Infant feeding demand evaluation method and device

Abstract

The invention provides an infant feeding demand assessment method and device. The method comprises the following steps: acquiring basic physiological information, activity data and nutrition intake information of a to-be-assessed infant; the obtained basic physiological information, activity data and nutrition intake information are input into an energy consumption model, and the energy consumption model determines the basal metabolic rate of the infant based on the weight and gender information and determines the exercise consumption of the infant based on the heart rate, the activity level, the body temperature, the weight and the non-eating duration; total consumed energy of the infant is determined based on the basal metabolic rate and the exercise consumption; the current total intake energy of the infant is obtained through the energy intake model; and inputting the acquired basic physiological information, nutrition intake information, total consumed energy and current intake total energy into a feeding demand evaluation model to obtain a feeding demand evaluation result of the to-be-evaluated infant. According to the invention, real-time feeding demand evaluation and personalized evaluation of infants can be realized, and the accuracy of feeding suggestions is improved.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method and apparatus for assessing the feeding needs of infants and young children. Background Technology

[0002] Infancy is the period of most rapid growth and development in the human body, and adequate nutrition is a key foundation for physical growth, brain and nerve development, and the maturation of immune function. The World Health Organization (WHO) emphasizes that nutritional status in the first 1,000 days of life not only affects an individual's current health but is also closely related to their long-term health status (such as the risk of obesity, diabetes, cardiovascular disease, and other chronic diseases). This stage is known as the "critical window period" for healthy development.

[0003] However, current infant feeding practices, especially during the introduction of complementary foods, generally suffer from the following four core pain points: 1) The experiential and subjective nature of feeding decisions: Currently, most families, especially new parents, rely heavily on the traditional experience of elders or fragmented knowledge obtained from social media and non-professional channels. These suggestions often suffer from problems such as large individual differences, lack of quantitative standards, and even cognitive biases, making it difficult to achieve precise nutritional management "tailored to each child".

[0004] 2) Difficulty in recognizing "hunger-feeding" signals and information asymmetry between supply and demand: A natural communication barrier exists between feeders (parents) and infants. Parents cannot accurately and quantitatively know the infant's real-time total energy consumption and dynamic nutritional needs, and can only guess their hunger status through indirect behavioral signals such as crying and facial expressions, which easily leads to underfeeding or overfeeding. The latter is one of the important contributing factors to the current rise in infant obesity rates.

[0005] 3) The lag and one-sidedness of nutritional assessment: Existing conventional methods, such as regularly measuring height and weight and comparing them with growth charts, physical examinations, etc., are all "post-assessment" and cannot conduct real-time and accurate quantitative analysis of daily or meal nutritional intake.

[0006] 4) Lack of dynamic regulation based on individual differences: There are significant differences in basal metabolic rate, activity level, digestive and absorptive capacity, and homeostatic elasticity among infants and young children. General dietary recommendations (such as average recommended intake based on age) are difficult to meet the needs of such highly heterogeneous individuals, and there is a lack of a closed-loop control system that can provide real-time feedback and adjustment based on the infant's own multi-dimensional physiological data.

[0007] To alleviate the aforementioned problems, some existing technologies employ comprehensive infant nutrition monitoring systems to assess the nutritional status of infants and young children. These systems typically collect data on infants' height, weight, and body composition using physical devices. The collected data is then analyzed to obtain a biometric set, which is combined with a smart nutrition database comprised of a food database and a standard database to ultimately generate a nutritional plan. The system also generates reports such as body composition analysis, nutritional metabolism regulation, and recommended meal plans.

