136 results about "Nutritional status" patented technology

The invention discloses a patient nursing strategy optimization system for nursing in the department of hepatobiliary and pancreatic, and relates to the technical field of nursing strategy optimization. The nursing strategy optimization platform is in communication connection with a patient information management module, a knowledge base module, a nursing evaluation module, a nursing strategy plan making module, a nursing implementation module, a communication and cooperation module and a nursing effect evaluation module. According to the patient nursing strategy optimization system for nursing in the department of hepatobiliary and pancreatic, data in multiple aspects of physiology, psychology, society and the like of a patient are comprehensively collected and analyzed through the integrated nursing evaluation module, and key indexes such as vital signs, pain degree, nutritional status, sleep quality and the like are monitored and evaluated in real time; in addition, a personalized nursing plan provided by the system is combined with specific requirements and illness state changes of the patient, so that the nursing service better fits the actual condition of the patient.

The invention discloses a feed proportion abnormity identification method and system, and particularly relates to the field of feed proportion abnormity identification, and the method comprises the steps: extracting the disturbance variables of vibration amplitude, feeding speed and voiceprint waveform in multi-source disturbance data, constructing the disturbance time sequence expression of a frequency, form and amplitude triple feature structure, and carrying out the recognition of the vibration amplitude, the feeding speed and the voiceprint waveform. Extracting a disturbance characteristic track with center characterization capability in a cluster through atlas clustering, and writing the disturbance characteristic track into a track benchmark expression library; constructing an aligned trajectory expression set by analyzing the frequency domain structure and the time slice expression of each channel signal in the current batch of disturbance data and combining the binding relationship between the batch number and the formula number; by constructing an offset matching and track consistency judgment mechanism based on multi-source disturbance track expression, structured recognition and path logic verification of a formula drift phenomenon are realized, and the problem that the actual feed nutrition state is misjudged due to the fact that real proportion offset caused by residual feed cannot be recognized is solved.

The invention discloses a severe pancreatitis early-stage enteral nutrition intolerance assessment method and system based on multi-dimensional indexes, and relates to the technical field of enteral nutrition tolerance. According to the method, enteral microorganism environment parameters of a patient are monitored in real time through non-invasive detection equipment, and the enteral nutrition intolerance of the patient is evaluated by combining a multi-dimensional index parameter set; the early enteral nutrition tolerance condition of the severe pancreatitis patient can be accurately evaluated. In the steps S1 to S3, through data preprocessing and data fusion, an initial nutrition tolerance risk value and a correction value are calculated through a tolerance evaluation model, the nutrition tolerance condition of a patient can be accurately evaluated, a scientific basis is provided for medical staff to formulate a personalized nutrition support scheme, and finally a comprehensive tolerance evaluation value is obtained. The medical staff can perform primary evaluation on the enteral nutrition of the patient according to the value, and grade division is performed based on the evaluation result. And the overall nutritional status and rehabilitation speed of the patient are improved by adjusting a nutrition support scheme in a personalized manner.

The invention provides a causal algorithm-based plant nutrition management model construction method and system, and the method comprises the steps: collecting the historical planting data of a target plant, and determining and screening a plurality of key factors in plant nutrition management; constructing a causal relationship set among the plurality of key factors based on a causal relationship model; and training and correcting the causal relationship model by using the historical planting data to predict the nutritional status of the target plant under different conditions. According to the method, the model is constructed based on the causal relationship model, so that the optimal proportion and time scheme of plant nutrition is calculated, the fertilization guidance suggestions are generated, a user is helped to avoid the phenomenon that the model generation content does not conform to reality in the planting research process, the model illusion is reduced, and meanwhile the generalization ability of the model in a planting scene is improved. The method can be applied to planting industry model training, improves the accuracy of fertilization guidance, and can be used for agricultural machinery design guidance.

The invention relates to the technical field of animal feeds, and provides an animal feed and a preparation method and optimization method thereof, and the optimization method of the animal feed comprises the following steps: determining candidate microorganisms and nutrition raw material formulas, establishing an optimization model, and solving to obtain an optimal microorganism formula and an optimal nutrition raw material formula; the animal feed comprises microorganisms such as lactic acid bacteria, saccharomycetes and bacillus and nutritional raw materials such as corn and soybean meal. By adopting a multilayer microcapsule technology, the survival rate of microorganisms in an acid environment is improved, the digestion and absorption efficiency is improved, and the nutritional condition and the milk production performance are improved; the invention further provides a corresponding preparation method, and the feed has the remarkable slow release characteristic and the effect of improving the feed utilization rate.

