Recipe recommendation system and recipe recommendation method

Abstract

The invention discloses a recipe recommendation system and a recipe recommendation method. The system comprises a feature acquisition module, a processing analysis module and an interactive operation module, the feature acquisition module is used for acquiring attribute feature information of a user and sending the attribute feature information to the processing analysis module; the attribute characteristic information comprises biological characteristic information, food material limitation information and nutrient element information; the interactive operation module is used for receiving and responding to an input operation, acquiring physique index information of a user and sending the physique index information to the processing and analyzing module; and the processing analysis module is used for generating food material screening conditions according to the attribute feature information, and searching target food materials and target recipes meeting the food material screening conditions from a preset food material library and a preset recipe library based on the physique index information. According to the system, the nutrition theory and the food limitation information are combined, and the corresponding food materials and recipes are more comprehensively searched from the preset database, so that the target food materials and the target recipes meeting the food material screening conditions are accurately determined, and the recipes recommendation accuracy is improved.

Description

Technical Field

[0001] The present invention generally relates to the field of intelligent recommendation technology, and in particular to a recipe recommendation system and a recipe recommendation method. Background Art

[0002] With the rapid development of medical and health technology, users are paying more and more attention to recipes. Healthy diets can help improve users' physical health and play an important role in promoting recovery and preventing diseases. Among them, intelligent diagnosis and treatment equipment and resources such as Chinese and Western medicine experts can provide users with personalized dietary guidance, so as to develop a full-chain health management plan for users, such as from initial diagnosis to treatment plan to rehabilitation management. In order to improve users' dietary recommendation experience, it is particularly important to recommend recipes to users.

[0003] At present, the related technology only obtains the corresponding menu according to the ingredients that the user likes. However, the obtained menu is relatively single and one-sided and cannot meet the user's needs for healthy diet, resulting in low accuracy of recipe recommendations for users during the treatment stage. Summary of the invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, it is desired to provide a recipe recommendation system and a recipe recommendation method.

[0005] In a first aspect, an embodiment of the present application provides a recipe recommendation system, the system comprising:

[0006] The recipe recommendation system comprises:

[0007] A feature acquisition module, a processing and analysis module and an interactive operation module, wherein the processing and analysis module is electrically connected to the feature acquisition module and the interactive operation module respectively;

[0008] The feature acquisition module is used to: acquire the attribute feature information of the user and send it to the processing and analysis module; the attribute feature information includes: biometric information, food restriction information and nutritional element information;

[0009] The interactive operation module is used to: receive and respond to input operations, obtain the user's physical index information and send it to the processing and analysis module;

[0010] The processing and analysis module is used to generate food screening conditions according to the attribute feature information, and search for target food and target recipes that meet the food screening conditions from a preset food library and a preset recipe library based on the physical index information.

[0011] In one embodiment, the processing and analysis module is specifically used for:

[0012] Searching for a list of ingredients and a list of recipes that meet the ingredient screening condition from the preset ingredient library and the preset recipe library;

[0013] Calculating a calorie restriction parameter of the user according to the physical index information;

[0014] Based on the calorie restriction parameter, performing calorie analysis on the ingredient list to determine target ingredients and corresponding ingredient portions;

[0015] A target recipe is determined according to the target ingredients, the ingredient quantities and the recipe list.

[0016] In one of the embodiments, the feature acquisition module includes: a biometric feature detection unit, a food restriction information acquisition unit, and a nutrient element acquisition unit;

[0017] The biometric detection unit is used to: obtain the biometric information of the user;

[0018] The food restriction information acquisition unit is used to: acquire the food restriction information of the user;

[0019] The nutrient element acquisition unit is used to: acquire the nutrient element information of the user.

[0020] In one of the embodiments, the biometric detection unit includes: an electroencephalogram detection unit, an electrocardiogram detection unit, a quantum resonance detection unit, a blood pressure detection unit, a lung function detection unit, a body temperature detection unit, and a body surface color detection unit;

[0021] The EEG detection unit is used to: obtain EEG parameters of the user;

[0022] The electrocardiogram detection unit is used to: obtain electrocardiogram parameters of the user;

[0023] The quantum resonance detection unit is used to: obtain the quantum resonance detection parameters of the user;

[0024] The blood pressure detection unit is used to: obtain the blood pressure parameters of the user;

[0025] The pulmonary function detection unit is used to: obtain the pulmonary function parameters of the user;

[0026] The body temperature detection unit is used to: obtain the body temperature parameters of the user;

[0027] The body surface color detection unit is used to obtain the body surface color parameters of the user.

