determined, including:

[0019] Based on the actual total energy intake and the daily meal energy target value, a difference between energy intake and energy demand is calculated to identify an energy imbalance risk caused by excessive or insufficient energy.

[0020] identify disease-related nutritional contraindications and specific needs according to comorbidities and medication use in the clinical phenotype data;

[0021] identify nutritional imbalance risks caused by dietary structure in combination with the deviation of the macro-nutrient energy supply ratio;

[0022] identify circadian rhythm disorder risks caused by late-night eating, meal skipping, or meal rhythm disorder in combination with eating times reflected in the nutritional assessment data;

[0023] calculate actual protein intake in the nutritional assessment data and compare it with recommended protein intake determined based on age and body composition data to identify protein intake deficiency risks;

[0024] determine the risk factors comprehensively based on the energy imbalance risks, the nutritional imbalance risks, the nutritional contraindications and the specific needs, the circadian rhythm disorder risks, and the protein intake deficiency risks, and output specific risk labels and nutritional risk levels.

[0025] Optionally, the intervention direction at least includes energy intake adjustment, nutritional quality optimization, and eating time adjustment; based on the intervention direction, an individualized nutrition plan is generated according to the quantity-quality-time balance mechanism and the nutrition intervention mechanism, including:

[0026] determine energy intake distribution throughout the day and normal three-meal eating times according to the clock nutrition principle to synchronize nutritional intake with the human circadian rhythm;

[0027] determine post-exercise nutritional intake windows according to exercise training times in the exercise program;

[0028] based on the intervention direction, call the intake mechanism to determine total energy intake and nutritional formula, and call the nutritional quality mechanism to determine nutritional agents to be supplemented;

[0029] based on the eating time mechanism, integrate the energy intake distribution throughout the day, the normal three-meal eating times, and the post-exercise nutritional intake windows to generate a daily and weekly eating schedule and exercise coordination suggestion, forming an intervention plan;

[0030] generate the nutrition plan by integrating the total energy intake, the nutritional formula, the nutritional agents, and the intervention plan.

[0031] Optionally, the method further comprises:

[0032] match exercise intervention intensity levels according to grip strength, gait speed, sit-to-stand ability score, and balance ability score in the muscle function data;

[0033] According to the exercise intervention intensity level, an anti-resistance training action in a sitting or standing position is screened from a preset action library, and a resistance level of an elastic band or a dumbbell is matched;

[0034] Based on the exercise intervention intensity level, the anti-resistance training action, and the resistance level, an exercise scheme including a training mode, a training frequency, a training intensity, a training time, and matters needing attention is generated.

[0035] In a second aspect, a nutritional intervention system for sarcopenia patients is disclosed, which is used to implement the nutritional intervention method for sarcopenia patients in the first aspect. The system comprises:

[0036] A data acquisition module is configured to acquire multi-modal data of the patient, wherein the multi-modal data comprises basic information of the user, human body composition data, clinical phenotype data, nutritional assessment data, biochemical index data, muscle function data, and exercise preference data.

[0037] A data processing module is configured to determine a nutritional status, risk factors, and an intervention direction of the patient based on the multi-modal data, wherein the intervention direction is an intervention target after comprehensively considering the nutritional status and the risk factors.

[0038] A scheme generation module is configured to generate an individualized nutritional scheme according to a quantity-quality-time balance mechanism and a nutritional intervention mechanism based on the intervention direction, wherein the nutritional intervention mechanism comprises an intake quantity mechanism, a nutritional quality mechanism, and an eating time mechanism. The intake quantity mechanism is used to determine total energy intake and a nutritional formula, the nutritional formula comprises the types and quantities of food materials and a cooking method, the nutritional quality mechanism is used to determine nutritional agents that need to be supplemented, and the eating time mechanism is used to determine a daily meal time distribution and a cooperation timing sequence with an exercise scheme.

[0039] Optionally, the data acquisition module comprises:

[0040] A system interface unit is configured to interact with a hospital information system through a hypertext transfer protocol secure (HTTPS) to acquire the clinical phenotype data and the biochemical index data. The clinical phenotype data comprises disease conditions, comorbidities, and drug use conditions. The biochemical index data comprises protein indicators, inflammation indicators, and metabolism indicators.

[0041] At least one external device interface unit is configured to connect to and acquire data from at least one of the following devices:

[0042] A human body composition analyzer is configured to acquire the human body composition data, wherein the human body composition data comprises body weight, body mass index, muscle mass, and fat content distribution.

[0043] A handgrip dynamometer is configured to acquire grip strength.

[0044] a balance test module configured to collect a balance score;

[0045] a gaitway grating sensor configured to collect a gait speed;

[0046] a lift pressure sensor seat configured to collect a sit-to-stand score;

[0047] a circumference ruler configured to collect a limb circumference;

[0048] The grip strength, the balance score, the gait speed, and the sit-to-stand score are the muscle function data.

[0049] Optionally, the data collection module further comprises:

[0050] a diet assessment module configured to record the nutritional assessment data, the nutritional assessment data including dietary preferences and 24-hour dietary review;

[0051] a physical activity assessment module configured to record the physical activity preference data, the physical activity preference data including personal exercise habits, activity amount, exercise type, and activity frequency.

[0052] Optionally, the scheme generation module comprises:

[0053] a nutrition scheme module configured to execute the intake mechanism, the nutritional quality mechanism, and the eating timing mechanism, and output the nutrition scheme;

[0054] a physical activity scheme module configured to call a physical activity scheme generated by a preset rule library based on a physical activity intervention level matched by the data processing module.

[0055] Optionally, the system further comprises:

[0056] a report management module configured to generate, store, query, and print sarcopenia assessment reports, nutrition schemes, and physical activity schemes;

[0057] a user management module configured to manage patient archives and support addition, editing, deletion, and query of patients.

[0058] A third aspect of the embodiments of the present application discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the steps of the nutrition intervention method for a sarcopenia patient.

[0059] The embodiments of the present application have the following advantages:

[0060] In the embodiments of the present application, a comprehensive patient health portrait can be constructed by collecting multi-modal data such as patient basic information, human body composition data, clinical phenotype data, nutritional assessment data, biochemical index data, muscle function data, and exercise preference data. This multi-dimensional data collection method overcomes the limitations of a single data source, making the judgment of the patient's nutritional status and risk factors more accurate and comprehensive, and laying a solid data foundation for precise intervention.

[0061] By applying the quantity-quality-time opportunity balance mechanism in cooperation with the intake mechanism, the nutritional quality mechanism, and the eating opportunity mechanism, the nutritional intervention scheme is comprehensively optimized from the three dimensions of "quantity-quality-time". Among them, the intake mechanism ensures the accurate quantification of energy and nutrient supply; the nutritional quality mechanism supplements the nutritional preparation in a targeted manner; the eating opportunity mechanism scientifically matches the nutritional intake with the exercise training to maximize the nutritional utilization efficiency. This intervention mechanism makes the generated nutritional scheme not only meet the actual needs of the patient, but also has good executability.

[0062] In this way, the method converts the intervention process originally relying on clinical experience into a standardized process based on data-driven, and establishes a systematic intervention method through clear nutritional status analysis, risk factor identification, and intervention direction determination. This not only improves the scientificity and consistency of the intervention scheme, but also significantly improves the efficiency of medical work, and provides an effective scheme for the standardized diagnosis and treatment of sarcopenia. BRIEF DESCRIPTION OF DRAWINGS

[0063] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0064] Figure 1 is a step flow chart of a nutritional intervention method for a sarcopenia patient provided by the embodiments of the present application;

[0065] Figure 2 is a structural schematic diagram of a nutritional intervention system for a sarcopenia patient provided by the embodiments of the present application;

[0066] Figure 3 is a structural schematic diagram of an electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0067] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0068] The embodiment of the present application provides a nutritional intervention method for a sarcopenia patient. Figure 1 As shown in the figure, Figure 1 is a step flow chart of the nutritional intervention method for a sarcopenia patient provided by the embodiment of the present application. As shown in the figure, Figure 1 The nutritional intervention method for a sarcopenia patient can include steps S110 to S130:

[0069] Step S110: Collecting multi-modal data of the patient, the multi-modal data including patient basic information, human body composition data, clinical phenotype data, nutritional assessment data, biochemical index data, muscle function data and exercise preference data.

[0070] The patient basic information includes but is not limited to the age, gender, height, etc. of the patient, and the patient basic information is a benchmark parameter for determining the basic nutritional requirement threshold, physiological state assessment, and determining the normal or abnormal nutrition interval. For example, the nutritional requirement threshold of different age groups of the elderly is different.

[0071] The human body composition data can be obtained by a human body composition analyzer or other equipment, including body weight, body mass index (BMI), muscle mass, fat content distribution, etc. The human body composition data is used for objective evaluation of the degree of muscle loss and body composition, and is the core basis for diagnosing sarcopenia and calculating the basic energy consumption.