According to the clinical nutrition intelligent management system and method disclosed by the invention, nutrition status evaluation is carried out by applying a nutrition comprehensive evaluation formula, the standardization and objectivity of evaluation are greatly improved, the formula quantifies multiple key factors and gives weights, different evaluators carry out calculation based on the same information and formula, and the consistency of evaluation results is ensured; besides, the comprehensive nutrition evaluation formula comprehensively considers the body mass index, the disease-related nutrition influence coefficient, the nutrition-related index comprehensive score, the diet health degree score and other aspects adjusted by age and gender, accurately reflects the actual nutrition condition of the patient, and solves the problem of insufficient accuracy of traditional evaluation. And the nutrition plan generation module can customize nutrition plans for patients according to the nutrition comprehensive evaluation indexes in combination with a preset rule base, so that individual requirements of different patients are fully met, and a scientific, accurate and personalized solution is provided for clinical nutrition management.

The invention provides an AI technology-based hemodialysis patient malnutrition prediction method and system. The system comprises a data collection module, a data preprocessing module, a data standardization module, a dimension reduction module and a nutrition state prediction module. The method comprises the following steps: S1, collecting related attributes of hemodialysis patients to obtain a hemodialysis patient data set; s2, preprocessing the hemodialysis patient data set; s3, performing standardization processing on the hemodialysis patient data set; s4, a feature selection and model construction method; s5, model training and generation; according to the method, the AI technology is combined with the multi-dimensional data to comprehensively analyze the patient, the nutrition state of the patient can be more comprehensively predicted, the evaluation result is comprehensive, and the problems that in the prior art, the nutrition state of the hemodialysis patient is predicted based on a few indexes, the indexes are too single, and the prediction result is not comprehensive are solved.

The invention provides a planting nutrition diagnosis method based on a large model, and the method comprises the steps: extracting the nutrient metabolism and morphological expression characteristics of a plant based on the growth and development law and environment variables of the plant, and constructing a plant nutrition metabolism model; according to the plant nutrition metabolism model, model parameters are adjusted based on multi-modal data of plant growth, and a multi-dimensional correlation model is constructed; obtaining a morphological picture and an environmental condition in the growth process of a target plant, and identifying the nutrition state of the target plant according to the multi-dimensional correlation model; and generating personalized precise fertilization suggestions according to the nutrition state of the target plant. According to the method, personalized precise fertilization suggestions are generated according to the nutrition state of the target plant, and the suggestions comprise functional fertilizer use suggestions, fertilization mode suggestions, fertilization dosage suggestions and fertilization time suggestions. Scientific guidance can be provided for agricultural production, a user is helped to achieve precise fertilization, crop growth is optimized, and the efficiency of agricultural production is improved.

The invention relates to a precise nutrition decision-making system and method based on offline reinforcement learning, and belongs to the field of medical informatization. According to the method, patient medical record data are collected and preprocessed, and patient nutrition state indexes, a nutrition intervention scheme and nutrition state benefits after nutrition intervention are defined as a state space, an action space and a reward function respectively. And then, constructing a model by using an offline reinforcement learning algorithm, so that the intelligent agent learns to select an optimal nutrition intervention strategy under different nutrition conditions. And finally, evaluating the performance of the model in a test data set, and comparing the influence of different intervention schemes on the nutrition state of the patient. According to the invention, the nutrition intervention effect of the inpatient can be effectively improved, the reasonable distribution of medical resources is promoted, and the application value is high.

The invention relates to the technical field of medical health monitoring and evaluation, and discloses a method and system for evaluating and monitoring the nutrition risk of a cancer palliative treatment patient, and the method comprises the steps: obtaining a daily diet image of the cancer patient through an image device, recognizing the type of food in the daily diet image, recognizing the weight of food in the daily diet image, and calculating the nutrition risk of the cancer palliative treatment patient; analyzing diner actions in the daily diet image; the daily diet condition of the cancer patient is analyzed according to the food category, the food weight, the diner action and the target food, the nutrition change item of the initial nutrition condition is determined according to the daily diet condition, and the nutrition risk condition of the cancer patient is identified according to the nutrition change item; determining target monitoring equipment of the cancer patient from non-image equipment; and constructing a nutrition risk sequence of the nutrition risk level, analyzing the nutrition risk trend of the cancer patient by using the nutrition risk sequence, and determining a nutrition risk monitoring result of the cancer patient. The convenience of nutrition risk assessment of the patient can be improved.