[0028] In one embodiment, the processing and analysis module is further used for:

[0029] When at least one of the electroencephalogram parameter, electrocardiogram parameter, quantum resonance detection parameter, blood pressure parameter, lung function parameter, body temperature parameter, and body surface color parameter is in a dangerous range, a danger warning instruction is generated and a danger warning is given;

[0030] When at least one of the electroencephalogram parameter, electrocardiogram parameter, quantum resonance detection parameter, blood pressure parameter, lung function parameter, body temperature parameter, and body surface color parameter is in an abnormal range, the health assessment parameter of the user is calculated.

[0031] In one of the embodiments, the interactive operation module includes: an input unit and a display unit, wherein the input unit and the display unit are electrically connected;

[0032] The input unit is used to: receive and respond to input operations to obtain the user's physical index information;

[0033] The display unit is used to display the physical indicator information.

[0034] In a second aspect, the present application provides a recipe recommendation method, the method comprising:

[0035] Acquire attribute characteristic information of the user; the attribute characteristic information includes: biometric information, food restriction information and nutritional element information;

[0036] Receiving and responding to an input operation, obtaining physical index information of the user;

[0037] Ingredient screening conditions are generated according to the attribute characteristic information, and target ingredients and target recipes that meet the ingredient screening conditions are searched from a preset ingredient library and a preset recipe library based on the physical index information.

[0038] The recipe recommendation system and recipe recommendation method provided in the embodiments of the present application include: a feature acquisition module, a processing and analysis module and an interactive operation module, the processing and analysis module is electrically connected to the feature acquisition module and the interactive operation module respectively, the feature extraction module is used to: obtain the user's attribute information and send it to the processing and analysis module, the attribute feature information includes: biometric information, food restriction information and nutritional element information; the recipe recommendation interactive operation module is used to: receive and respond to input operations, and obtain the physical index information of the recipe recommendation user; the recipe recommendation processing and analysis module is used to: generate ingredient screening conditions according to the recipe recommendation attribute feature information, and search for target ingredients and target recipes that meet the recipe recommendation ingredient screening conditions from the preset ingredient library and the preset recipe library based on the recipe recommendation physical index information. Compared with the existing technology, the system can obtain the user's biometric information, food restriction information and nutritional element information by setting up a feature acquisition module, and obtain the user's physical index information through an interactive operation module. It can comprehensively consider the biometric information, food restriction information, nutritional element information and physical index information through a processing and analysis module, and combine the nutritional theory of traditional Chinese medicine and food restriction information, so as to more comprehensively search for corresponding ingredients and recipes from the preset food library and recipe library, so as to accurately find the target ingredients and target recipes that meet the food screening conditions, thereby improving the accuracy of recipe recommendations for users in the treatment stage, and is suitable for dietary recommendation scenarios for users at different stages. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 A schematic diagram of the structure of a recipe recommendation system provided in an embodiment of the present application;

[0041] Figure 2 A schematic diagram of the structure of a recipe recommendation system provided in another embodiment of the present application;

[0042] Figure 3 A schematic diagram of a recipe recommendation method provided in an embodiment of the present application;

[0043] Description of reference numerals:

[0044] Feature acquisition module-10, biometric feature detection unit-11, food restriction information acquisition unit-12, nutrient element acquisition unit-13, processing and analysis module-20, interactive operation module-30, input unit-31, display unit-32, electroencephalogram detection unit-111, electrocardiogram detection unit-112, quantum resonance detection unit-113, blood pressure detection unit-114, lung function detection unit-115, body temperature detection unit-116, body surface color detection unit-117. DETAILED DESCRIPTION

[0045] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the invention are shown in the accompanying drawings.

[0046] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0047] As mentioned in the background technology, the related technology only obtains the corresponding menu according to the ingredients that the user likes. However, the obtained menu is relatively single and one-sided and cannot meet the user's needs for healthy diet, resulting in low accuracy of recipe recommendations for users during the treatment stage.

[0048] Based on the above-mentioned defects, the present application provides a recipe recommendation system and an ingredient recommendation method. Compared with the prior art, the system can obtain the user's biometric information, ingredient restriction information and nutritional element information by setting up a feature acquisition module, and obtain the user's physical index information through an interactive operation module. The system can comprehensively consider the biometric information, ingredient restriction information, nutritional element information and physical index information through a processing and analysis module, and combine the nutritional theory of traditional Chinese medicine and food restriction information, so as to facilitate a more comprehensive search for corresponding ingredients and recipes from the preset ingredient library and recipe library, so as to accurately find the target ingredients and target recipes that meet the ingredient screening conditions, thereby improving the accuracy of recipe recommendations for users in the treatment stage, and is suitable for dietary recommendation scenarios for users at different stages.

[0049] See also Figure 1 As shown, Figure 1 It is a structural diagram of a recipe recommendation system provided in an embodiment of the present application. The recipe recommendation system includes: a feature acquisition module 10, a processing and analysis module 20 and an interactive operation module 30. The processing and analysis module 20 is electrically connected to the feature acquisition module 10 and the interactive operation module 30 respectively.

