Intelligent nutrition intake measuring system and method

Abstract

The invention relates to the technical field of computer systems based on biological models, in particular to an intelligent nutrition intake measuring system and method. An image storage module; the spectral analysis module is used for acquiring spectral information of chemical components of the food; the spectrum storage module is used for storing the spectrum data of the chemical components of the food; the weighing module is used for measuring the weight of the food; the water content data storage module is used for storing food water content data; and the data processing module is used for calling the food image to compare with the food photo, preliminarily judging the food category, calling the chemical component spectrum information of the food to compare with the chemical component spectrum data so as to confirm the food category, and calculating the water content of the food in combination with the food weight and the water content data. The food type and the water content of the same food in different cooking states can be accurately identified, the input amount calculation accuracy is improved, and the nutrition intake of the patient is accurately evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of computer systems based on biological models, and in particular to an intelligent nutrition intake measurement system and method. Background Art

[0002] In nursing work, intake refers to the total amount of various fluids that a patient takes in within a certain period of time. It includes fluids taken orally, such as drinking water, water in food (such as water contained in soup, porridge, fruit, etc.); fluids infused through intravenous routes, such as various drug solutions, nutrient solutions, blood products, etc.; and liquid food and nutrient solutions injected into the gastrointestinal tract through nasogastric feeding, gastroenterostomy, etc.

[0003] The intake and output can directly reflect the circulating blood volume status of critically ill patients. If the patient's intake is significantly less than the output, it may lead to insufficient effective circulating blood volume, which in turn causes shock symptoms such as decreased blood pressure and increased heart rate. For example, patients with severe trauma that leads to massive blood and fluid loss will experience the above symptoms if they fail to replenish enough fluids in time. On the contrary, if the intake is too much and the discharge is not smooth, it may cause excessive circulating blood volume, increase the burden on the heart, and cause heart failure. For example, patients with acute renal failure in the oliguria stage are prone to this situation if they are given too much fluid. Therefore, the calculation of intake and output plays an important role in helping nurses observe the condition and understand the patient's health level.

[0004] The conventional intake statistics method requires medical personnel to weigh the food first, and then calculate the intake in combination with the food water content table. However, this method has cumbersome operation steps, which can easily increase the workload of medical personnel. It is also prone to human errors and reduce the accuracy of intake calculation. Therefore, there are some intake calculation systems specifically for patients in the prior art, such as "A Multifunctional Medical Food Water Content Measuring Scale" (Publication No.: CN 110455389 A), which combines computer audio-visual software and artificial intelligence systems, collects photos of food through image recognition technology, compares the food photos with the food photos in the database to confirm the food type, and then uses the weighing module to measure the weight of the food. Finally, the liquid intake of the food is obtained in combination with the food water content data. However, the prior art still has the following technical problems:

[0005] Since there are various cooking methods for food, for the same kind of food, its water content is different when it is steamed, boiled, fried, stir-fried, etc. respectively. In the prior art, when using image recognition technology to identify the same kind of food with different cooking methods, it is easy to produce misjudgment or confusion, resulting in inaccurate discrimination of the food state and incorrect calculation of the food water content. Moreover, affected by factors such as the image shooting angle, shooting distance, and lighting conditions, it is also easy to misjudge foods with similar appearances as the same kind of food, such as broccoli and cauliflower, cut yams and taros, etc. The image recognition module may not be able to correctly identify the food type, resulting in incorrect calculation of the food water content. Summary of the Invention

[0006] The present invention provides an intelligent nutritional intake measurement system and method, which can solve the problem that the prior art cannot accurately identify the type and state of food, resulting in inaccurate calculation of the food water content and inaccurate calculation of the intake, thus affecting the physical recovery of patients.