The invention provides a CKD nutrition management visual monitoring method and system based on big data, and relates to the technical field of data processing, and the method comprises the steps: carrying out the data preprocessing according to real-time health data, and obtaining a standardized health data set; according to the standardized health data set, evaluating nutritional requirements of the patient, and combining disease progression, individual differences and diet preferences of the patient to generate a personalized nutrition management scheme, the personalized nutrition management scheme including recommended diet, a nutrition supplement scheme and an intake behavior adjustment scheme; according to the personalized nutrition management scheme, a visual display interface is generated, and the visual display interface displays the nutrition state, diet suggestions, potential health risks and predicted effects of the patient; adjusting a personalized nutrition management scheme in real time according to feedback data and health state changes provided by the patient in the use process, and presenting an updated scheme through a visual display interface; the autonomy and accuracy of nutrition management are improved.

The invention provides a soybean peptide with an effect of preventing and / or treating chronic nephritis as well as a preparation method and application of the soybean peptide, and belongs to the technical field of bioactive peptides. According to the preparation method of the soybean peptide mixture provided by the invention, a three-step enzymolysis mode is adopted, the molecular weight of soybean peptide is controlled to be 1000 Daltons or below, micromolecular oligopeptide is used as a main component, and the prepared soybean peptide mixture is low in sodium, phosphorus and potassium content and capable of improving the nutritional status and muscle loss condition of nephritis patients. The prepared soybean peptide mixture is further separated and purified, the purified soybean peptide mixture, the single-chain polypeptide S1 and the single-chain polypeptide S2 are obtained, the content of uric acid and creatinine can be effectively reduced, inflammation can be inhibited, and the soybean peptide is expected to be developed into a novel polypeptide medicine for preventing and / or treating chronic kidney diseases.

The invention relates to the technical field of medical monitoring, and discloses an intestinal nutrition monitoring system and method based on a critically ill patient, and the method comprises the steps: collecting a dynamic image of a gastric antrum region of the critically ill patient, and recognizing the contraction frequency and amplitude of the gastric antrum of the critically ill patient to calculate a gastric emptying index; calculating the intestinal transport efficacy of the critically ill patient by using the intestinal peristalsis data and the gastric emptying index; constructing an intestinal nutrition transmission scheme of the critically ill patient, and collecting transmission conversion data about the critically ill patient under the nutrition transmission scheme; the intestinal nutrition tolerance of the critically ill patient is analyzed, the metabolic data and the immune state of the critically ill patient after the nutrition transmission scheme are collected, and a target nutrition transmission scheme is constructed; and monitoring the intestinal nutrition status of the critically ill patient under the target nutrition transmission scheme in real time to obtain an intestinal nutrition monitoring report. According to the invention, the comprehensiveness of intestinal nutrition monitoring of critically ill patients can be improved, so that an optimal nutrition collocation scheme is constructed.

The invention discloses a child nutrition recommendation method based on big data, and relates to the technical field of intelligent recommendation, and the method comprises the steps: collecting child basic information and vitamin D level detection data, and carrying out the preprocessing; using correlation analysis and principal component analysis to identify main features affecting the vitamin D demand, and analyzing the current vitamin D nutrition status of the child through a deep learning model; a deep neural network is utilized, historical child basic information and vitamin D level detection data are combined, a vitamin D nutritional demand prediction model of children is constructed, and the future nutritional demand of children for vitamin D is predicted; personalized vitamin D nutrition suggestions are provided for children; through correlation analysis, principal component analysis and construction of the vitamin D demand prediction model, dynamic adjustment can be performed according to specific conditions of different children, scientificity and practicability of suggestions are ensured, the vitamin D nutritional status of the children can be improved, and the health level of the children is improved.

The invention provides a hemodialysis patient risk assessment system based on an objective assessment method, and relates to the technical field of medical data, and the system comprises a performance assessment unit which is used for collecting the clinical basic information of a hemodialysis patient, calculating a nutrition state index through the objective assessment method, and determining the performance of the hemodialysis patient; evaluating the evaluation efficiency of the objective evaluation method on the nutrition state indexes by using the subject working characteristic curve; the model construction unit is used for constructing a risk assessment model of the hemodialysis patient by utilizing a matter-element extension variable weight theory and a data fusion technology based on the efficiency assessment result; and the risk assessment unit is used for performing individual risk assessment on the hemodialysis patient by using the risk assessment model of the hemodialysis patient to obtain a risk assessment result. According to the method, efficient medical resource allocation, early recognition of high-risk patients, reduction of complications, improvement of patient prognosis and fusion of multiple technologies and theories are facilitated, and the innovativeness and flexibility of an evaluation system are improved.