[0008] While existing comprehensive infant nutrition monitoring systems can ultimately generate nutritional plans, they primarily focus on body composition and physical data (such as body fat percentage, height, and weight) at a specific point in time. They cannot monitor and quantify infants' actual daily energy expenditure in real-time or continuously, nor can they continuously track behavioral parameters related to nutrient metabolism. Their assessments are inherently intermittent and fragmented, failing to achieve a closed-loop correlation analysis of the entire "intake-expenditure-state" cycle, thus deviating from the core physiological theories of "homeostasis" and "total energy expenditure." Furthermore, the nutritional recommendations provided by these systems are mainly based on extrapolations and model predictions from physical measurements, rather than precise, real-time measurements of the infant's actual food intake at each meal. Therefore, they cannot provide real-time, dynamic guidance and adjustments during daily feeding. Consequently, while existing comprehensive infant nutrition monitoring systems can generate nutritional recommendations, they cannot conduct real-time assessments of feeding needs or provide personalized assessments, thus failing to offer accurate feeding advice.

[0009] Therefore, how to achieve real-time and personalized assessment of infants' feeding needs, and how to improve the accuracy of feeding recommendations, are urgent technical problems that need to be solved. Summary of the Invention

[0010] In view of this, embodiments of the present invention provide a method and apparatus for assessing infant feeding needs, in order to eliminate or improve one or more defects existing in the prior art.

[0011] One aspect of the present invention provides a method for assessing the feeding needs of infants and young children, the method comprising: Obtain basic physiological information, activity data, and nutritional intake information of the infants to be evaluated. The basic physiological information includes age in months, height, weight, gender, and body temperature. The activity data includes heart rate and activity level. The nutritional intake information includes milk type, total milk intake, complementary food type, total complementary food intake, and duration of fasting. The basic physiological information, activity data, and nutritional intake information of the infant to be evaluated are input into the energy consumption model. The energy consumption model determines the basal metabolic rate of the infant to be evaluated based on the obtained weight and gender information, determines the exercise consumption of the infant to be evaluated based on the obtained heart rate, activity level, body temperature, weight, and fasting time, and determines the total energy consumption of the infant to be evaluated based on the basal metabolic rate and exercise consumption. The obtained nutrient intake information is input into the energy intake model to obtain the current total energy intake of the infant to be evaluated; The basic physiological information, nutritional intake information, total energy expenditure, and current total energy intake of the infant to be assessed are input into the feeding needs assessment model to obtain the feeding needs assessment results of the infant to be assessed.

[0012] In some embodiments of this application, the nutritional intake information includes the amount of milk and complementary food fed at the last feeding. The basic physiological information, nutritional intake information, total energy expenditure, and current total energy intake of the infant to be assessed are input into a feeding needs assessment model to obtain the feeding needs assessment results for the infant to be assessed, including: The milk requirement of the infant to be assessed is determined based on the infant's age in months, duration of non-feeding, amount of milk in the last feeding, and total amount of milk fed. The milk requirement includes the recommended amount of milk to be fed. The complementary food requirement of the infant to be evaluated is determined based on the infant's age in months, duration of non-feeding, amount of complementary food fed last time, type of complementary food, and total amount of complementary food fed. The complementary food requirement includes the recommended amount of complementary food and the recommended type of complementary food. The hunger level and feeding status of the infant to be assessed are determined based on the total energy expenditure and current total energy intake of the infant to be assessed. The feeding status is defined as needing to be fed immediately, needing to be fed as soon as possible, not needing to be fed, reducing the amount of the next feeding, or extending the feeding interval. The feeding needs assessment results of the infants to be assessed are determined based on their milk intake requirements, complementary food intake requirements, energy balance, and hunger level.

[0013] In some embodiments of this application, determining the hunger level and feeding status of the infant to be assessed based on the total energy expenditure and current total energy intake includes: The energy balance status is determined based on the difference between the total energy expenditure and the current total energy intake of the infant to be evaluated. The hunger level and feeding status of the infant to be evaluated are determined based on the energy balance state.