[0072] The clinical phenotype data covers the existing disease condition, comorbidities (such as chronic kidney disease, diabetes, hypertension) and drug use of the patient. The clinical phenotype data is used to identify key nutritional contraindications (such as protein restriction for patients with kidney disease), disease-specific nutritional requirements (such as blood glucose generation load control for patients with diabetes, high protein intake for patients with sarcopenia, etc.), and to investigate the influence of drugs on nutritional metabolism, and to provide targeted nutritional intervention opinions related to disease specificity, to ensure the safety of the intervention scheme.

[0073] The nutritional assessment data can be obtained through a dietary frequency questionnaire, a 24-hour dietary review or a patient diet record, including dietary preferences, 24-hour dietary review, diet records (actual food types and quantities consumed). This data is used for gap analysis, i.e., comparing actual intake with theoretical recommended amounts to identify structural problems such as "insufficient protein intake" or "excessive carbohydrate proportion".

[0074] Biochemical index data comes from blood and other body fluid tests, including protein indicators, inflammation indicators and metabolic indicators, etc. This data is used to reveal hidden malnutrition status and assess the body's protein assimilation capacity (i.e., whether it is easy to convert to muscle), providing metabolic level evidence for precise adjustment of nutrition support strategies.

[0075] Muscle function data can be measured by standardized equipment such as hand dynamometers, balance testers, step speed testers, etc., including grip strength, step speed, balance ability and 5 sit-to-stand times, etc. This data directly reflects the physical function status and is the core indicator for sarcopenia diagnosis, and is directly used to match the intensity and type of exercise intervention. For example, patients with slow step speed and poor balance have a higher risk of exercise, so they are assigned to sit-down resistance training videos (standing exercises are prone to falls); for example, different muscle strength requires different resistance for resistance training, such as different recommended dumbbell weights and elastic band resistance;

[0076] Exercise preference data includes personal exercise habits, daily activity levels, exercise types, and activity frequencies, which can be obtained through questionnaires or interviews to understand the patient's preferred exercise types, daily activity levels, and regular exercise time periods. This data is used to improve the compliance of exercise prescriptions and provides key reference for scheduling meal times.

[0077] In the embodiments of the present application, by collecting multi-modal data that can reflect the overall health status of the patient, a comprehensive patient health portrait can be constructed, providing a solid data foundation for subsequent construction of individualized intervention programs, ensuring the accuracy and comprehensiveness of subsequent analysis.

[0078] Step S120: Based on the multi-modal data, determine the nutritional status, risk factors and intervention direction of the patient, the intervention direction being the intervention target after comprehensively considering the nutritional status and the risk factors.

[0079] In the embodiments of the present application, after obtaining the multi-modal data of the patient, comprehensive operation and logical judgment are performed on the multi-modal data, and three levels of analysis conclusions are output, i.e., the nutritional status, risk factors and intervention direction of the patient.

[0080] The nutritional status is an objective description of the current nutritional status of the patient, for example: "daily protein intake is insufficient, only 60% of the recommended amount", "energy intake is excessive, but high-quality protein intake is insufficient". The nutritional status is obtained by correlating analysis of various patient data. For example, combining "advanced age" (patient basic information), "low muscle mass" (human body composition data), and "dietary records show insufficient protein intake" (nutritional assessment data), the conclusion of the current "protein-energy malnutrition" can be drawn. For another example, combining "low serum vitamin D level" (biochemical indicators) and "slow walking speed" (muscle function data), it can be judged that there is "muscle function decline related to vitamin D deficiency".

[0081] The risk factor is to identify potential risks of future health deterioration according to a medical knowledge base. For example, identifying "diabetic patients" (clinical phenotype data) but "prefer high GI (Glycemic Index, blood glucose generation index) food" (nutritional assessment data), and marking "blood sugar out of control risk"; identifying patients with "poor balance ability" (muscle function data), if recommended standing posture training, mark "high risk of falling".

[0082] The intervention direction is a set of intervention targets formed by comprehensively weighing the nutritional deficiencies listed in the nutritional status and the safety boundaries and future adverse outcome risks listed in the risk factors. The intervention direction at least includes: energy intake adjustment (amount), nutritional quality optimization (quality), and eating time (time) adjustment. For example, possible intervention directions are: "Direction 1: moderately increase the proportion of high-quality protein while ensuring stable blood sugar"; "Direction 2: supplement vitamin D and strengthen lower limb sitting posture resistance training"; "Direction 3: adjust the dietary structure, reduce the proportion of refined carbohydrates, and increase the source of high-quality protein".

[0083] Step S130: based on the intervention direction, generating an individualized nutrition plan according to the amount-quality-time balance mechanism and the nutrition intervention mechanism; wherein the nutrition intervention mechanism includes an intake amount mechanism, a nutritional quality mechanism, and an eating time mechanism, the intake amount mechanism is used to determine the total energy intake and the nutritional formula, the nutritional formula includes the types and quantities of food materials, and the cooking method, the nutritional quality mechanism is used to determine the nutritional preparation that needs to be supplemented and strengthened, and the eating time mechanism is used to determine the daily meal time distribution and the cooperation timing with the exercise plan.

[0084] In the embodiments of the present application, the quantity-quality-time balance mechanism is applied, which emphasizes the recovery or maintenance of body metabolic balance by synergistically regulating the total intake of nutrients (quantity), the quality of supplementation (quality), and the supply time (time). Based on this mechanism, the nutrition intervention mechanism of the intake mechanism, the nutrition quality mechanism, and the eating time mechanism is called to convert the abstract intervention direction determined in step S120 into a specific and executable individualized nutrition plan, which includes total energy intake, nutrition formula (i.e., types and quantities of food materials, cooking methods), nutritional preparations (for example, enteral / parenteral formula, functional food), and eating schedule.

[0085] Specifically, the intake mechanism is responsible for the "quantitative" part of the nutrition plan, specifically calculates the total energy intake (such as 1500 kcal) and nutrition formula (for example, recommended food material types and quantities) required by the patient per day according to the intervention direction (such as "increase protein"), and recommends healthy food cooking methods (such as replacing deep-frying with steaming, boiling, and stewing) to ensure that the nutrition target is achieved and easy to execute.

[0086] The nutrition quality mechanism is responsible for the "qualitative" part of the nutrition plan, and determines the nutritional preparations that need to be supplemented based on the specific deficiency or special needs of the patient. For example, for vitamin D deficiency, it is explicitly recommended to "take vitamin D3 800 IU per day"; for patients with dysphagia, it is recommended to "take 20 grams of whey protein powder per day".

[0087] The eating time mechanism is responsible for the "timing optimization" part of the nutrition plan, which formulates a scientific daily meal time distribution (such as small and frequent meals, five meals a day), and pays special attention to the timing of cooperation with exercise training. For example, it is explicitly recommended to "take a snack containing 20-25 grams of protein within 30 minutes after the completion of resistance training", so as to make full use of the post-exercise metabolic window and maximize the promotion of muscle protein synthesis.

[0088] In this way, through the synergistic effect of the above three mechanisms, the structured nutrition plan ultimately generated not only tells the patient "what to eat and how much to eat", but also guides the patient "how to eat and when to eat", realizing the leap from traditional experiential guidance to digital precise intervention.

[0089] By adopting the technical solution of the embodiments of the present application, a comprehensive patient health portrait can be constructed by collecting multiple modalities of data such as patient basic information, body composition data, clinical phenotype data, nutrition assessment data, biochemical index data, muscle function data, and exercise preference data. This multi-dimensional data collection method overcomes the limitations of a single data source, making the judgment of the patient's nutritional status and risk factors more accurate and comprehensive, and laying a solid data foundation for precise intervention.

[0090] By applying the quantity-quality-time balance mechanism in coordination with the intake mechanism, the nutritional quality mechanism, and the eating time mechanism, the nutritional intervention scheme is comprehensively optimized from the three dimensions of "quantity-quality-time". Among them, the intake mechanism ensures the accurate quantification of energy and nutrient supply; the nutritional quality mechanism supplements the nutritional preparation in a targeted manner; and the eating time mechanism scientifically matches the nutritional intake with the training, maximizing the nutritional utilization efficiency. This intervention mechanism makes the generated nutritional scheme not only meet the actual needs of the patient, but also has good executability.

[0091] In this way, the method converts the intervention process originally relying on clinical experience into a standardized process based on data-driven, and establishes a systematic intervention method through clear nutritional status analysis, risk factor identification, and intervention direction determination. This not only improves the scientificity and consistency of the intervention scheme, but also significantly improves the efficiency of medical work, providing an effective scheme for the standardized diagnosis and treatment of sarcopenia.