[0050] The feature acquisition module 10 is used to obtain the user's attribute feature information and send it to the processing and analysis module; the interactive operation module 30 is used to receive and respond to input operations to obtain the user's physical index information; the processing and analysis module 20 is used to generate food screening conditions based on the attribute feature information, and search for target ingredients and target recipes that meet the food screening conditions from the preset food library and the preset recipe library based on the physical index information.

[0051] It should be noted that the attribute characteristic information of the above-mentioned user includes: biometric information, food restriction information and nutritional element information; biometric information refers to the information of various vital signs detected by the user, which can be obtained through various types of sensor detection, and food restriction information refers to some restrictions on food by the user, which can be affected by factors such as allergens and dietary preferences. For example, if the user cannot eat spicy food, the corresponding food restriction information may include garlic, peppers, green onions, etc. The above-mentioned nutritional element information refers to various chemical elements required to maintain normal physiological functions and health, which can include two categories: macronutrients and micronutrients. Macronutrients mainly include: carbohydrates, proteins, and lipids; micronutrients include: vitamins and minerals. Vitamins can include: fat-soluble vitamins and water-soluble vitamins. Fat-soluble vitamins include: vitamins A, D, E, and K; water-soluble vitamins include: B vitamins (such as B1, B2, B3, B6, B12, folic acid, etc.) and vitamin C.

[0052] The above-mentioned interactive operation module 30 is used to provide an input interface for the user, so that the user can perform input operations through the input interface to obtain the user's physical index information. The interactive operation module 30 may also include a display interface, which is used to display the user's physical index information, wherein the user's physical index information may include: height information, weight information.

[0053] In this embodiment, see Figure 2 As shown, the above-mentioned interactive operation module 30 includes an input unit 31 and a display unit 32, and the input unit 31 and the display unit 32 are electrically connected; the input unit 31 is used to: receive and respond to input operations, and obtain the user's physical indicator information; the display unit 32 is used to: display the physical indicator information.

[0054] The display unit 32 on the above-mentioned recipe recommendation system can display input options for the user, and the input options can be understood as an input interface, so that the user performs an input operation to enter the height information and the corresponding weight information in the input options, so that the interactive operation module obtains the user's height information and the corresponding weight information, which is convenient for subsequent calorie analysis, so as to provide the user with personalized recipes that better meet the user's own needs.

[0055] Optionally, the above input operation can be input by the user touching the display screen, or by pressing a button, or by voice, or by sliding. This embodiment does not impose any limitation on the implementation method of the user's input operation. The user's physical index information can also be obtained through real-time measurement.

[0056] Specifically, the processing and analysis module may include a computer device, which may include: a terminal and a server. The terminal may be a terminal device in various AI application scenarios. For example, the terminal may be a smart home device such as a smart TV or a smart TV set-top box, or the terminal may be a mobile portable terminal such as a smart phone, a tablet computer, and an e-book reader, or the terminal may be a smart wearable device such as smart glasses or a smart watch, which is not specifically limited in this embodiment.

[0057] The server can be a single server, or a server cluster consisting of several servers, or the server can include one or more virtualization platforms, or the server can be a cloud computing service center. The server can be a server device that provides background services for the AI ​​application installed in the above terminal.

[0058] The terminal and the server establish a communication connection through a wired or wireless network. Optionally, the wireless network or wired network uses standard communication technology and / or protocols. The network is usually the Internet, but can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a private network or any combination of a virtual private network.

[0059] Optionally, the terminal is used to obtain the user's attribute characteristic information and the user's physical indicator information, and send the attribute characteristic information and the physical indicator information to the server, so that the server generates ingredient screening conditions according to the attribute characteristic information, and searches for target ingredients and target recipes that meet the ingredient screening conditions from a preset ingredient library and a preset recipe library based on the physical indicator information, and sends the target ingredients and target recipes to the terminal so that they are displayed on the terminal, thereby realizing the recipe recommendation operation.

[0060] The processing and analysis module 20 is used to receive the user's attribute characteristic information and physical index information, analyze the attribute characteristic information, generate food screening conditions, and then search for a list of ingredients that meet the food screening conditions from the preset food library, search for a list of recipes that meet the food screening conditions from the preset recipe library, and search for target ingredients and target recipes from the ingredient list and recipe list according to the physical index information. The target ingredient is an ingredient that meets the user's physical index information and meets the food screening conditions, and the target recipe is a recipe that meets the user's physical index information and meets the food screening conditions.

[0061] The above-mentioned preset ingredient library and preset recipe library can be customized according to actual needs. The preset ingredient library contains multiple ingredient categories and corresponding ingredients; the preset recipe library contains multiple recipes, each recipe can include corresponding ingredients, servings, corresponding calories and other parameters.