[0014] In some embodiments of this application, the obtained nutrient intake information is input into an energy intake model to obtain the current total energy intake of the infant to be evaluated, including: The milk energy density is determined based on the milk type, and the milk energy intake is determined based on the milk energy density and the total amount of milk fed. The energy density of the complementary food is determined based on the type of complementary food, and the energy intake of the complementary food is determined based on the energy density of the complementary food and the total amount of complementary food fed. The total energy intake of the infant to be evaluated is obtained based on the energy intake from milk and complementary foods.

[0015] In some embodiments of this application, the energy expenditure model determines the basal metabolic rate of the infant to be evaluated based on the acquired weight and gender information, including: The formula for calculating the basal metabolic rate of the infant to be evaluated is determined based on the obtained gender information; The basal metabolic rate of the infant to be evaluated is calculated based on weight and the aforementioned basal metabolic rate calculation formula; when the infant to be evaluated is male, the basal metabolic rate calculation formula is as follows: When the sex of the infant to be evaluated is female, the formula for calculating the basal metabolic rate is: ;in, W represents basal metabolic rate, and W represents body weight.

[0016] In some embodiments of this application, the method includes: acquiring post-feeding status feedback data of the infant to be assessed based on the feeding needs assessment results, and determining the decision strategy of the feeding needs assessment model based on the hunger level and status feedback data of the infant to be assessed.

[0017] In some embodiments of this application, the exercise expenditure of the infant to be evaluated is determined based on the obtained heart rate, activity level, body temperature, weight, and duration of fasting, including: The basal metabolic rate of the infants to be evaluated was determined based on heart rate. The modified exercise metabolic rate is obtained by adjusting the basal exercise metabolic rate based on the activity level and body temperature. The exercise expenditure of the infants to be evaluated is determined based on the modified exercise metabolic rate, body weight, and duration of fasting.

[0018] In some embodiments of this application, the formula for calculating the basal metabolic rate is as follows: The formula for calculating the corrected exercise metabolic rate is as follows: The formula for calculating the amount of exercise consumed is: Where m1 represents basal metabolic rate, R represents heart rate, m2 represents modified metabolic rate, T represents temperature, and ac represents activity level. W represents energy expenditure during exercise, and W represents body weight. Indicates the duration of fasting.

[0019] According to another aspect of this application, an infant feeding needs assessment system is also disclosed, the system including a processor, a memory and a computer program stored in the memory, the processor being used to execute the computer program, and when the computer program is executed, the system performing the steps of the method as described in any of the above embodiments.

[0020] According to another aspect of this application, a computer-readable storage medium is also disclosed, on which a computer program is stored, which, when executed by a processor, implements the steps of the method as described in any of the above embodiments.

[0021] The infant feeding needs assessment method and apparatus of the above embodiments of this application integrate individual parameters such as infant age, height, weight, and body temperature, calculate basal metabolic rate and exercise expenditure based on an energy consumption model, and convert food weight data into a precise quantitative assessment of macronutrients, achieving a direct correlation between "food data and physiological needs." Furthermore, this method accurately obtains the energy and nutritional composition of each meal, combines heart rate and the interval between meals to quantify behavioral energy consumption, and simultaneously integrates metabolic data; it calculates total energy expenditure and energy surplus in real time, accurately determining whether hunger signals are a true negative energy balance or habitual crying; and it provides personalized feeding suggestions before the next feeding, achieving dynamic guidance "during feeding - before feeding," and realizing "steady-state flexibility" in daily assessment and intervention. This enables real-time and personalized assessment of infant feeding needs, improves the accuracy of feeding suggestions, and reduces the risk of overfeeding.

[0022] Additional advantages, objects, and features of the invention will be set forth in part in the description which follows, and will also become apparent in part to those skilled in the art upon studying the description, or may be learned by practice of the invention. The objects and other advantages of the invention can be realized and obtained by means of the structures specifically pointed out in the description and drawings.