[0092] In an optional embodiment, the step S120 of "determining the nutritional status of the patient based on the multi-modal data" specifically includes steps A1 to A7:

[0093] Step A1: Establish a basal metabolic demand parameter based on the muscle mass and fat distribution in the human body composition data as the basis for energy calculation.

[0094] In the embodiments of the present application, the basal metabolic demand parameter is the starting point for accurately calculating the energy consumption of an individual. Based on the accurate human body composition data provided by the human body composition analyzer, such as muscle mass, body fat rate, and visceral fat area, an individualized basal metabolic demand parameter is established through a metabolic calculation model (for example, a formula taking lean body mass as the core variable). This parameter serves as the basis for all subsequent energy calculations, which means that two patients with the same body weight but different muscle and fat proportions have different daily energy consumption calculation bases. Patients with high muscle content have higher basal metabolic rates and require more energy, which ensures that patients with the same body weight but different muscle and fat proportions can obtain an individualized starting point that truly reflects their energy consumption potential.

[0095] Step A2: Calculate the actual total energy intake according to the 24-hour dietary review in the nutritional assessment data.

[0096] This step aims to obtain the patient's current real energy intake data. By analyzing and calculating the "24-hour dietary review" information in the nutritional assessment data, the actual total energy intake is calculated according to the food types, quantities, and cooking methods reported by the patient, and the food composition database is matched and converted. This data is a core indicator that objectively reflects the patient's recent dietary "quantity".

[0097] Step A3: Determine the total energy consumption of the patient according to the age, physical activity consumption, basal metabolic demand parameter, and food thermal effect in the patient basic information, and determine the daily meal energy target value in combination with the human body composition data and the preset weight control target; wherein the physical activity consumption is calculated based on the metabolic equivalent value corresponding to the activity duration and intensity reflected by the exercise preference data, and the food thermal effect is calculated according to the actual total energy intake at a preset proportion.

[0098] In the embodiment of the present application, the individualized metabolic benchmark established in step A1 (basal metabolic demand parameter) is further combined with various factors to accurately calculate the energy demand and determine the daily meal energy target value. Specifically, first, the physical activity consumption is calculated, the activity type is mapped to the standard metabolic equivalent value based on the activity duration and intensity reflected by the exercise preference data, and the energy consumed by daily physical activity is calculated; then, the food thermal effect is estimated, and the actual total energy intake calculated in step A2 is calculated at a preset empirical proportion (such as 10% of the total energy). Then, the patient's age, basal metabolic demand parameter, physical activity consumption and food thermal effect are combined to obtain the patient's individualized total energy consumption. Finally, based on the total energy consumption, the physiological state reflected by the human body composition data (such as the current body fat rate, muscle mass), and the preset weight control target (such as weight maintenance, moderate muscle gain or fat loss), the total energy consumption is corrected or adjusted, and the daily meal energy target value is finally determined.

[0099] Step A4: Compare the actual total energy intake with the daily meal energy target value to obtain the total energy intake deviation.

[0100] This step performs consistency evaluation at the energy level, directly compares the actual total energy intake calculated in step A2 with the daily meal energy target value determined in step A3, and obtains the quantitative total energy intake deviation. The deviation value (which can be positive, negative or zero) directly reflects the gap between the current energy intake of the patient and the theoretical demand target, and is a core index for evaluating the energy balance state.

[0101] Step A5: Obtain the macro-nutrient intake in grams by 24-hour dietary review, convert the macro-nutrient intake in grams to energy contribution value, calculate the energy supply ratio of each macro-nutrient, compare the energy supply ratio of each macro-nutrient with the preset target energy supply ratio, and obtain the energy supply ratio deviation of each macro-nutrient; the macro-nutrients include carbohydrates, fats and proteins.

[0102] Specifically, first, by analyzing the 24-hour dietary review, the intake of the three macronutrients of carbohydrates, fats and proteins is analyzed in grams. Then, according to the energy coefficient of each nutrient, the grams are converted into the energy contribution value of each (e.g. carbohydrates 4 kcal / g, proteins 4 kcal / g, fats 9 kcal / g). Then, the energy contribution value of each macronutrient is divided by the actual total energy intake to calculate its actual energy supply ratio in total energy. Finally, the calculated actual energy supply ratio is compared with the preset target energy supply ratio range (such as the Nutrition Society Dietary Guidelines) one by one to obtain the quantitative macronutrient energy supply ratio deviation. The macronutrient energy supply ratio deviation accurately characterizes the degree of deviation of the dietary structure from the ideal model in terms of "quality".

[0103] Step A6: According to the protein index, inflammation index and metabolism index in the biochemical index data, the hidden malnutrition status and protein assimilation capacity are evaluated.

[0104] Among them, the evaluation of hidden malnutrition can be determined by analyzing the protein index (such as serum albumin, prealbumin). For example, even if the patient self-reports that the diet is acceptable, through this step, "hidden" malnutrition caused by absorption disorders or chronic consumption can be identified.

[0105] At the same time, the inflammation index (such as C-reactive protein, interleukin-6) can evaluate the inflammation level, and the elevated inflammation index will indicate that the body is in a catabolic state, which will exacerbate muscle loss and interfere with the effect of nutritional intervention.

[0106] The evaluation of protein assimilation capacity can be achieved by analyzing the metabolism index (such as insulin-like growth factor-1). For example, the physiological potential of patients to convert ingested protein into their own muscle (i.e. assimilation capacity) can be evaluated. A patient with low insulin-like growth factor-1 levels may have low muscle synthesis efficiency even if he ingests sufficient protein, which means that the intervention strategy needs to be adjusted (such as improving the metabolic environment or increasing the protein dose).

[0107] In this way, the qualitative internal state evaluation is achieved through this step, which makes up for the deep-seated problems that may not be revealed by the simple diet analysis (steps A3, A4), i.e. the evaluation of hidden malnutrition status and protein assimilation capacity.

[0108] Step A7: Based on the basal metabolic demand parameters, the macronutrient energy supply ratio deviation, the hidden malnutrition and the protein assimilation capacity, the nutritional status is comprehensively determined, and the nutritional status subtyping conclusion characterizing the specific nutritional problems is output.

[0109] In the embodiments of the present application, the multi-dimensional information obtained in steps A1 to A6 is comprehensively determined to obtain a comprehensive decision (nutritional status), and finally output a nutritional status classification conclusion representing a specific nutritional problem. The conclusion can be a structured and clinically readable description, for example, the output can be: "Patient A: normal metabolic demand type, energy intake is balanced, but protein assimilation ability suggests a risk of decline".

[0110] Specifically, the basal metabolic demand parameter, the macro-nutrient energy supply ratio deviation, the hidden malnutrition, and the protein assimilation ability are logically associated and weighted to obtain a nutritional status classification conclusion representing a specific nutritional problem. This classification conclusion directly points to a specific nutritional problem category, providing a clear and direct problem list for subsequent development of highly targeted intervention direction.

[0111] By using the technical solutions of the embodiments of the present application, individualized metabolic benchmarks are established, scientific energy targets are set, actual intake is quantified, energy balance and dietary structure deviation are analyzed, core nutrient risk assessment is focused on, and the internal metabolic state is explored. Finally, intelligent comprehensive decision is realized. Moreover, the process is completely data-driven and algorithmically supported, reducing subjective bias. Not only does it accurately identify apparent "intake deficiency" and "structure imbalance", but it also reveals deep "metabolic resistance", thereby laying a precise foundation for subsequent generation of highly individualized, safe and effective nutrition programs.

[0112] In an optional embodiment, the step S120 of "determining the risk factors of the patient based on the multi-modal data" specifically includes steps B1 to B6:

[0113] Step B1: Based on the actual total energy intake and the daily meal energy target value, the difference between energy intake and energy demand is calculated to identify the risk of energy imbalance caused by excessive or insufficient energy.

[0114] This step is a basic risk assessment at the metabolic balance level, which quantifies the core metabolic risk caused by "quantity" deviation from the perspective of energy balance. Specifically, based on the actual total energy intake and the daily meal energy target value, the difference between energy intake and energy demand is calculated. If the difference indicates a positive energy balance (i.e., actual intake is consistently higher than energy demand), it identifies the risk of fat accumulation and insulin resistance caused by excessive energy, which may in the long term lead to obesity and type 2 diabetes and other adverse problems. If the difference indicates a negative energy balance (i.e., actual intake is consistently lower than energy demand), it identifies the risk of muscle protein breakdown and lean body mass loss caused by insufficient energy, which will directly exacerbate malnutrition and sarcopenia.

[0115] Step B2: Identify disease-related nutritional contraindications and specific requirements based on comorbidities and medication usage in the clinical phenotype data.

[0116] Wherein the nutritional contraindications include but are not limited to protein intake restriction for patients with kidney disease, and the specific requirements include increased protein intake for patients with sarcopenia.