[0062] Optionally, the above-mentioned processing and analysis module 20 is specifically used to: search for a list of ingredients and a list of recipes that meet the ingredient screening conditions from a preset ingredient library and a preset recipe library; calculate the user's calorie restriction parameters based on physical indicator information; perform calorie analysis on the ingredient list based on the calorie restriction parameters to determine the target ingredients and the corresponding ingredient portions; determine the target recipe based on the target ingredients, ingredient portions and recipe list.

[0063] Among them, due to the different calories required for different activity levels, for example, the calories required for long-term sitting are less than the calories required for light activities, the calories required for light activities are less than the calories required for moderate activities, and the calories required for moderate activities are less than the calories required for high activities. After obtaining the user's height information and weight information, the body mass index (BMI) and basal metabolic rate (BMR) can be calculated first, and the user's calorie restriction parameter can be determined based on the body mass parameters and the basal metabolic rate. The calorie restriction parameter can be a calorie restriction range, for example, it can be 100-500 kcal. Since different ingredients of different portions have different calories, the calorie analysis of each ingredient in the ingredient list can be performed based on the calorie restriction parameter to determine the target ingredient and the corresponding ingredient portion within the calorie restriction range. The target ingredient is the ingredient that can be provided to the user for selection among all the ingredients in the ingredient list, and the target recipe is the recipe that can be provided to the user for selection in the recipe list.

[0064] After obtaining the target ingredients and the corresponding ingredient quantities, alternative recipes that include the target ingredients can be screened out from the recipe list, and then the alternative recipes can be improved and adjusted according to the ingredient quantities to obtain the target recipe that meets the user's personalized needs.

[0065] Exemplarily, after the processing and analysis module 20 obtains the attribute characteristic information and physical indicator information of the user, the attribute characteristic information includes biometric information, food restriction information and nutritional element information. According to the biometric information, it can be analyzed that the user has mild anemia and is controlling his weight, the food restriction information may be that the user is allergic to dairy products and does not eat red meat, and the nutritional element information may include: iron, protein, vitamins, and minerals. The generated food screening conditions may include: a small amount of carbohydrates, no dairy products and red meat, and the ingredients contain iron, protein, vitamins, and minerals.

[0066] After obtaining the ingredient screening conditions, you can filter out a list of ingredients that meet the ingredient screening conditions from the preset ingredient library, for example, it may include oatmeal, strawberries, pumpkin, spinach, brown rice, broccoli, etc., and filter out a list of recipes that meet the ingredient screening conditions from the preset recipe library, for example, it may include: oatmeal porridge with strawberries and pumpkin, grilled salmon with steamed spinach and brown rice.

[0067] After obtaining the ingredient list and recipe list, the user's calorie restriction parameters can be calculated based on the height information and weight information, for example, a calorie restriction range of 100-500 kcal. Then, a calorie analysis is performed on each ingredient in the ingredient list, and target ingredients and corresponding ingredient portions that meet the calorie restriction range are screened out from the ingredient list based on the calorie restriction parameters. For example, if the target ingredients are salmon and spinach, and the corresponding ingredient portions are both 500g, then the target recipe is determined to be grilled salmon with steamed spinach and brown rice based on the target ingredients, ingredient portions and recipe list.

[0068] In this embodiment, the above-mentioned recipe recommendation can be applied to the entire diagnosis and treatment cycle of the user, such as the initial diagnosis and treatment plan to the rehabilitation management stage. For each stage, ingredient screening conditions can be generated according to the user's biometric information, ingredient restriction information and nutritional element information, and based on the user's physical indicator information at the current stage, the target ingredients and target recipes that meet the ingredient screening conditions can be searched from the preset ingredient library and the preset recipe library. By combining traditional Chinese medicine nutrition and modern nutrition theory, the user is provided with a nutrition management plan that is more in line with personal physiological characteristics through calculation, thereby providing the user with a full-chain service for the entire diagnosis and treatment cycle, which is suitable for calorie control of different diseases, such as total calorie control for diabetes, kidney disease, etc., as well as certain special nutrient needs, and then through multi-dimensional ingredient screening such as body characteristic information and attribute characteristic information, a target recipe that better meets the user's current personalized needs is obtained.

[0069] In one embodiment, see Figure 2As shown, the feature acquisition module 10 may include a biometric detection unit 11, an ingredient restriction information acquisition unit 12, and a nutrient element acquisition unit 13; the biometric detection unit 11 is used to obtain the user's biometric information; the ingredient restriction information acquisition unit 12 is used to obtain the user's ingredient restriction information; the nutrient element acquisition unit 13 is used to obtain the user's nutrient element information.

[0070] It should be noted that the above-mentioned biometric detection unit 11 may include multiple detection devices or sensors, for example, it may include detection devices for detecting user's electroencephalogram, electrocardiogram, blood pressure, lung function, body temperature, body surface color and other information, and each detection device can detect at least one parameter information.