[0023] Those skilled in the art will understand that the objectives and advantages achievable with the present invention are not limited to those specifically described above, and that the above and other objectives achievable with the present invention will become clearer from the following detailed description. Attached Figure Description

[0024] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, are not intended to limit the scope of the invention. The components in the drawings are not drawn to scale but are merely illustrative of the principles of the invention. For ease of illustration and description of certain parts of the invention, corresponding portions in the drawings may be enlarged, i.e., may appear larger relative to other components in an exemplary device actually manufactured according to the invention. In the drawings: Figure 1 This is a flowchart illustrating an embodiment of an infant feeding needs assessment method according to this application.

[0025] Figure 2 This is a schematic diagram of the architecture of an infant feeding needs assessment system according to an embodiment of this application. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments and accompanying drawings. Here, the illustrative embodiments and descriptions of this invention are used to explain the invention, but are not intended to limit the invention.

[0027] It should also be noted that, in order to avoid obscuring the invention with unnecessary details, only the structures and / or processing steps closely related to the solution according to the invention are shown in the accompanying drawings, while other details that are not closely related to the invention are omitted.

[0028] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, element, step, or component, but does not exclude the presence or addition of one or more other features, elements, steps, or components.

[0029] It should also be noted that, unless otherwise specified, the term "connection" in this article can refer not only to a direct connection, but also to an indirect connection with an intermediary, and can refer not only to a wired connection, but also to a wireless connection. The specific meaning can be changed based on the actual application scenario.

[0030] The core drawback of existing infant nutrition monitoring systems lies in their inability to meet the dynamic, real-time, and family-oriented precise feeding needs, as detailed below: (1) The data dimensions are limited to static physique, lacking dynamic metabolic and behavioral closed-loop monitoring.

[0031] Focusing solely on static data from the "intake end" and "vital signs end" (such as food weight, dietary images, height, and weight) fails to quantify infants' daily energy expenditure and behavioral status in real time and continuously. It cannot combine individual parameters like height, weight, and body temperature to calculate dynamic energy expenditure parameters such as basal metabolic rate (BMR) and active metabolic rate (AEE), nor can it quantify energy expenditure resulting from behaviors like crawling, crying, and sleep cycles. It lacks the ability to integrate with wearable devices (such as heart rate and activity monitoring devices), making it impossible to obtain key physiological parameters related to energy expenditure, and it lacks the ability to quantify the "hunger index" in real time, resulting in fragmented nutritional assessments. Even with auxiliary tools like food scales, it can only measure the physical quantity of food weight, unable to analyze macronutrient composition, and cannot correlate it with infants' physiological needs to determine the rationality of intake (e.g., when weighing 150ml of formula, it cannot indicate whether it meets individual energy requirements). Ultimately, nutritional assessment becomes an "open-loop system," unable to answer the crucial question of "whether the ingested nutrients are fully consumed and utilized," thus deviating from the core physiological theory of "homeostasis."

[0032] (2) Nutritional assessment relies on post-hoc estimation and lacks the ability to accurately monitor intake in real time.

[0033] Their nutritional recommendations are all based on model predictions of periodic body measurement data (such as body fat percentage, height and weight), rather than precise monitoring of actual intake at each meal. They fail to deeply integrate with hardware such as high-precision IoT baby food scales, and cannot analyze the calorie and macronutrient (carbohydrate, fat, protein) composition of mixed meals. The data foundation is detached from daily dietary scenarios. Nutritional calculations rely heavily on image recognition and manual input, resulting in large errors in judging food weight and difficulty in accurately analyzing the specific components of mixed complementary foods. This leads to a lack of accurate data support for personalized feeding guidance.

[0034] (3) The feedback is delayed and there is no dynamic adjustment mechanism, lacking the ability to intervene in real time.