[0117] This step is used to determine the boundary conditions of quality, quantity, and timing in the nutritional plan. Specifically, by analyzing the patient's comorbidities (such as chronic kidney disease, diabetes, heart failure) and medication usage, and combining with medical knowledge base, two types of constraints are identified, namely disease-related nutritional contraindications and specific requirements.

[0118] Wherein the nutritional contraindications refer to nutrients that must be restricted or avoided due to disease status. For example, for patients with kidney disease, protein and phosphorus, potassium intake should be restricted to avoid aggravating the burden on the kidneys. The specific requirements refer to the additional nutritional requirements due to disease or physiological status. For example, for patients with sarcopenia, protein intake should be increased under safe conditions.

[0119] In this way, the boundary conditions that cannot be exceeded in the intervention plan are determined, and the contradictory requirements between coexisting diseases (such as high protein for sarcopenia and low protein for kidney disease) can be accurately identified and managed, laying the foundation for subsequent development of intervention plans that seek the optimal solution within a safe range.

[0120] Step B3: Identify the risk of nutritional imbalance caused by dietary structure based on the energy-providing ratio deviation of macronutrients.

[0121] This step is used to assess the risk of imbalance in the quality of dietary structure. The energy-providing ratio deviation of macronutrients calculated in the nutritional status assessment (which quantifies the deviation of the actual energy-providing ratio of carbohydrates, fats, and proteins from the recommended range) is used to identify specific dietary structure risks.

[0122] For example, if the deviation shows that the carbohydrate energy-providing ratio is too high, the risk of "highly refined carbohydrate diet" is identified, which may be related to blood glucose fluctuations and insulin resistance. If the deviation shows that the fat energy-providing ratio is too high or the protein energy-providing ratio is too low, the risks of "excessive fat intake" or "relative protein deficiency" are identified accordingly.

[0123] In this way, abstract "unhealthy eating habits" are converted into specific, quantifiable, and intervenable risk points, ensuring that subsequent dietary recommendations can directly optimize the patient's real eating behavior.

[0124] Step B4: Identify whether there is a risk of circadian rhythm disorder caused by late eating, skipping meals, or meal rhythm disorder based on the eating time reflected in the nutritional assessment data.

[0125] This step is the risk assessment of eating timing behavior and rhythm. Specifically, by analyzing the eating time regularity reflected in the nutrition assessment data (such as diet records); identifying whether there is high-energy eating at night (especially carbohydrate-rich dinner), which may inhibit night fat oxidation, disturb blood glucose rhythm, and lead to increased metabolic burden; identifying whether there is skipping meals (such as habitual skipping breakfast) or extremely irregular mealtime behavior, which can interfere with the body's inherent circadian rhythm, leading to decreased insulin sensitivity and reduced metabolic efficiency. Finally, by comprehensively judging whether the above behavior patterns constitute a risk of circadian rhythm disorder, which is a potential cause of metabolic syndrome, obesity and other diseases.

[0126] Step B5: Calculate the actual protein intake in the nutrition assessment data, and compare it with the recommended protein intake based on age and body composition data to identify the risk of insufficient protein intake.

[0127] This step is the risk assessment of key nutrients for sarcopenia; specifically, the actual protein intake is calculated from the nutrition assessment data (such as 24-hour dietary review), and at the same time, according to the patient's age (considering the change of protein demand with age), body composition data (in the case of obesity, corrected body weight is used for correction), disease conditions (such as kidney disease, according to CKD (Chronic Kidney Disease) stage to call the corresponding protein intake recommendation coefficient), call algorithm model to determine its individualized protein recommended intake (for example, for old people diagnosed with sarcopenia, the recommended amount may be 1.2-1.5 grams per kilogram of body weight per day). By comparing the actual intake with the recommended amount, the risk of insufficient protein intake, which is crucial for maintaining muscle health, is identified.

[0128] Step B6: Based on the energy imbalance risk, the nutrition imbalance risk, the nutritional contraindications and the specific needs, the circadian rhythm disorder risk, the protein intake insufficient risk, the risk factors are comprehensively determined, and the specific risk label and nutrition risk level are output.

[0129] In the embodiments of the present application, the various risks identified in steps B1 to B5 are integrated and analyzed for weight to generate risk factors and output specific risk labels and nutritional risk levels. Among them, the risk label can be a structured list of risk items containing specific descriptions. For example, ["energy negative balance risk", "high carbohydrate diet structure risk", "night eating rhythm risk", "protein intake deficiency risk"]. The nutritional risk level can be a comprehensive nutritional risk level (such as "high risk", "medium risk", "low risk") evaluated by a pre-set rule model based on the number, nature and severity of risk labels. For example, the presence of "energy negative balance", "protein intake deficiency" and "chronic kidney disease" contraindications may be rated as "high risk".

[0130] The technical solutions of the embodiments of the present application construct a risk assessment system covering five dimensions of "energy balance, disease safety boundary, diet structure, eating rhythm, and core nutrients", and finally intelligently output structured risk labels and risk levels, realizing the transformation from complex risk information to intuitive and classifiable clinical decision support. This provides the most critical and reliable basis for subsequent development of individualized intervention programs.

[0131] In an alternative embodiment, the intervention direction includes at least energy intake adjustment, nutritional quality optimization, and eating time adjustment; the step S130 of "generating an individualized nutrition program based on the intervention direction according to the quantity-quality-time balance mechanism and the nutrition intervention mechanism" specifically includes steps C1 to C5:

[0132] Step C1: According to the clock nutrition principle, determine the energy intake distribution throughout the day and the normal three meals eating time to synchronize the nutritional intake with the human circadian rhythm.

[0133] In the embodiments of the present application, the clock nutrition principle is applied to plan an eating pattern synchronized with the circadian rhythm based on the body's internal biological clock. Specifically, determining the energy intake distribution throughout the day can set a higher proportion of energy and nutrients for breakfast, moderate for lunch, and actively limit energy intake for dinner. For example, generate a distribution suggestion of "35% of total daily energy for breakfast, 40% for lunch, and 25% for dinner". Determining the normal three meals eating time can be understood as recommending fixed breakfast, lunch and dinner time points (such as breakfast at 7:30, lunch at 12:30, and dinner at 18:30) in combination with the patient's lifestyle to stabilize the biological clock signal.

[0134] This energy distribution pattern synchronized with the circadian rhythm helps to improve daytime insulin sensitivity, optimize glucose metabolism and reduce nighttime metabolic burden, thereby laying a foundation for improving overall metabolic health at the timing level.

[0135] Step C2: Determine the post-exercise nutrition intake window according to the exercise training time in the exercise program.

[0136] This step is used to achieve the timing coordination of nutrition and exercise. Specifically, based on the individualized exercise program generated for the patient, the exercise training time (e.g., the time point of resistance training) planned in the exercise program is identified, and based on this, a post-exercise nutrition intake window is defined.

[0137] In some embodiments, the post-exercise nutrition intake window is set within a certain period of time after the training. The best time for muscle protein synthesis in the elderly is within 2-3 hours after exercise, so protein should be supplemented quickly after resistance training. In addition, for special groups such as diabetics, it is also necessary to remind them to supplement carbohydrates before exercise to avoid the risk of hypoglycemia.

[0138] In this way, the post-exercise nutrition intake window is determined according to the exercise training time in the exercise program, achieving precise coordination of nutrition and exercise in the time dimension.

[0139] Step C3: Based on the intervention direction, call the intake amount mechanism to determine the total energy intake and nutrition formula, and call the nutrition quality mechanism to determine the nutritional preparation to be supplemented.

[0140] This step is used to generate a "quantity" and "quality" plan; specifically, the intake amount mechanism is called, which converts the energy intake adjustment target into a specific, digital total energy intake value (such as 1800 kcal per day) and a fine nutrition formula. The nutrition formula refers to the types and quantities of food materials, as well as the cooking method.

[0141] The nutrition quality mechanism is called, which converts the "nutrition quality optimization" target into a specific product recommendation for additional supplementation, i.e., determines the nutritional preparation to be supplemented. Nutritional preparations include but are not limited to enteral nutrition formulas (such as specific protein powder), parenteral nutrition support plans, or functional foods (such as vitamin D supplements), and clearly specify their types and dosages (such as "supplement 20 grams of whey protein powder per day").

[0142] Step C4: Based on the eating timing mechanism, integrate the whole-day energy intake distribution, the normal three-meal eating timing, and the post-exercise nutrition intake window to generate a daily and weekly eating schedule and exercise coordination recommendation, forming an intervention plan.

[0143] This step is the integration and plan generation of the "timing" plan. Specifically, the eating timing mechanism is applied to integrate the timing elements determined in the previous step: i.e., the whole-day energy distribution of Step C1 and the normal three-meal timing are used as the basic framework, and the post-exercise nutrition intake window of Step C2 is used as a key event node embedded in the framework.