[0007] The present application provides the following technical solutions: An intelligent nutritional intake measurement system includes the following modules

[0008] An image acquisition module for acquiring food images;

[0009] An image storage module for storing various food photos;

[0010] A spectral analysis module for obtaining the spectral information of the chemical components of food;

[0011] A spectral storage module for storing the spectral data of the chemical components of various foods;

[0012] A weighing module for measuring the weight of food;

[0013] A water content data storage module for storing the water content data of various foods;

[0014] A data processing module for retrieving the food image and comparing it with the food photo to preliminarily determine the food category, and retrieving the spectral information of the chemical components of the food and comparing it with the spectral data of the chemical components to confirm the food category. Finally, combining the food weight and the water content data, the water content of the food is calculated.

[0015] Advantageous Effects:

[0016] 1. Improve the accuracy of calculating the water content of food and ensure more accurate calculation of the intake. By obtaining the food graph through the image acquisition module and comparing it with the food photos in the image storage module, the food category can be initially determined. However, there is still a situation where foods with similar appearances are easily misjudged. Therefore, the present invention also adopts a spectral analysis module to obtain the chemical composition detection information of the food. The principle is that the chemical compositions of each food are different, and their spectra are also different. Through spectral analysis, the type of food can be accurately determined. At the same time, after the same food undergoes different cooking methods, the chemical bonds of water, protein, fat, carbohydrates, etc. in the food change, thereby affecting the corresponding peaks and positions in the spectrum, showing different spectral images, so as to achieve a more accurate food type recognition function and lock the food type. Finally, by combining the food weight and food water content data obtained by the weighing module, the food water content can be accurately calculated to assist medical staff in calculating the intake quickly and more accurately, reducing human error and the work intensity of medical staff.

[0017] 2. Accurately evaluate nutritional intake and ensure the physical health of patients. Since the spectral analysis module can accurately quantify the contents of components such as water, protein, fat, and carbohydrates in food and comprehensively understand the nutritional composition of food, it helps medical staff to more comprehensively evaluate the nutritional status of patients, avoid ignoring the intake of other important nutrients due to the evaluation of a single nutritional component, and is more convenient to provide accurate nutritional information for different patients, helping medical staff to develop personalized nutritional plans according to the specific conditions of patients and ensuring the physical health of patients.

[0018] Further, the spectral analysis module uses a near-infrared spectral sensor to detect the spectral information of the chemical composition of food.

[0019] Beneficial effects: The chemical components (such as protein, fat, carbohydrates, water, etc.) in each food have unique absorption characteristics for near-infrared light of a specific wavelength. The near-infrared spectral sensor emits near-infrared light in a specific wavelength range to irradiate the food sample, and then detects the reflected or transmitted light signal to obtain the near-infrared absorption spectrum of the food. By comparing this spectrum with the pre-established food spectral database, the type of food can be accurately determined to improve the accuracy of calculating the food water content.

[0020] Further, it also includes a data recording module for recording the basic information, medical condition information, diet and nutritional intake information, and health feedback information of the patient.

[0021] Beneficial effects: Through the data recording module, various information of the patient can be systematically collected and saved, ensuring the integrity and continuity of the data. Medical staff can consult the patient's historical records at any time to understand the changes in the patient's nutritional status and treatment process, providing comprehensive data support for formulating more scientific and reasonable nutritional plans.

[0022] Furthermore, it also includes a display module, which adopts a touch screen display.

[0023] Beneficial effects: The touch screen display provides a more convenient interaction method. Medical staff can operate by touching the screen, such as switching pages, viewing detailed data, inputting personal information, etc. This interactivity makes information acquisition more flexible and improves the usage experience. At the same time, the touch screen can also integrate a handwriting recognition function, which is convenient for medical staff to record special situations or for patients to input personalized needs.

[0024] Furthermore, it also includes a judgment module, which is used for medical staff to confirm whether the food information recognition is correct.

[0025] Beneficial effects: The judgment module is used for medical staff to finally confirm the food information, ensuring the accuracy of food information recognition and laying a foundation for formulating a precise nutrition plan. The judgment module also provides a tool for medical staff to verify and confirm. Even if there are some small errors in the system, medical staff can correct them through their professional judgment, improving the reliability of the entire system.