[0071] The biometric detection unit 11 includes an electroencephalogram detection unit 111 , an electrocardiogram detection unit 112 , a quantum resonance detection unit 113 , a blood pressure detection unit 114 , a lung function detection unit 115 , a body temperature detection unit 116 , and a body surface color detection unit 117 .

[0072] The electroencephalogram detection unit 111 is used to obtain the electroencephalogram parameters of the user; the electrocardiogram detection unit 112 is used to obtain the electrocardiogram parameters of the user; the quantum resonance detection unit 113 is used to obtain the quantum resonance detection parameters of the user; the blood pressure detection unit 114 is used to obtain the blood pressure parameters of the user; the pulmonary function detection unit 115 is used to obtain the pulmonary function parameters of the user; the body temperature detection unit 116 is used to obtain the body temperature parameters of the user; and the body surface color detection unit 117 is used to obtain the body surface color parameters of the user.

[0073] It is understandable that the above-mentioned EEG parameters can be used to reflect the electrical activity of the brain. By analyzing the waveform, frequency, amplitude and other parameters of the EEG, brain diseases can be diagnosed, brain function status can be evaluated, neuroscience can be studied, etc. The electrocardiogram parameters are used to reflect the electrophysiological activity of the heart. By analyzing the waveform, frequency, amplitude and other parameters of the electrocardiogram, heart disease can be diagnosed, heart function can be monitored, and a basis for the treatment of heart disease can be provided. Quantum resonance monitoring parameters are used for early disease screening and evaluation of the overall state of the body. Blood pressure parameters are important indicators for evaluating cardiovascular health, which are used to diagnose hypertension, evaluate cardiovascular analysis, and provide guidance for the treatment of hypertension. Pulmonary function parameters are used to evaluate the functional state of the respiratory system, and by monitoring indicators such as pulmonary ventilation function and ventilation function, lung diseases can be diagnosed, respiratory function can be evaluated, and occupational health assessment can be performed. Body temperature parameters are one of the basic indicators reflecting the state of physical victory, which are used to diagnose diseases, monitor changes in the condition, etc. Body surface color parameters are parameters that reflect physical health, which are used to diagnose anemia, evaluate blood circulation, and evaluate skin diseases.

[0074] In this embodiment, since an electroencephalogram detection unit, an electrocardiogram detection unit, a quantum resonance detection unit, a blood pressure detection unit, a lung function detection unit, a body temperature detection unit, and a body surface color detection unit are provided, various biometric information of the user can be more comprehensively acquired, including electroencephalogram parameters, heart point diagram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, and body temperature parameters, which provides good data guidance information for subsequent recipe recommendations and facilitates accurate recipe recommendations based on the information.

[0075] In one embodiment of the present application, the processing and analysis module is further used to: generate a danger warning instruction and issue a danger warning when at least one of the electroencephalogram parameter, electrocardiogram parameter, quantum resonance detection parameter, blood pressure parameter, lung function parameter, body temperature parameter, and body surface color parameter is in a dangerous range;

[0076] When at least one of the electroencephalogram parameter, electrocardiogram parameter, quantum resonance detection parameter, blood pressure parameter, lung function parameter, body temperature parameter, and body surface color parameter is in an abnormal range, the health assessment parameter of the user is calculated.

[0077] Specifically, each of the above parameters has a normal interval, a dangerous interval, and an abnormal interval. The normal interval, dangerous interval, and abnormal interval corresponding to each parameter can be the same or different, and are customized according to actual needs. The abnormal interval may include a normal threshold and a dangerous threshold. The normal threshold is less than the dangerous threshold. When the parameter is less than the normal threshold, the parameter is characterized as normal; when the parameter is greater than or equal to the normal threshold and less than or equal to the dangerous threshold, the parameter is characterized as abnormal; when the parameter is greater than the dangerous threshold, the parameter is characterized as dangerous.

[0078] After detecting the user's electroencephalogram parameters, electrocardiogram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters, each parameter can be compared with the corresponding abnormal interval and danger interval. When at least one of the electroencephalogram parameters, electrocardiogram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters is in the danger interval, a danger warning instruction is generated and a danger warning is given; when at least one of the electroencephalogram parameters, electrocardiogram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters is in the abnormal interval, the user's health assessment parameters are calculated.

[0079] As an implementable method, when issuing a danger warning, a voice alarm prompt may be used, a display alarm prompt may be used, or an SMS alarm prompt may be used. This embodiment does not impose any limitation on the method of the danger alarm prompt.

[0080] As another feasible method, when at least one of the electroencephalogram parameters, electrocardiogram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters is in an abnormal range, the abnormal parameter can be determined and analyzed using a preset health assessment algorithm to evaluate the user's health status.