[0144] Thus, a structured intervention plan is generated, which is specifically manifested as a daily and weekly eating schedule (e.g., specific time points and contents of each meal / snack) and detailed exercise matching suggestions (e.g., "within 30 minutes after resistance training on Monday, Wednesday, and Friday, a protein supplement snack needs to be completed").

[0145] Step C5: generating the nutrition plan based on the total energy intake, the nutrition formula, the nutrition preparation, and the intervention plan.

[0146] This step is the generation of the final nutrition plan, specifically, the quantitative targets (total energy intake, nutrition formula, nutrition preparation) generated in step C3 are integrated with the intervention plan generated in step C4 to generate a structured and executable individualized nutrition plan, which is a health management file that clearly answers all core questions of "how much to eat (total energy), what to eat (nutrition formula and preparation), when to eat, and how to match exercise (intervention plan)", and can be directly used to guide the daily practice of patients.

[0147] The technical solution of the embodiment of the present application generates an individualized nutrition plan by precisely calculating and integrating the macroscopic goals of intervention direction, the clock nutrition principle, the exercise coordination strategy, and the "quantity, quality, and time" mechanism. It realizes the seamless connection from clinical evaluation to executable plan, improves the scientificity and metabolic benefit of nutrition intervention by introducing the timing concept of "clock nutrition" and "exercise nutrition coordination", and finally generates a plan with clear quantitative indicators and specific behavior guidance, which provides a reliable benchmark for objective monitoring and dynamic adjustment of intervention effect.

[0148] In an optional embodiment, the method further includes the following steps D1 to D3 in addition to the above steps:

[0149] Step D1: matching the exercise intervention intensity level according to the grip strength, step speed, sit-to-stand ability score, and balance ability score in the muscle function data.

[0150] Among them, grip strength directly reflects upper limb muscle strength and is the core basis for determining the initial resistance of dumbbells or elastic bands. Step speed and sit-to-stand ability (e.g., 5 sit-to-stand times) scores comprehensively reflect lower limb muscle strength, power, and body function, and are the key to determining whether the patient can safely perform standing, walking, or high-intensity lower limb training. Balance ability score is a core indicator for safety risk assessment. For patients with poor balance ability (e.g., unable to complete half-foot standing), the system will automatically match a low intensity level and preferentially avoid training movements that are unstable in a standing position, thereby fundamentally preventing the risk of falling.

[0151] The exercise intervention intensity level can be divided into three different levels: initial, intermediate and high. The patient is classified into the corresponding exercise intervention intensity level through comprehensive analysis of the muscle function data measured objectively.

[0152] Step D2: According to the exercise intervention intensity level, the resistance training movements in sitting or standing position are screened from the preset movement library, and the resistance level of the elastic band or dumbbell is matched.

[0153] In the embodiments of the present application, a preset movement library containing various variants such as sitting and standing positions is pre-set, and the movement is intelligently screened based on the matched exercise intervention intensity level of step D1. For example, sitting resistance movements (such as sitting leg flexion and extension) are screened for patients with poor balance to completely exclude the risk of falling; standing movements are recommended for patients with functional capabilities.

[0154] At the same time, according to the patient's grip strength, upper limb strength and other data, the tension level of the elastic band or the specific weight of the dumbbell (such as 2 kg, 5 kg) is matched for the patient, to ensure that the resistance of the training is effective and safe for the patient, neither too light to be ineffective, nor too heavy to cause injury or be unable to complete.

[0155] Step D3: Based on the exercise intervention intensity level, the resistance training movement and the resistance level, an exercise program containing training method, training frequency, training intensity, training time and precautions is generated.

[0156] The training method refers to the training movement, which can give the name, illustration or video guidance of each resistance training movement screened in step D2 in the exercise program. The training frequency is determined according to the exercise intervention intensity level, which specifies the number of training days per week (such as 2-3 times per week for beginners, and 3-4 times per week for intermediate and advanced levels). The training intensity refers to the number of sets and times of each movement, as well as the resistance level. The training time refers to the duration of a single training. The precautions provide key safety and execution prompts; for example, for patients with poor balance, it is noted that "all movements are completed on a stable chair".

[0157] This step integrates the elements (intensity, movement, resistance) determined in steps D1 to D2, and further refines it into a complete, clear and executable exercise program. Specifically, the training frequency (such as 3 times per week) can be determined according to the exercise intervention intensity level, and for each selected resistance training movement, the specific number of sets (such as 3 sets) and times (such as 10-15 repetitions per set) are specified, to finally generate a clear exercise program.

[0158] By adopting the technical solutions of the embodiments of the present application, high-risk exercise content is eliminated from the source by performing intensity grading and safety pre-screening based on objective function data in step D1; the applicability and safety of the training prescription to each patient are ensured by performing double personalized matching of actions and resistance in step D2; and finally, a complete exercise prescription covering the five elements of mode, frequency, intensity, time and matters needing attention is generated in step D3, so as to convert complex exercise science principles into clear guidelines that can be directly followed and executed by patients. The precision and individualization of the exercise prescription are realized, and the effectiveness and feasibility of the training are ensured by ensuring that each training suggestion is highly consistent with the actual functional status of the patient and the equipment conditions.

[0159] The embodiments of the present application provide a nutritional intervention system for sarcopenia patients, which is used to implement the nutritional intervention method for sarcopenia patients described in the above embodiments. Referring to Figure 2 Figure 2 is a schematic diagram of a nutritional intervention system for sarcopenia patients provided by the embodiments of the present application. Specifically, the nutritional intervention system for sarcopenia patients can include:

[0160] a data acquisition module, configured to acquire multi-modal data of the patient, the multi-modal data including user basic information, human body composition data, clinical phenotype data, nutritional assessment data, biochemical index data, muscle function data, and exercise preference data;

[0161] a data processing module, configured to determine a nutritional status, risk factors and intervention direction of the patient based on the multi-modal data, the intervention direction being an intervention target after comprehensively considering the nutritional status and the risk factors;

[0162] a scheme generation module, configured to generate an individualized nutritional scheme based on the intervention direction according to a quantity-quality-time balance mechanism and a nutritional intervention mechanism; wherein the nutritional intervention mechanism includes an intake quantity mechanism, a nutritional quality mechanism and an eating time mechanism, the intake quantity mechanism is used to determine total energy intake and a nutritional formula, the nutritional formula includes the types and quantities of food materials and cooking methods, the nutritional quality mechanism is used to determine nutritional agents that need to be supplemented, and the eating time mechanism is used to determine daily meal time distribution and cooperation timing with the exercise scheme.

[0163] ​In the embodiments of the present application, the data acquisition module is responsible for comprehensively and accurately obtaining the multi-modal data required for constructing the patient health portrait. Specifically, the data acquisition module can connect and drive special medical detection equipment through the interface unit, for example, communicate with the handgrip dynamometer and girth tape through the Bluetooth protocol, and interact with the human body composition analyzer, balance test module and treadmill sensor through the serial port, thereby realizing the automatic and high-precision acquisition of muscle function data and human body composition data, and avoiding the errors of manual input. The data acquisition module can also obtain clinical phenotype data and biochemical index data from other information systems (such as hospital information systems, laboratory information systems); at the same time, the software front end questionnaire and form are used for doctors or patients to input user basic information, nutrition assessment data and exercise preference data.

[0164] The data processing module receives the multi-modal data from the data acquisition module and executes the built-in algorithm model to determine the patient's nutritional status, risk factors and intervention direction. Specifically, the workflow of the data processing module is: first, the multi-source data collected is cleaned, standardized and associated; then, based on the pre-set medical knowledge base and algorithm rules (such as gap analysis algorithm, risk assessment model), the data is deeply mined. Its core function is to determine the nutritional status, risk factors and intervention direction. Among them, the intervention direction is the key decision result output by the module, which is the strategic and general intervention target (for example, "muscle gain and fat loss under the premise of safety", "sugar control while improving inflammation") based on the comprehensive weighing of the nutritional status (current problem) and risk factors (future hidden trouble), providing clear and high-level guidance for the scheme generation module.

[0165] The scheme generation module is responsible for converting the abstract intervention direction into a specific and quantifiable nutrition scheme. It internally encapsulates a nutrition intervention mechanism composed of intake amount mechanism, nutrition quality mechanism and eating time mechanism, and the scheme generation module calls the three sub-mechanisms according to the intervention direction output by the data processing module and applies the quantity-quality-time balance mechanism. Among them, the intake amount mechanism executes the calculation logic according to the energy and nutrition targets in the intervention direction, and outputs the specific total energy intake (such as 1800 kcal) and nutrition formula (i.e., the types and quantities of food materials, cooking methods). The nutrition quality mechanism determines the nutritional preparations that need to be supplemented (for example, enteral / parenteral formula, functional food) according to the needs of micronutrients and supplements in the intervention direction. The eating time mechanism determines the daily meal time distribution (such as "five meals a day") according to the patient's work and rest and exercise rules, and especially pays attention to the cooperation timing with exercise training (such as "supplement protein and fast sugar within 30 minutes after exercise"). Finally, the scheme generation module integrates the output results of the three mechanisms to generate a complete and complete individualized nutrition scheme.