The invention belongs to the technical field of medical data information processing, and discloses a human nutrient element deficiency risk intelligent prediction method based on conventional test data, comprising the following steps: acquiring basic personal information and conventional test data of a subject; performing data cleaning on the acquired data information; the individual nutrition status is comprehensively evaluated, and risk labels of nutrient element deficiency are marked in a standardized mode; training a human nutrient element deficiency risk prediction model; determining an optimal threshold value of the human nutrient element deficiency risk prediction model; and evaluating the feasibility of human nutrient element deficiency risk prediction based on conventional test data. By adopting the human nutrient element deficiency risk intelligent prediction method based on the conventional inspection data, the capability of identifying the human nutrient element deficiency risk is comprehensively improved, the detection cost is reduced, the detection time is shortened, dynamic monitoring and immediate feedback of the nutrition status are realized, and the human nutrient element deficiency risk intelligent prediction method is suitable for popularization and application. The method has the characteristics of comprehensiveness, high efficiency, accuracy and real-time dynamic monitoring.

The invention relates to the technical field of specific total nutrient formula foods, and discloses a specific total nutrient formula food for tumor patients and a preparation method thereof, 1000 g of the specific total nutrient formula food comprises 187-280.5 g of proteins, 265-397 g of fat, 200-300.28 g of carbohydrates, 41-62 g of dietary fibers, 1.42-2.15 g of composite vitamins, 15.9-24.0 g of composite minerals, and 57.4-85.2 g of immune nutrition nutritional factors. The health-care food has the characteristics of high fat, high energy, low carbohydrate and comprehensive nutrition, accords with the related recommendation of the nutrition treatment guide of malignant tumors in modern medicine, can meet the special nutritional requirements of tumor patients, and improves the nutritional status of the tumor patients.

The invention discloses a malignant tumor patient personalized nutrition assessment dynamic analysis method based on blood data, and relates to the technical field of personalized nutrition assessment, and the method comprises the steps: taking a multilayer perceptron neural network as a basic model to train a data set S2 of blood routine and biochemical data, and obtaining model1; adding the historical blood routine and biochemical data of the person to be tested into the data set S2 to form a data set S3, and re-assigning the weight to the data set S3; s3, the parameters of the second layer and the third layer of the model1 are activated, training is continued, the training epoch is 200, and model2 is obtained. The model structure and the parameters of the model1 are reloaded, and the parameters of the first layer of the model1 are fixed, and the parameters of the second layer and the third layer of the model1 are activated to continue training. According to the method, customized nutrition state evaluation is provided according to unique physiological changes of each person and data in the treatment process, compared with a general model, the method can better fit individual differences, and meanwhile, the model has the ability of re-training by continuously incorporating new data, and the prediction accuracy and adaptability of the model are continuously improved along with accumulation of historical data of patients.

The invention relates to a high-steam-quantity self-heating body and a steam eyeshade, the self-heating body comprises a nutrition layer and a heating layer, the nutrition layer is distributed on the inner side of the heating layer, and a temperature control breathable film I is arranged between the nutrition layer and the heating layer. The steam eyeshade has the advantages that the structure is simple, design is reasonable, the steam amount of the steam eyeshade can be obviously increased through the double-bag design, the physical thermal therapy effect is achieved, tear circulation and tear secretion are promoted, the nutritional condition of eye tissue is improved, and a certain effect is achieved for treating xerophthalmia.

The present application relates to a kind of nutrition state prognosis prediction model construction method and system based on weight dynamics, belong to medical information field.This method first establishes the population dataset containing individual weight information and nutrition state data, and carries out data preprocessing, including calculating weight loss percentage and defining outcome label.Subsequently, the dataset is divided into training set and test set, and the key features related to nutrition state prognosis are extracted from the training set by feature screening.Based on the screened features and training set, multiple machine learning classifiers are constructed, and the best model is selected according to the performance indicators of the classifier.Finally, the best model is used to predict the test set, and the performance of the model is evaluated.The present application uses weight dynamic information, without the aid of other information, can realize the high-performance prediction of common adverse nutrition state prognosis, has high practical value.