[0026] Furthermore, it also includes a control module, which is used to control other modules in the system and is electrically connected to all other modules.

[0027] Beneficial effects: The control module will control when the spectral analysis module starts to detect the food, when the display module updates the display content, when the judgment module compares and judges the food information, etc. At the same time, it can also make real-time adjustments according to the operating state of the system to ensure the stable and efficient operation of the entire system.

[0028] An intelligent nutritional intake measurement method includes the following steps:

[0029] a. Data collection: Place the food to be detected in the detection area of the system. The image acquisition module obtains the food image, the near-infrared spectral sensor obtains the spectral information of the chemical composition of the food, and the weighing module obtains the food weight.

[0030] b. Data comparison: The data processing module retrieves the food image and compares it with the food photos in the image storage module to preliminarily determine the food category. At the same time, it retrieves the spectral information of the chemical composition and compares it with the spectral data of the chemical composition in the spectral storage module to confirm the food category.

[0031] c. Data display: Display the recognized food information on the touch screen display.

[0032] d. Data judgment: Medical staff verify and confirm the food information.

[0033] e. Data calculation: The data processing module retrieves the food category and food weight, and at the same time retrieves the food water content data in the water content data storage module to calculate the water content of the food sample. The water content calculation formula is: food sample weight (g) × food standard unit water content ratio (%). Brief Description of the Drawings

[0034] Figure 1 is a schematic structural diagram of the present invention;

[0035] Figure 2 is a left view of the present invention. Detailed Description of the Preferred Embodiments

[0036] The following is a further detailed description through specific embodiments:

[0037] The reference signs in the drawings of the specification include: touch display screen 1, high-definition wide-angle camera 2, weighing platform 3.

[0038] Embodiment 1

[0039] As Figure 1 shown, a certain intelligent food intake calculation device incorporates an intelligent nutrition intake measurement system in the present invention, including the following modules.

[0040] An image acquisition module for acquiring food images; in this embodiment, the high-definition wide-angle camera 2 is used to take pictures of the food on the weighing platform 3, and the image acquisition frequency is set to 5-10 frames per second to capture the fine features of the food.

[0041] An image storage module for storing various food photos.

[0042] A spectral analysis module is used to obtain the spectral information of the chemical composition of food. It uses a near-infrared spectroscopy sensor to emit near-infrared light and detect the spectral signals reflected or transmitted by the food, so as to analyze the chemical composition and structure inside the food; obtain the detection information of the chemical composition of food. The principle is that the chemical composition of each food is different, and its spectrum is also different. Through spectral analysis, the type of food can be accurately determined. At the same time, after the same kind of food has undergone different cooking methods, the chemical bonds of water, protein, fat, carbohydrates, etc. in the food change, thus affecting the corresponding peaks and positions in the spectrum, showing different spectral images, so as to achieve a more accurate food type recognition function and lock the food type; finally, by combining the food weight and food water content data obtained by the weighing module, the food water content can be accurately calculated to assist medical staff in quickly and more accurately calculating the intake, reducing human error and reducing the work intensity of medical staff. At the same time, because the spectral analysis module can accurately quantify the content of components such as water, protein, fat, and carbohydrates in food and comprehensively understand the nutritional composition of food, it helps medical staff to more comprehensively evaluate the nutritional status of patients, avoid ignoring the intake of other important nutrients due to the evaluation of a single nutritional component, and is more convenient to provide accurate nutritional information for different patients, helping medical staff to develop personalized nutrition plans according to the specific conditions of patients and ensuring the health status of patients.

[0043] A spectral storage module is used to store the spectral data of the chemical composition of various foods.

[0044] A weighing module is used to measure the weight of food; it uses a high-precision electronic scale with an accuracy of up to ±0.1 g. At the same time, a disposable meal box is set on the electronic scale, and the food can be placed in the disposable meal box to complete the weighing.