[0081] The recipe recommendation system provided in the embodiment of the present application includes: a feature acquisition module, a processing and analysis module and an interactive operation module, the processing and analysis module is electrically connected to the feature acquisition module and the interactive operation module respectively, the feature extraction module is used to: obtain the user's attribute information and send it to the processing and analysis module, the attribute feature information includes: biometric information, food restriction information and nutritional element information; the recipe recommendation interactive operation module is used to: receive and respond to input operations, and obtain the physical index information of the recipe recommendation user; the recipe recommendation processing and analysis module is used to: generate ingredient screening conditions according to the recipe recommendation attribute feature information, and search for target ingredients and target recipes that meet the recipe recommendation ingredient screening conditions from the preset ingredient library and the preset recipe library based on the recipe recommendation physical index information. Compared with the existing technology, the system can obtain the user's biometric information, food restriction information and nutritional element information by setting up a feature acquisition module, and obtain the user's physical index information through an interactive operation module. It can comprehensively consider the biometric information, food restriction information, nutritional element information and physical index information through a processing and analysis module, and combine the nutritional theory of traditional Chinese medicine and food restriction information, so as to more comprehensively search for corresponding ingredients and recipes from the preset food library and recipe library, so as to accurately find the target ingredients and target recipes that meet the food screening conditions, thereby improving the accuracy of recipe recommendations for users in the treatment stage, and is suitable for dietary recommendation scenarios for users at different stages.

[0082] For ease of understanding and explanation, the following Figure 3 The recipe recommendation method provided in the embodiments of the present application is described in detail.

[0083] Figure 3 FIG. 1 is a flow chart of a recipe recommendation method according to an embodiment of the present application. The method may be executed by a processing and analysis module, such as Figure 3 As shown, the method includes:

[0084] S101. Acquire attribute characteristic information of the user; the attribute characteristic information includes: biometric information, food restriction information and nutritional element information.

[0085] It should be noted that the attribute characteristic information of the above-mentioned user includes: biometric information, food restriction information and nutritional element information; the biometric information includes: electroencephalogram parameters, electrocardiogram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters. The user's biometric information may include detection parameters for each of the user's biometric characteristics, and the food restriction information may be determined based on the user's own vital signs. For example, it may be affected by allergens, dietary preferences and other factors, resulting in some food restrictions. The nutritional element information may be determined based on the needs of the user's own conditions.

[0086] Optionally, the user's biometric information, food restriction information and nutritional element information may be obtained through real-time detection, or by querying a database or other information, or by importing from an external device.

[0087] S102: Receive and respond to an input operation to obtain physical indicator information of the user.

[0088] S103: Generate food screening conditions according to the attribute feature information, and search for target food and target recipes that meet the food screening conditions from a preset food library and a preset recipe library based on the physical index information.

[0089] In this embodiment, the above-mentioned physical index information may include: height information and weight information. The recipe recommendation system may provide a user input interface, through which the height information and weight information are input, or the height information and weight information may be obtained through real-time measurement. The food screening condition is used to characterize the rules for screening food in the preset food library.

[0090] In one of the embodiments, in the process of searching for target ingredients and target recipes that meet ingredient screening conditions from a preset ingredient library and a preset recipe library based on physical indicator information, an ingredient list and a recipe list that meet the ingredient screening conditions are searched from the preset ingredient library and the preset recipe library, and the user's calorie restriction parameter is calculated based on the physical indicator information, and then a calorie analysis is performed on the ingredient list based on the calorie restriction parameter to determine the target ingredient and the corresponding ingredient portion, and the target recipe is determined based on the target ingredient, the ingredient portion and the recipe list.

[0091] Specifically, after obtaining the user's attribute characteristic information and physical index information, integration and analysis can be performed based on the attribute characteristic information to generate food screening conditions, and then a list of ingredients that meet the food screening conditions can be found from the preset food library, and a list of recipes that meet the food screening conditions can be found from the preset recipe library. The recipe list can include various ingredients in the food list, and based on the physical index information, the user's calorie restriction parameters are calculated, and calorie analysis is performed on various ingredients in the food list to obtain target ingredients and corresponding ingredient portions, and then based on the target ingredients, a target recipe containing the target ingredients is screened out from the recipe list.

[0092] In this embodiment, by searching for ingredient lists and recipe lists that meet the ingredient screening conditions from the preset ingredient library and the preset recipe library, the ingredient library and the recipe library can be combined to coarsely screen out the ingredient list and the recipe list, and by considering the user's physical indicator information, the user's calorie restriction parameters are calculated, and the calorie needs suitable for the individual are calculated more accurately, which helps to provide more personalized dietary advice and meet the nutritional needs of different individuals. Therefore, the calorie restriction parameters can be comprehensively considered, and the calorie analysis of the ingredient list can be performed to determine the target ingredients and the corresponding ingredient portions, and then the target recipe can be determined in a fine-grained manner. By performing a detailed calorie analysis on the selected ingredients and adjusting the specific amount of each ingredient accordingly, the user can better control the total daily energy intake.