[0035] Nutritional analysis and treatment plans are provided only after physical testing, offering retrospective recommendations that cannot provide dynamic guidance and intervention during feeding. The lack of a closed-loop algorithm that combines immediate nutritional intake with continuous physiological status prevents the achievement of routine assessment and intervention for "steady-state elasticity," making it difficult to respond to infants' real-time nutritional needs. Furthermore, the absence of dynamic energy balance assessment based on "intake-expenditure" makes it impossible for parents to determine the nature of their infants' hunger signals (whether it's a genuine negative energy balance or habitual crying), potentially increasing the risk of overfeeding and leading to long-term obesity tendencies.

[0036] (4) The system is closed and the scenarios are limited, making it impossible to integrate into daily family feeding.

[0037] Most of these are large, fixed devices that require infants and young children to go to specific places such as medical institutions or maternal and infant service centers for periodic measurements, making it impossible to achieve continuous monitoring in the home setting. Furthermore, they have not formed a collaborative ecosystem with lightweight hardware such as wearable behavior monitoring devices and home smart baby food scales, resulting in serious deficiencies in data continuity and ease of use, making it difficult to adapt to the high-frequency needs of daily feeding.

[0038] (5) The assessment criteria are not suitable for infants and young children, and the degree of personalization is seriously insufficient.

[0039] Existing technologies lack a dedicated assessment system designed for the specific physiological needs of infants and young children, and also lack individualized adaptation capabilities. General calorie calculation modules typically use adult standards, resulting in structural flaws: the database lacks detailed data on infant-specific foods, failing to distinguish the nutritional differences between adult foods and infant complementary foods; it uses adult energy formulas to calculate basal metabolic rate, which is completely unsuitable for the metabolic characteristics of infants and young children; it fails to incorporate the unique growth and development energy requirements of infants and young children (which account for approximately 25%-30% of total energy), simply adding up food calories while ignoring their specific nutritional reserve needs; and the recommendation algorithms are mostly based on population data or static models, unable to adapt to the highly heterogeneous metabolic levels, digestive and absorptive capacities, and activity patterns of each infant and young child, making it difficult to achieve truly individualized dynamic nutrition planning.

[0040] Existing infant and toddler nutritional needs assessment systems are essentially sophisticated "static physical and body composition measurement devices." They suffer from fundamental deficiencies in data continuity, dimensional behavioral and metabolic dynamics, immediate feedback, and the ability to be seamlessly integrated into daily family settings. Therefore, they are not complete "dynamic assessment and feeding guidance systems" that are fully integrated into daily life. These limitations, particularly the gaps in accurate and immediate intake monitoring, daily metabolic behavior tracking, and individual hunger index calculation, clearly create space and necessity for the innovation of this invention.

[0041] To address the core shortcomings of existing comprehensive infant nutrition monitoring technologies in terms of assessment accuracy, personalization, closed-loop monitoring, nutritional comprehensiveness, and scenario adaptability, this invention provides a method and device for assessing infant feeding needs, enabling real-time and personalized assessment of infant feeding needs and improving the accuracy of feeding recommendations.

[0042] With the rapid development of the Internet of Things, high-precision sensors, artificial intelligence, and metabolomics analysis technologies, the health management field is undergoing a digital, intelligent, and personalized transformation. In the field of infant nutrition, the double-labeled water method has been recognized as the "gold standard" for measuring TEE (Transmitted Energy Excess), providing a scientific basis for accurately calculating individualized energy requirements. Meanwhile, the commercialization of high-precision smart hardware (such as smart baby food scales and wearable devices) has made it possible to continuously and non-invasively monitor nutrient intake and behavioral activities. Furthermore, the concepts of homeostasis and homeostatic elasticity, derived from physiology, have been introduced into health assessment, emphasizing that the body's ability to restore metabolic balance after nutrient intake is a crucial indicator of metabolic health, providing a core theoretical framework for dynamic nutritional assessment.

[0043] These technological advancements and theoretical advancements have laid a solid technical and theoretical foundation for building an infant feeding needs assessment system capable of achieving "multi-dimensional data perception (intake + consumption + status) -> model-based dynamic assessment -> personalized intelligent feedback".