[0045] A water content data storage module is used to store the water content data of various foods.

[0046] A data recording module is used to record the basic information, medical condition information, diet and nutrition intake information, and health feedback information of patients. Through the data recording module, various information of patients can be systematically collected and saved, ensuring the integrity and continuity of the data. Medical staff can consult the historical records of patients at any time to understand the changes in the nutritional status and treatment process of patients, providing comprehensive data support for formulating more scientific and reasonable nutrition plans.

[0047] A display module uses a touch screen display. The touch screen display provides a more convenient interaction method. Medical staff can operate by touching the screen, such as switching pages, viewing detailed data, inputting personal information, etc. This interactivity makes information acquisition more flexible and improves the user experience. At the same time, the touch screen can also integrate a handwriting recognition function, which is convenient for medical staff to record special situations or for patients to input personalized needs.

[0048] A judgment module is used for medical staff to confirm whether the food information recognition is correct. The judgment module is used for the final confirmation of food information by medical staff, ensuring the accuracy of food information recognition, laying a foundation for formulating a precise nutrition plan in the follow-up. The judgment module also provides a tool for medical staff to verify and confirm. Even if there are some small errors in the system, medical staff can correct them through their professional judgment, improving the reliability of the entire system.

[0049] A data processing module is used to retrieve the food image and compare it with the food photo to preliminarily determine the food category, and retrieve the chemical composition spectral information of the food and compare it with the chemical composition spectral data to confirm the food category. Finally, combined with the food weight and water content data, the water content of the food is calculated.

[0050] A control module is used to control other modules in the system and is electrically connected to all other modules. The control module will control when the spectral analysis module starts to detect the food, when the display module updates the display content, when the judgment module compares and judges the food information, etc. At the same time, it can also make real-time adjustments according to the operating state of the system to ensure the stable and efficient operation of the entire system.

[0051] An intelligent nutrition intake measurement method, the logic block diagram of which is as Figure 2 shown, including the following steps:

[0052] a. Data acquisition: Place the food to be detected in the detection area of the system. The image acquisition module obtains the food image, the near-infrared spectral sensor obtains the chemical composition spectral information of the food, and the weighing module obtains the food weight.

[0053] b. Data comparison: The data processing module retrieves the food image and compares it with the food photo in the image storage module to preliminarily determine the food category. At the same time, it retrieves the chemical composition spectral information and compares it with the chemical composition spectral data in the spectral storage module to confirm the food category.

[0054] c. Data display: Display the recognized food information on the touch screen monitor.

[0055] d. Data judgment: Medical staff verify and confirm the food information and can choose to confirm or modify.

[0056] e. Data calculation: The data processing module retrieves the food category and food weight. When retrieving the food weight, the weight of the disposable food container has already been deducted. At the same time, it retrieves the food water content data from the water content data storage module to calculate the water content of the food sample. The water content calculation formula is: weight of food sample (g) × water content ratio of food standard unit (%). For the convenience of calculation, the water content ratio of the food standard unit is based on every 100g. For example, if the weight of a portion of rice is 170g, according to the food water content data table, the water content of every 100g of rice is 70g, that is, the water content ratio of the rice standard unit is 70%. Then the water content calculation method for 170g of rice is 170g × 0.7 = 119g.

[0057] After the data calculation is completed, it will be automatically entered into the data recording module, so that medical staff can consult the patient's historical records at any time, understand the changes in the patient's nutritional status and the treatment process, and provide comprehensive data support for formulating a more scientific and reasonable nutrition plan.

[0058] Example Two

[0059] The difference between this example and Example One is that it further includes an odor sensor and an odor data storage module, both of which are electrically connected to the control module. The odor sensor can identify the odor information of the food sample, and the odor data storage module is used to store the food odor data. By comparing the odors and combining image recognition and spectral analysis, the recognition accuracy of various different types and states of food is further improved, ensuring the accuracy of food water content calculation.