[0093] The above method also includes: when at least one of the electroencephalogram parameters, electrocardiogram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters is in a dangerous range, generating a danger warning instruction and issuing a danger warning; when at least one of the electroencephalogram parameters, electrocardiogram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters is in an abnormal range, calculating the user's health assessment parameters.

[0094] Exemplarily, normal intervals and danger intervals are corresponding to electroencephalogram parameters, electrocardiogram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters. After obtaining electroencephalogram parameters, electrocardiogram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters, it can be determined whether the electroencephalogram parameters are in the corresponding danger interval or abnormal interval. When one or more of the parameters are in the corresponding danger interval, for example, when the electroencephalogram parameters and electrocardiogram parameters are in the corresponding danger interval, a danger alarm prompt instruction is generated and a danger prompt is performed. When one or more of the parameters are in the corresponding danger interval, for example, when the body temperature parameters and blood pressure parameters are in the corresponding abnormal interval, a health status analysis is performed on the body temperature parameters and blood pressure parameters to obtain a health assessment result.

[0095] In this embodiment, by analyzing EEG parameters, ECG parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters, the user's biometric parameters can be monitored more accurately, which facilitates timely alarm prompts when dangerous conditions occur, and quickly and accurately assesses the user's health assessment parameters when abnormal conditions occur, thereby achieving high-quality healthy life.

[0096] The recipe recommendation method provided in the embodiment of the present application includes: obtaining attribute feature information of the user; the attribute feature information includes: biometric feature information, food restriction information and nutrient element information, receiving and responding to input operations, obtaining the user's physical index information, generating food screening conditions according to the attribute feature information, and searching for target food and target recipes that meet the food screening conditions from the preset food library and the preset recipe library based on the physical index information. Compared with the prior art, the technical solution can obtain the user's biometric feature information, food restriction information and nutrient element information, and obtain the user's physical index information through the interactive operation module, and can comprehensively consider the biometric feature information, food restriction information, nutrient element information and physical index information through the processing and analysis module, combining the nutritional theory of traditional Chinese medicine and food restriction information, so as to more comprehensively search for corresponding food and recipes from the preset food library and recipe library, so as to accurately find the target food and target recipes that meet the food screening conditions, improve the accuracy of recipe recommendation for users in the treatment stage, and is suitable for dietary recommendation scenarios for users at different stages.

[0097] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of the code, and the aforementioned module, program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0098] The units or modules involved in the embodiments described in this application may be implemented in software or hardware, and the units or modules described may also be set in a processor.

[0099] In summary, the recipe recommendation system and recipe recommendation method provided in the embodiments of the present application include: a feature acquisition module, a processing and analysis module and an interactive operation module, the processing and analysis module is electrically connected to the feature acquisition module and the interactive operation module respectively, the feature extraction module is used to: obtain the user's attribute information and send it to the processing and analysis module, the attribute feature information includes: biometric information, ingredient restriction information and nutritional element information; the recipe recommendation interactive operation module is used to: receive and respond to input operations, and obtain the physical index information of the recipe recommendation user; the recipe recommendation processing and analysis module is used to: generate ingredient screening conditions according to the recipe recommendation attribute feature information, and search for target ingredients and target recipes that meet the recipe recommendation ingredient screening conditions from the preset ingredient library and the preset recipe library based on the recipe recommendation physical index information. Compared with the existing technology, the system can obtain the user's biometric information, food restriction information and nutritional element information by setting up a feature acquisition module, and obtain the user's physical index information through an interactive operation module. It can comprehensively consider the biometric information, food restriction information, nutritional element information and physical index information through a processing and analysis module, and combine the nutritional theory of traditional Chinese medicine and food restriction information, so as to more comprehensively search for corresponding ingredients and recipes from the preset food library and recipe library, so as to accurately find the target ingredients and target recipes that meet the food screening conditions, thereby improving the accuracy of recipe recommendations for users in the treatment stage, and is suitable for dietary recommendation scenarios for users at different stages.

[0100] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other.

Claims

1. A recipe recommendation system, characterized in that: The recipe recommendation system comprises: A feature acquisition module, a processing and analysis module and an interactive operation module, wherein the processing and analysis module is electrically connected to the feature acquisition module and the interactive operation module respectively; The feature acquisition module is used to: acquire the attribute feature information of the user and send it to the processing and analysis module; the attribute feature information includes: biometric information, food restriction information and nutritional element information; The interactive operation module is used to: receive and respond to input operations, obtain the user's physical index information and send it to the processing and analysis module; The processing and analysis module is used to generate food screening conditions according to the attribute feature information, and search for target food and target recipes that meet the food screening conditions from a preset food library and a preset recipe library based on the physical index information.