Methods of improving nutrition in subjects, including individuals who have undergone gastrointestinal surgery, by avexitide therapy are disclosed. Avexitide may be administered subcutaneously or intravenously as a part of a liquid pharmaceutical formulation. Avexitide therapy may improve weight and / or nutritional intake / status in subjects.

The invention discloses a method and a device for judging a blood folic acid deficiency boundary value by liquid chromatography-mass spectrometry in the technical field of medical detection. The method comprises the following steps: step 1, pre-treating a sample; step 2, UPLC-MS / MS detection is carried out; step 3, data calculation and verification; and 4, performing boundary value conversion and judgment. According to the method, the regression model is constructed by fitting experimental data, the boundary value of folic acid deficiency and edge deficiency detected by the liquid chromatography-mass spectrometry is defined, serum pretreatment and liquid chromatography are integrated through the developed micro-fluidic chip, the speed and accuracy of serum folic acid detection by the liquid chromatography-mass spectrometry are further improved, and the method is suitable for large-scale popularization and application. The clinical detection requirements are met, and the efficiency and accuracy of judging the folic acid nutritional status are improved.

The invention discloses a full-automatic cooking control method and a cooking machine. The full-automatic cooking control method comprises the steps that 1, a menu text is analyzed, actions and food material information are extracted, and a standardized food material list and an action sequence are generated; 2, calculating a temperature curve and a time sequence in combination with nutrition attenuation characteristics of the food materials; 3, controlling the feeding opportunity and the stir-frying rotating speed according to the temperature curve and the time sequence; step 4, calculating a nutrition score, and optimizing the seasoning amount by using the nutrition score and the seasoning cost; 5, quantifying the nutritional status of the dishes in combination with the seasoning amount, and outputting an evaluation result according to the user satisfaction; step 6, adjusting cooking parameters according to an evaluation result, and feeding back to the step 1 to realize taste individuation; according to the intelligent kitchen intelligent cooking system, the subject technologies of natural language processing, computer vision, thermodynamics, biology and reinforcement learning are fused, automation and personalized optimization of the whole cooking process are achieved, the consistency of cooking quality is remarkably improved, and an efficient and healthy cooking solution is provided for a household intelligent kitchen.

The present invention provides a hemodialysis patient risk assessment system based on an objective assessment method, which relates to the field of medical data technology and includes: an effectiveness assessment unit for collecting basic clinical information of hemodialysis patients, calculating nutritional status indicators through objective assessment methods, and evaluating the effectiveness of objective assessment methods on nutritional status indicators using receiver operating characteristic curves; a model construction unit for constructing a risk assessment model for hemodialysis patients based on the effectiveness assessment results using matter-element extension variable weight theory and data fusion technology; and a risk assessment unit for performing individualized risk assessment on hemodialysis patients using the risk assessment model for hemodialysis patients to obtain risk assessment results. The present invention helps to efficiently allocate medical resources, identify high-risk patients early, reduce the occurrence of complications, and improve patient prognosis. It integrates multiple technologies and theories to enhance the innovation and flexibility of the assessment system.

1. The name of this design product: Graphical user interface for a clinical nutrition management module for inpatients of an electronic device. 2. Purpose of this design product: Used for integrated nutrition management of hospitalized patients in doctor's workstations, for an electronic device. 3. The key design point of this design product lies in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: main view. 5. Purpose of the graphical user interface: Used for integrated nutrition management of hospitalized patients in the doctor's workstation: used for nutrition screening, evaluation, nutrition prescription issuance, consultation and other operations for hospitalized patients, as well as preview of the patient's overall nutritional status and visual monitoring of indicators. 6. Human-computer interaction method of the graphical user interface: 1) Click the "Nutrition Order" icon button in the upper right corner of the main view to enter the interface change state diagram 1; 2) Click the "Yes" icon button in the interface change state diagram 1 to enter the interface change state diagram 2; 3) Click the "Not Required" icon button in the main interface change state diagram 2 and enter the relevant options to enter the interface change state diagram 3; 4) Enter a number in the "Gap Percentage" in the interface change state diagram 3 and press the Enter key to enter the interface change state diagram 4; 5) In the interface change state diagram 4, click the "Whole Hospital" button, check the "Serial Number" on the left, click the "Calculate" icon button on the right to enter the interface change state diagram 5; 6) Click the "EN Order" icon button in the interface change state diagram 5 to enter the interface change state diagram 6, enter a number in the "Gap Percentage" in the interface change state diagram 6 and press the Enter key, check the medicine on the left, and click Calculate on the right to refresh the interface to display the calculated value. 7) Click the "Value" button in the NRS2002 score "input box" in the interface change state diagram 6 to enter the interface change state diagram 7.