[0060] Example Three

[0061] The difference between this example and Example One is that in this example, it further includes a second matching and recognition module. The second matching and recognition module includes a positioning record module, a payment record acquisition module, a restaurant recognition module, and a dish matching module. Since there are many sources of food, some patient families may bring their own food, but there are also takeaway foods purchased by mild patients. There are more types of takeaway foods, and it may not be possible to store all of them in the image storage module. Therefore, when the food category is misidentified multiple times, the second matching and recognition module is used to assist in identifying the food. The dish matching module is used to match the food to be matched with the menu foods of the merchant; the restaurant recognition module is used to judge the merchant or restaurant corresponding to the food purchased by the user based on the user's location record and payment record; the positioning record module is used to record the user's location record before dining; the payment record acquisition module has the function of acquiring the payment record of the user for a period of time before dining. The data processing module can identify the restaurant name through the payment record and dining record, and then retrieve the menu dishes in the restaurant to match with the actual dishes, so as to determine the type of the food, expand the way the system identifies food, improve the system recognition function, and enhance the reliability of the entire system.

[0062] The above are only embodiments of the present invention. The invention is not limited to the fields involved in this embodiment. Common knowledge such as specific structures and characteristics known in the art are not described in detail herein. It should be noted that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the implementation effect of the present invention and the practicality of the patent. The protection scope required by this application shall be subject to the content of its claims, and the specific implementation manners and the like recorded in the specification can be used to interpret the content of the claims.

Claims

1. An intelligent nutrition intake measurement system, characterized in that: Includes the following modules: An image acquisition module, used for acquiring food images; Image storage module, used to store various food photos; Spectral analysis module, used to obtain spectral information of chemical components of food; Spectral storage module, used to store the spectral data of chemical components of various foods; Weighing module, used to measure food weight; A water content data storage module, used for storing water content data of various foods; The data processing module is used to retrieve food images and compare them with food photos to preliminarily determine the food category, and retrieve the chemical composition spectrum information of the food and compare it with the chemical composition spectrum data to confirm the food category, and finally combine the food weight and water content data to calculate the water content of the food.

2. The intelligent nutrition intake measurement system according to claim 1, characterized in that: The spectrum analysis module uses a near-infrared spectrum sensor to detect the spectrum information of the chemical components of food.

3. The intelligent nutrition intake measurement system according to claim 2, characterized in that: It also includes a data recording module for recording the patient's basic information, medical condition information, diet and nutritional intake information, and health feedback information.

4. The intelligent nutrition intake measurement system according to claim 3, characterized in that: It also includes a display module, which uses a touch screen display.

5. The intelligent nutrition intake measurement system according to claim 4, characterized in that: It also includes a judgment module for medical staff to confirm whether the food information identification is correct.

6. The intelligent nutrition intake measurement system according to claim 5, characterized in that: It also includes a control module, which is used to control other modules in the system and is electrically connected to all other modules. An intelligent nutrition intake measurement method, applied in an intelligent nutrition intake measurement system in claim 1, characterized in that: The steps include: a. Data acquisition: place the food to be tested in the detection area of ​​the system, the image acquisition module obtains the food image, the near-infrared spectral sensor obtains the spectral information of the chemical composition of the food, and the weighing module obtains the weight of the food; b. Data comparison; The data processing module retrieves the food image and compares it with the food photo in the image storage module to preliminarily determine the food category, and retrieves the chemical component spectrum information and compares it with the chemical component spectrum data in the spectrum storage module to confirm the food category; c. Data display, displaying the identified food information on the touch screen display; d. Data judgment: medical staff verify and confirm food information; e. Data calculation: the data processing module retrieves the food category and food weight, and at the same time retrieves the food moisture content data in the moisture content data storage module to calculate the moisture content of the food sample. The moisture content calculation formula is: food sample weight × food standard unit moisture content ratio.

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