[0166] The technical scheme of the embodiment of the application realizes seamless integration and automatic processing of multi-source heterogeneous data, realizes automatic acquisition and convergence of multi-channel data from special equipment, a hospital information system, manual input and the like through a data acquisition module, breaks a "data island" in a medical scenario, provides a complete data basis for accurate evaluation, and greatly reduces the workload and error rate of manual input. Moreover, the data processing module and the scheme generation module form an efficient "analysis-decision-execution" closed loop, which converts a fuzzy decision-making process depending on clinical experience into an automatic process based on clear algorithms and rules, which is repeatable and verifiable, thereby guaranteeing the objectivity, scientificity and consistency of the evaluation results and the intervention scheme. In addition, the standardized output and the highly individualized customization of the intervention scheme are unified, the modular design of the system, especially the three mechanisms encapsulated in the scheme generation module, ensures that the output nutritional scheme is standardized in structure and elements, and since the input is based on individual multi-modal data, each scheme finally generated is highly individualized in specific content (quantity, quality and timing), thereby perfectly balancing the efficiency of the standardized process and the precision requirement of individualized medical treatment.

[0167] In an optional embodiment, the data acquisition module comprises:

[0168] a system interface unit configured to interact with a hospital information system through a hypertext transfer protocol secure (HTTPS) to obtain the clinical phenotype data and the biochemical index data; the clinical phenotype data comprises disease conditions, comorbidities and drug use conditions; and the biochemical index data comprises protein indicators, inflammation indicators and metabolism indicators;

[0169] at least one external device interface unit configured to connect to and obtain data from at least one of the following devices:

[0170] a body composition analyzer configured to acquire the body composition data, the body composition data comprising body weight, body mass index, muscle mass and fat content distribution;

[0171] a handgrip dynamometer configured to acquire handgrip strength;

[0172] a balance test module configured to acquire balance ability scores;

[0173] a gait optical grating sensor configured to acquire gait speed;

[0174] a lift and pressure sensor chair configured to acquire sit-to-stand ability scores;

[0175] a circumference tape configured to acquire limb circumference;

[0176] The handgrip strength, the balance ability scores, the gait speed and the sit-to-stand ability scores are the muscle function data.

[0177] In the embodiments of the present application, the system interface unit is the hub for seamless integration of the system with the existing information ecosystem of the hospital. It performs secure data interaction with the hospital information system, laboratory information system, etc. through the Hypertext Transfer Protocol Secure (HTTPS) to obtain the clinical phenotype data and the biochemical index data.

[0178] The clinical phenotype data can be directly obtained from the structured electronic medical record of the patient, including the disease condition, comorbidities (such as diabetes, chronic kidney disease), and medication use. This provides authoritative and timely diagnostic evidence for subsequent identification of nutritional contraindications and disease-specific needs. The biochemical index data can be automatically obtained from the system to obtain the latest laboratory test results, including protein indicators (such as serum albumin, prealbumin), inflammation indicators (such as C-reactive protein), and metabolic indicators (such as insulin-like growth factor-1). This provides objective biochemical evidence for the assessment of hidden malnutrition and protein assimilation capacity.

[0179] In this way, through the system interface unit, the tedious process of manual review and repeated entry of medical record information by medical staff is avoided, greatly improving the efficiency and accuracy of data collection, and ensuring the real-time nature of clinical data.

[0180] The external device interface is used to connect and control a series of specific medical detection devices to achieve standardized and digital collection of muscle function data and human body composition data. These interfaces are usually based on communication protocols such as Bluetooth, serial port, Universal Serial Bus (USB), Transmission Control Protocol (TCP), and Internet Protocol (IP) to achieve stable and reliable data transmission.

[0181] The human body composition analyzer accurately collects human body composition data including body weight, body mass index, muscle mass of limbs and trunk, body fat percentage, and visceral fat area through techniques such as bioelectrical impedance analysis. This is the most critical basis for assessing muscle loss and calculating basal metabolic rate.

[0182] The handgrip dynamometer is used to quantitatively assess upper limb muscle strength. The collected grip strength data is one of the key indicators for sarcopenia diagnosis and strength level classification.

[0183] The balance test module is usually a platform equipped with pressure sensors to objectively assess the static balance ability of patients, outputting quantitative balance ability scores. This data is crucial for assessing fall risk and developing safe exercise programs.

[0184] Gait Raster Sensor refers to a raster or infrared sensor embedded in a dedicated gaitway, which is used to accurately measure the time required for a patient to walk a fixed distance (e.g. 4 meters), so as to calculate the gait speed. Gait speed is a core indicator reflecting the physical function status.

[0185] The lift pressure receptor seat is used to record the time required for a patient to complete 5 standing and sitting, i.e. the standing and sitting ability score, in the standard "5 times standing and sitting test", and the data effectively reflects the lower limb muscle strength and power.

[0186] The girth meter is an intelligent electronic device for collecting limb girth, especially calf girth. Calf girth is an important and easily accessible objective indicator in sarcopenia screening (such as SARC-CalF).

[0187] By the collaborative work of the system interface unit and the external device interface unit, the clinical data from the information system and the function and composition data from the special hardware device are integrated, which provides a solid, reliable and multi-dimensional multi-modal data basis for the subsequent data processing and analysis module, and fundamentally guarantees the accuracy and individualization level of the finally generated nutrition and exercise scheme.

[0188] In an alternative embodiment, the data collection module further comprises:

[0189] The diet assessment module is used to record the nutrition assessment data, which includes dietary preferences, 24-hour meal review;

[0190] The exercise assessment module is used to record the exercise preference data, which includes personal exercise habits, activity amount, exercise type and activity frequency.

[0191] In the embodiment of the present application, the diet assessment module is a special function unit integrated in the system software, which systematically records the meal-related information of the patient through structured and guided human-computer interaction, thereby forming the nutrition assessment data. For example, the diet assessment module can guide the patient or medical staff to input dietary preferences, 24-hour meal review and diet records through graphical interfaces, forms or voice input, etc.

[0192] Among them, the dietary preference is used to record the patient's preference for food types, taboos, allergy history and preferred cooking flavors (such as light, spicy, etc.); these information is the key to ensure that the subsequent nutrition scheme has high compliance, avoiding recommending foods that patients dislike or are intolerant to. The 24-hour meal review can guide the patient to recall and record all the food types, specific quantities and cooking methods consumed in the past 24 hours through a standardized questionnaire process; this data provides the basis for quantitative nutrition analysis (such as calculating the actual intake of protein and carbohydrate) and is the core basis for identifying current dietary problems (such as insufficient intake or structural imbalance). In this way, the dietary detection module converts subjective and scattered dietary information into structured and analyzable digital nutrition assessment data, providing an important source of behavioral data for subsequent gap analysis and risk identification.

[0193] The exercise evaluation module is a software functional unit for quantifying the patient's physical activity level, and is specially responsible for recording exercise preference data. Specifically, the exercise evaluation module can collect exercise habits, daily activity amount, exercise type, and activity frequency through questionnaires, logs, or data interfaces with wearable devices (such as smart bracelets).

[0194] Among them, the personal exercise habit is used to record the patient's preferred exercise type (such as walking, taijiquan, swimming, etc.), the usual exercise frequency (such as several times a week) and the habit exercise time period (such as morning or evening); these information is used to ensure that the subsequent generated exercise scheme meets the patient's interest and life rhythm, thereby improving the long-term persistence feasibility. The daily activity amount quantifies the patient's overall energy consumption level through patient self-evaluation (such as "sedentary", "light activity", "high activity") or through the interface to obtain the daily step count, calorie consumption and other data estimated by the wearable device. This data is an indispensable correction parameter for calculating the daily total energy requirement in the intake mechanism, ensuring that the energy recommendation of the nutrition scheme matches the patient's actual consumption. In this way, the exercise evaluation module digitizes the patient's exercise willingness and ability, making the finally generated exercise scheme and the coordinated nutrition timing arrangement truly realize individual customization.

[0195] The technical scheme of the embodiment of the present application uses the dietary evaluation module and the exercise evaluation module as important components of the data acquisition module, and together with the hardware interface and the system interface unit forms a multi-modal data acquisition system covering physiological, clinical, biochemical, behavioral and preference dimensions. Ensures that all subsequent analysis and decision-making is not only based on objective medical data, but also deeply integrates the patient's subjective will and life habits, which is the cornerstone of truly individualized and highly compliant intervention scheme.