2. The recipe recommendation system according to claim 1, characterized in that: The processing and analysis module is specifically used for: Searching for a list of ingredients and a list of recipes that meet the ingredient screening condition from the preset ingredient library and the preset recipe library; Calculating a calorie restriction parameter of the user according to the physical index information; Based on the calorie restriction parameter, performing calorie analysis on the ingredient list to determine target ingredients and corresponding ingredient portions; A target recipe is determined according to the target ingredients, the ingredient quantities and the recipe list.

3. The recipe recommendation system according to claim 1, characterized in that: The feature acquisition module includes: a biometric feature detection unit, a food restriction information acquisition unit, and a nutrient element acquisition unit; The biometric detection unit is used to: obtain the biometric information of the user; The food restriction information acquisition unit is used to: acquire the food restriction information of the user; The nutrient element acquisition unit is used to: acquire the nutrient element information of the user.

4. The recipe recommendation system according to claim 3, characterized in that: The biometric detection unit includes: an electroencephalogram detection unit, an electrocardiogram detection unit, a quantum resonance detection unit, a blood pressure detection unit, a lung function detection unit, a body temperature detection unit, and a body surface color detection unit; The EEG detection unit is used to: obtain EEG parameters of the user; The electrocardiogram detection unit is used to: obtain electrocardiogram parameters of the user; The quantum resonance detection unit is used to: obtain the quantum resonance detection parameters of the user; The blood pressure detection unit is used to: obtain the blood pressure parameters of the user; The pulmonary function detection unit is used to: obtain the pulmonary function parameters of the user; The body temperature detection unit is used to: obtain the body temperature parameters of the user; The body surface color detection unit is used to obtain body surface color parameters of the user.

5. The recipe recommendation system according to claim 4, characterized in that: The processing and analysis module is also used for: When at least one of the electroencephalogram parameter, electrocardiogram parameter, quantum resonance detection parameter, blood pressure parameter, lung function parameter, body temperature parameter, and body surface color parameter is in a dangerous range, a danger warning instruction is generated and a danger warning is given; When at least one of the electroencephalogram parameter, electrocardiogram parameter, quantum resonance detection parameter, blood pressure parameter, lung function parameter, body temperature parameter, and body surface color parameter is in an abnormal range, the health assessment parameter of the user is calculated.

6. The recipe recommendation system according to claim 1, characterized in that: The interactive operation module includes: an input unit and a display unit, wherein the input unit and the display unit are electrically connected; The input unit is used to: receive and respond to input operations to obtain the user's physical index information; The display unit is used to display the physical indicator information.

7. A recipe recommendation method, characterized in that: Applied to the recipe recommendation system as described in any one of claims 1 to 6 above, the method comprises: Acquire attribute characteristic information of the user; the attribute characteristic information includes: biometric information, food restriction information and nutritional element information; Receiving and responding to an input operation, obtaining physical index information of the user; Ingredient screening conditions are generated according to the attribute characteristic information, and target ingredients and target recipes that meet the ingredient screening conditions are searched from a preset ingredient library and a preset recipe library based on the physical index information.

8. The recipe recommendation method according to claim 7, characterized in that: Searching for target ingredients and target recipes that meet the ingredient screening conditions from a preset ingredient library and a preset recipe library based on the physical index information includes: Searching for a list of ingredients and a list of recipes that meet the ingredient screening condition from the preset ingredient library and the preset recipe library; Calculating a calorie restriction parameter of the user according to the physical index information; Based on the calorie restriction parameter, performing calorie analysis on the ingredient list to determine target ingredients and corresponding ingredient portions; A target recipe is determined according to the target ingredients, the ingredient quantities and the recipe list.

9. The recipe recommendation method according to claim 7, characterized in that: The user's attribute characteristic information includes: biometric information, food restriction information and nutritional element information; the biometric information includes: electroencephalogram parameters, electrocardiogram parameters, quantum resonance detection parameters, blood pressure parameters, lung function parameters, body temperature parameters, and body surface color parameters.

10. The recipe recommendation method according to claim 9, characterized in that: The method further comprises: When at least one of the electroencephalogram parameter, electrocardiogram parameter, quantum resonance detection parameter, blood pressure parameter, lung function parameter, body temperature parameter, and body surface color parameter is in a dangerous range, a danger warning instruction is generated and a danger warning is given; When at least one of the electroencephalogram parameter, electrocardiogram parameter, quantum resonance detection parameter, blood pressure parameter, lung function parameter, body temperature parameter, and body surface color parameter is in an abnormal range, the health assessment parameter of the user is calculated.

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