A system for tracking diet and nutrition includes an oral module configured to be affixed within a mouth of a user and including a set of salivary sensors responsive to a level of at least one nutrient. The system also includes a set of eating event sensors responsive to an eating event. The set of eating event sensors can be included in the oral module, or can be included in a body module configured to be affixed adjacent to a body part of the user.

The present application relates to the technical field of animal health monitoring, and relates to a wild animal non-invasive genome monitoring and population health evaluation system. A time indication marker is generated based on the ratio of a predetermined indicator bacteria genus, and microenvironment data is input into a pre-trained microbial succession model to intelligently infer the actual exposure time of the sample in the wild. Then, the initial intestinal flora map of the sample at the instant of discharge is reconstructed. The high-fidelity flora map after reconstruction is further deeply coupled with health evaluation to realize scientific diagnosis and early warning of the physiological state of wild animal individuals. The accuracy of health evaluation, nutritional status analysis and pathogen detection is greatly improved, and major misjudgments such as misjudging environmental bacteria as pathogenic bacteria or misdiagnosing flora natural decay as ecological imbalance are avoided. A stable and reliable technical tool is provided for wild animal protection management.

This invention relates to a precision nutrition decision-making system and method based on offline reinforcement learning, belonging to the field of medical informatics. The method collects and preprocesses patient medical record data, defining patient nutritional status indicators, nutritional intervention plans, and nutritional status benefits after intervention as the state space, action space, and reward function, respectively. Subsequently, an offline reinforcement learning algorithm is used to build a model, enabling the agent to learn to select the optimal nutritional intervention strategy under different nutritional conditions. Finally, the model performance is evaluated on a test dataset, and the impact of different intervention plans on patient nutritional status is compared. This invention can effectively improve the nutritional intervention effect for hospitalized patients and promote the rational allocation of medical resources, possessing high application value.

This invention belongs to the field of spectral detection technology, specifically relating to a method for detecting the nutritional status of honeysuckle plants based on near-infrared spectroscopy. It aims to solve the problems of strong specular reflection interference, moisture background shielding of nutrient signals, and insufficient applicability throughout the entire growth period in in-situ detection of live honeysuckle. The method suppresses specular reflection on the leaf surface through orthogonal extinction and collects deep diffuse reflectance spectra; it obtains standardized reflectance using real-time background difference and dark current compensation; it achieves moisture background decoupling through orthogonal signal correction and external parameter orthogonalization; it extracts feature wavelength vectors through multi-scale continuous wavelet transform; it inputs a deep residual network model with a self-attention mechanism and combines it with a phenological adaptive compensation algorithm to invert nutrient quality fractions; finally, it compares the results with a nutrient critical value database for the entire growth period to calculate the surplus / deficit index and complete nutrient diagnosis. This significantly improves the spectral signal-to-noise ratio and detection accuracy, achieving rapid and stable detection of the nutritional status of live honeysuckle throughout the entire growth period.

The invention provides a specific full-nutrient formula food applied to diet-restricted diabetes mellitus groups, and belongs to the technical field of formula foods for special medical purposes. According to the product, marine active substances and medicinal and edible traditional Chinese medicine extracts are innovatively compounded, and a multi-probiotic microencapsulation technology is combined, so that a specific full-nutrition formula with the functions of regulating blood sugar, improving insulin resistance and protecting target organ functions is formed. The formula comprises marine active ingredients such as marine collagen tripeptide, a sea cucumber saponin extract and fucoidan as well as medicinal and edible traditional Chinese medicine extracts such as mulberry leaves, rhizoma polygonati and radix puerariae, and oligopeptide, amino acid, multivitamins and mineral substances in a specific proportion are matched. Probiotics are protected by adopting a three-layer microencapsulation technology to pass through a gastric acid environment, active ingredients are reserved by utilizing a low-temperature enzymolysis and molecular directed extraction technology, and the nutritional status and blood sugar control of diabetic patients can be remarkably improved through clinical verification. The product conforms to the GB 29922-2013 special medical purpose formula food standard, can be used as a single nutrition source for diabetics, and meets the special nutrition requirements of the diabetics.