[0196] In an optional embodiment, the scheme generation module comprises:

[0197] a nutrition regimen module for executing the intake mechanism, the nutrition quality mechanism and the meal timing mechanism, and outputting the nutrition regimen;

[0198] a movement regimen module for generating a movement regimen based on the movement intervention level matched by the data processing module.

[0199] In the embodiments of the present application, the nutrition regimen module is a core engine for generating individualized nutrition regimen, which encapsulates and executes the nutrition intervention mechanism to generate the nutrition regimen. Specifically, the nutrition regimen module receives the intervention direction (for example, "increase protein intake under the premise of controlling sugar") from the data processing module, and then calls three sub-mechanisms (intake mechanism, nutrition quality mechanism and meal timing mechanism) in parallel or series to operate and decide, to obtain the final nutrition regimen.

[0200] The movement regimen module is a dedicated engine for generating individualized movement regimen, which works in parallel with and cooperates with the nutrition regimen module. The input of the module is the movement intervention level (for example, "primary, poor balance ability, need to sit posture training") matched by the data processing module, which is obtained based on the comprehensive analysis of muscle function data (grip strength, walking speed, balance ability, etc.); based on this movement intervention level, the module calls a preset rule library, which stores preset movement method rules for different levels and different physical conditions. For example, a safe movement library suitable for the level (such as presetting a sit posture movement for a primary poor balance person), a recommended training frequency, a group number and a range of times, and a corresponding equipment resistance level selection suggestion. By applying these movement method rules, the movement regimen module generates a structured movement regimen that strictly matches the functional status of the patient, with specific content such as training movements, equipment, group number, times and frequency.

[0201] By adopting the technical solutions of the embodiments of the present application, the division and cooperation of the nutrition regimen module and the movement regimen module realize functional decoupling and professional processing, respectively handle the complex rules and calculations in the fields of nutrition and exercise science, so that the system architecture is clear, and subsequent independent maintenance, optimization and upgrading are facilitated. The two modules do not work in isolation. For example, the movement schedule generated by the movement regimen module is transmitted to the nutrition regimen module as a key input parameter for accurately setting the post-exercise nutrition window in the meal timing mechanism. This dynamic interaction ensures that the final output of the nutrition and movement regimen is highly synchronized in terms of timing and goals.

[0202] In an optional embodiment, the system further comprises:

[0203] a report management module for generating, storing, querying and printing sarcopenia assessment reports, nutrition regimens and movement regimens;

[0204] User management module, used for managing patient files, supporting the addition, editing, deletion and query of patients.

[0205] In the embodiments of the present application, the report management module is the management center and display window of all output results of the system, and is responsible for the whole life cycle management of key documents generated in the evaluation and intervention process.

[0206] Among them, the generation means that the module receives structured data from the data processing module and the scheme generation module, and automatically generates three core documents (sarcopenia evaluation report, nutrition scheme and exercise scheme) according to the pre-defined and standardized report template. The sarcopenia evaluation report is used to comprehensively present the detection data, nutritional status analysis, risk factor identification and final intervention direction conclusion of the patient; the nutrition scheme formats the individualized nutrition suggestion in the form of data into a clear and easy-to-understand prescription document containing all elements of "quantity-quality-time". The exercise scheme converts the generated individualized exercise prescription into a guidance document containing action illustrations (such as calling preset pictures or video links), frequency, group number and times.

[0207] Storage means that all generated reports and related data are stored in the system database after encryption, forming a complete electronic medical record file, which is convenient for tracing historical records and conducting long-term efficacy comparison analysis. Query means providing multiple search methods (such as according to patient ID (Identity, identity), name, date range, etc.), for medical staff to quickly query and review any historical report. Print support prints electronic reports into paper documents, which is convenient for inclusion into the physical medical record of the patient or directly delivered to the patient to meet the needs of different clinical workflow.

[0208] The user management module is the administrator of all patient information in the system, ensuring the accuracy, integrity and uniqueness of the user file in the system. Among them, managing patient files means that the module maintains a centralized patient information database and establishes an independent electronic file for each patient. The file is associated with all evaluation data, generated reports and schemes of the patient in the system.

[0209] In addition, the user management module supports the addition, editing, deletion and query of patients. The addition refers to creating a file for a new patient, entering or automatically obtaining the basic information (such as name, gender, age, height, etc.) of the user through a system interface, and the system can automatically generate a unique patient ID according to the preset rules (such as hospital code + date + serial number). The editing refers to that when the patient information (such as contact information, height and weight) changes, the authorized user (such as medical staff) can update and edit the file information to ensure the timeliness of the data. The deletion refers to supporting the deletion operation (usually logical deletion) of a specific patient file under the premise of complying with the medical data management regulations, so as to manage invalid or test data. The query refers to providing powerful query functions, allowing medical staff to quickly locate the target patient through patient ID, name, mobile phone number and other keywords, so as to efficiently perform subsequent detection, report viewing and other operations.

[0210] By adopting the technical solutions of the embodiments of the present application, the report management module and the user management module jointly constitute the infrastructure for stable and efficient operation of the system, effectively encapsulate, manage and deliver the intelligent achievements generated by the core algorithm module, ensure the integrity, standardization and traceability of the entire evaluation and intervention process, and greatly improve the practical value and user experience of the system in real medical scenarios.

[0211] The embodiments of the present application also provide an electronic device, which refers to Figure 3 , Figure 3 is a structural schematic diagram of an electronic device provided by the embodiments of the present application. As shown in Figure 3 , the electronic device 300 includes a memory 310 and a processor 320, the memory 310 and the processor 320 are in communication connection through a bus, the memory 310 stores a computer program, the computer program can run on the processor 320, and then the steps of the nutritional intervention method for sarcopenia patients are realized.

[0212] Each of the embodiments in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same and similar parts between the embodiments can be referred to each other.

[0213] Although the preferred embodiments of the embodiments of the present application have been described, those skilled in the art can make other changes and modifications to the embodiments once they know the basic creative concept. Therefore, the appended claims are intended to include the preferred embodiments and all changes and modifications falling within the scope of the embodiments of the present application.

[0214] Finally, it is to be understood that the phraseology or terminology such as "first" and "second" etc. used herein is merely intended to differentiate one entity or operation from another entity or operation, without necessarily requiring or implying any actual such relationship or order between such entities or operations. Moreover, the terms "comprising", "including", or any other closure, are intended to cover the non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements does not include those elements alone but can include other elements not expressly listed or even include elements inherent in such process, method, article, or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0215] The above describes in detail the nutritional intervention method and system for sarcopenia patients provided by the present application, specific examples are applied herein to explain the principles and implementation modes of the present application, and the above example is only used to help understand the method and core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed, and the above description should not be understood as a limitation of the present application.

Claims

1. A nutritional intervention method for patients with sarcopenia, characterized in that, The method includes: Collect multimodal data from patients, including basic patient information, body composition data, clinical phenotype data, nutritional assessment data, biochemical index data, muscle function data, and exercise preference data; Based on the multimodal data, the patient's nutritional status, risk factors, and intervention direction are determined. The intervention direction is an intervention goal that integrates the nutritional status and risk factors. The intervention direction includes at least energy intake adjustment, nutritional quality optimization, and meal timing adjustment. Based on the aforementioned intervention direction, an individualized nutritional plan is generated according to the quantity-quality-timing balance mechanism and nutritional intervention mechanism. The nutritional intervention mechanism includes an intake mechanism, a nutritional quality mechanism, and a meal timing mechanism. The intake mechanism is used to determine the total energy intake and nutritional formula. The nutritional formula includes the types and amounts of ingredients and cooking methods. The nutritional quality mechanism is used to determine the nutritional preparations that need to be supplemented. The meal timing mechanism is used to determine the daily meal time distribution and the timing of coordination with the exercise plan. Among these, determining the patient's nutritional status based on the multimodal data includes: Based on the muscle mass and fat distribution in the aforementioned body composition data, basal metabolic requirement parameters are established as a benchmark for energy calculation. Calculate the actual total energy intake based on the 24-hour dietary review in the nutritional assessment data; Based on the patient's age, physical activity expenditure, basal metabolic rate (BMR) parameters, and the thermic effect of food in the patient's basic information, the patient's total energy expenditure is determined, and combined with the body composition data and the preset weight control target, the daily dietary energy target value is determined; wherein, the physical activity expenditure is calculated based on the metabolic equivalent value corresponding to the activity duration and intensity reflected by the exercise preference data, and the thermic effect of food is calculated based on the actual total energy intake according to a preset ratio; The actual total energy intake is compared with the daily dietary energy target value to obtain the total energy intake deviation. The 24-hour dietary review was used to obtain the intake weight of macronutrients and convert the intake weight of macronutrients into energy contribution values. The energy ratio of each macronutrient was calculated and compared with the preset target energy ratio to obtain the deviation of the macronutrient energy ratio. The macronutrients include carbohydrates, fats and proteins. Based on the protein, inflammatory, and metabolic indicators in the biochemical data, assess the status of latent malnutrition and protein assimilation capacity. Based on the basal metabolic demand parameters, the macronutrient energy ratio deviation, the latent malnutrition, and the protein assimilation capacity, the nutritional status is comprehensively determined, and a nutritional status classification conclusion characterizing specific nutritional problems is output. Based on the aforementioned intervention direction, individualized nutritional plans are generated according to the quantity-quality-timing balance mechanism and nutritional intervention mechanism, including: Based on the principle of clock nutrition, determine the distribution of energy intake throughout the day and the timing of normal meals to synchronize nutrient intake with the body's circadian rhythm. Determine the post-exercise nutrition window based on the exercise training time in the exercise plan; Based on the intervention direction, the intake mechanism is invoked to determine the total energy intake and nutritional formula, and the nutritional quality mechanism is invoked to determine the nutritional supplements that need to be added. Based on the aforementioned eating timing mechanism, the daily energy intake distribution, the timing of normal meals, and the post-exercise nutrition window are integrated to generate a daily and weekly eating schedule and exercise coordination suggestions, forming an intervention plan. The nutritional plan is generated by combining the total energy intake, the nutritional formula, the nutritional preparation, and the intervention plan.

2. The nutritional intervention method for patients with sarcopenia according to claim 1, characterized in that, Based on the multimodal data, the patient's risk factors are identified, including: Based on the actual total energy intake and the daily dietary energy target, the difference between energy intake and energy requirement is calculated to identify the risk of energy imbalance caused by excessive or insufficient energy intake. Based on the comorbidities and medication use in the clinical phenotypic data, identify disease-related nutritional contraindications and specific needs; Based on the aforementioned deviations in the macronutrient energy ratio, the risk of nutritional imbalance caused by dietary structure can be identified. By combining the eating times reflected in the nutritional assessment data, we can identify whether there is a risk of circadian rhythm disorder caused by eating in the evening, skipping meals, or disrupting the eating rhythm. The actual protein intake in the nutritional assessment data is calculated and compared with the recommended protein intake determined based on age and body composition data to identify the risk of insufficient protein intake. Based on the risks of energy imbalance, nutritional imbalance, nutritional contraindications and specific needs, circadian rhythm disorder, and insufficient protein intake, the risk factors are comprehensively determined, and specific risk labels and nutritional risk levels are output.

3. The nutritional intervention method for patients with sarcopenia according to claim 1 or 2, characterized in that, The method further includes: Based on the muscle function data, including grip strength, gait speed, sit-up ability score, and balance ability score, the intensity level of exercise intervention is matched. Based on the intensity level of the exercise intervention, select seated or standing resistance training exercises from the preset exercise library and match the resistance level of the resistance band or dumbbell. Based on the exercise intervention intensity level, the resistance training movements, and the resistance level, an exercise plan is generated that includes training methods, training frequency, training intensity, training time, and precautions.

4. A nutritional intervention system for patients with sarcopenia, characterized in that, For implementing the nutritional intervention method for patients with sarcopenia as described in any one of claims 1-3, the system comprises: The data acquisition module is used to collect multimodal data of patients, including user basic information, body composition data, clinical phenotype data, nutritional assessment data, biochemical index data, muscle function data, and exercise preference data. The data processing module is used to determine the patient's nutritional status, risk factors, and intervention direction based on the multimodal data. The intervention direction is an intervention goal that integrates the nutritional status and the risk factors. The intervention direction includes at least energy intake adjustment, nutritional quality optimization, and meal timing adjustment. The plan generation module is used to generate an individualized nutrition plan based on the intervention direction and according to the quantity-quality-timing balance mechanism and the nutrition intervention mechanism. The nutrition intervention mechanism includes an intake mechanism, a nutrition quality mechanism, and a meal timing mechanism. The intake mechanism is used to determine the total energy intake and the nutrition formula. The nutrition formula includes the types and amounts of ingredients and the cooking methods. The nutrition quality mechanism is used to determine the nutritional preparations that need to be supplemented. The meal timing mechanism is used to determine the daily meal time distribution and the timing of coordination with the exercise plan. Among these, determining the patient's nutritional status based on the multimodal data includes: Based on the muscle mass and fat distribution in the aforementioned body composition data, basal metabolic requirement parameters are established as a benchmark for energy calculation. Calculate the actual total energy intake based on the 24-hour dietary review in the nutritional assessment data; Based on the patient's age, physical activity expenditure, basal metabolic rate (BMR) parameters, and the thermic effect of food in the patient's basic information, the patient's total energy expenditure is determined, and combined with the body composition data and the preset weight control target, the daily dietary energy target value is determined; wherein, the physical activity expenditure is calculated based on the metabolic equivalent value corresponding to the activity duration and intensity reflected by the exercise preference data, and the thermic effect of food is calculated based on the actual total energy intake according to a preset ratio; The actual total energy intake is compared with the daily dietary energy target value to obtain the total energy intake deviation. The 24-hour dietary review was used to obtain the intake weight of macronutrients and convert the intake weight of macronutrients into energy contribution values. The energy ratio of each macronutrient was calculated and compared with the preset target energy ratio to obtain the deviation of the macronutrient energy ratio. The macronutrients include carbohydrates, fats and proteins. Based on the protein, inflammatory, and metabolic indicators in the biochemical data, assess the status of latent malnutrition and protein assimilation capacity. Based on the basal metabolic demand parameters, the macronutrient energy ratio deviation, the latent malnutrition, and the protein assimilation capacity, the nutritional status is comprehensively determined, and a nutritional status classification conclusion characterizing specific nutritional problems is output. Based on the aforementioned intervention direction, individualized nutritional plans are generated according to the quantity-quality-timing balance mechanism and nutritional intervention mechanism, including: Based on the principle of clock nutrition, determine the distribution of energy intake throughout the day and the timing of normal meals to synchronize nutrient intake with the body's circadian rhythm. Determine the post-exercise nutrition window based on the exercise training time in the exercise plan; Based on the intervention direction, the intake mechanism is invoked to determine the total energy intake and nutritional formula, and the nutritional quality mechanism is invoked to determine the nutritional supplements that need to be added. Based on the aforementioned eating timing mechanism, the daily energy intake distribution, the timing of normal meals, and the post-exercise nutrition window are integrated to generate a daily and weekly eating schedule and exercise coordination suggestions, forming an intervention plan. The nutritional plan is generated by combining the total energy intake, the nutritional formula, the nutritional preparation, and the intervention plan.

5. The nutritional intervention system for sarcopenia patients according to claim 4, characterized in that, The data acquisition module includes: The system interface unit is used to interact with the hospital information system via a hypertext transfer security protocol to obtain the clinical phenotypic data and the biochemical indicator data; the clinical phenotypic data includes disease status, comorbidities, and drug usage; the biochemical indicator data includes protein indicators, inflammatory indicators, and metabolic indicators. At least one external device interface unit is provided for connecting to and acquiring data from at least one of the following devices: A body composition analyzer is used to collect the body composition data, which includes weight, body mass index, muscle mass, and fat distribution. A grip strength meter is used to measure grip strength. The balance test module is used to collect balance ability scores; A walkway grating sensor is used to collect walking speed data. A height-adjustable pressure sensor seat is used to collect scores on the ability to sit up and stand. A circumference measuring tape is used to measure limb circumference. Among them, the grip strength, the balance ability score, the walking speed, and the sit-up ability score are muscle function data.

6. The nutritional intervention system for sarcopenia patients according to claim 5, characterized in that, The data acquisition module also includes: The dietary assessment module is used to record the nutritional assessment data, which includes dietary preferences and a 24-hour dietary review. The exercise assessment module is used to record the exercise preference data, which includes personal exercise habits, activity level, exercise type, and activity frequency.

7. The nutritional intervention system for sarcopenia patients according to claim 4, characterized in that, The scheme generation module includes: The nutrition plan module is used to execute the intake mechanism, nutrition quality mechanism and eating timing mechanism, and output the nutrition plan. The exercise plan module is used to call the exercise plan generated by the preset rule library based on the exercise intervention level matched by the data processing module.

8. The nutritional intervention system for sarcopenia patients according to any one of claims 4-7, characterized in that, The system also includes: The report management module is used to generate, store, query, and print sarcopenia assessment reports, nutrition plans, and exercise plans; The user management module is used to manage patient records and supports adding, editing, deleting, and querying patients.

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