[0044] In the following description, embodiments of the invention will be illustrated with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar parts, or the same or similar steps.

[0045] Figure 1 This is a flowchart illustrating an embodiment of an infant feeding needs assessment method according to this application. Figure 1 As shown, the method includes at least steps S10 to S40.

[0046] Step S10: Obtain basic physiological information, activity data, and nutritional intake information of the infant to be evaluated. The basic physiological information includes age in months, height, weight, gender, and body temperature. The activity data includes heart rate and activity level. The nutritional intake information includes milk type, total milk intake, complementary food type, total complementary food intake, and duration of fasting.

[0047] This step involves acquiring basic physiological data, activity data, and nutritional intake information of infants and young children, providing a complete data source for determining total energy expenditure, current total energy intake, and feeding needs. This step can be implemented through a data acquisition module. For example, the data acquisition module can collect multi-dimensional data through structured forms; additionally, data such as milk volume and complementary food volume can be obtained through devices such as electronic scales, while data such as heart rate, activity level, and body temperature can be obtained through wearable devices.

[0048] After obtaining multi-dimensional data on the infants to be evaluated, further data preprocessing and verification can be performed to clean outliers and fill in missing values, ensuring the accuracy of subsequent calculations and avoiding evaluation bias caused by invalid data. When filtering outliers, if numerical data exceeds the range (e.g., weight <2kg or >25kg, body temperature <35℃ or >41℃), a prompt is triggered, blocking the calculation process and displaying a pop-up message: "Please check the input data (e.g., weight, age in months, etc. must be entered with valid values)." Furthermore, if necessary data (e.g., age in months, gender, body temperature) is not obtained, the submission can be intercepted using the HTML5 required attribute, forcibly completing the core data. When filling in missing values ​​in the data, if a non-required field (such as height) is missing, the "age in months - height" formula is used by default for estimation. For example, the height of an infant aged 0-3 months is calculated as 50 + age in months × 2.5. If data related to complementary foods is missing and the infant is less than 3 months old, 0 is filled in by default (indicating no intake) to avoid errors in calculating empty values.

[0049] In addition, during the data preprocessing stage, all numerical data can be converted to float type to ensure the accuracy of subsequent calculations; time-based data can be uniformly converted to "hour" units to avoid mixing minutes and hours. Data preprocessing can be implemented through a data preprocessing module, which outputs a standardized dataset that has passed verification (e.g., age=3.5, weight=7.2, heartRate=95, lastMilkAmount=150). This standardized dataset is then used by subsequent modules to determine the total energy expenditure, current total energy intake, and feeding requirements of the infants to be evaluated.

[0050] In one specific embodiment, the collection items, control types, parameter limitations, and data flow corresponding to basic physiological information, activity data, and nutritional intake information are shown in the table below: Step S20: Input the basic physiological information, activity data and nutritional intake information of the infant to be evaluated into the energy consumption model. The energy consumption model determines the basal metabolic rate of the infant to be evaluated based on the obtained weight and gender information, determines the exercise consumption of the infant to be evaluated based on the obtained heart rate, activity level, body temperature, weight and fasting time, and determines the total energy consumption of the infant to be evaluated based on the basal metabolic rate and exercise consumption.

[0051] In this step, the basal metabolic rate (BMR), total energy expenditure (TEE), and total energy expenditure of the infants to be assessed are calculated based on relevant data, providing a quantitative basis for nutritional needs assessment. Specifically, this step uses the infant's height, weight, and gender as basic reference values, employs a basal metabolic rate calculation formula specific to infants, and combines multiple dimensions such as body temperature, heart rate, and activity level to construct a dynamic metabolic model that reflects the infant's true energy needs.

[0052] The total energy requirement over a period of time can be divided into basal metabolism and exercise-induced metabolism. Therefore, the energy consumption model calculates the basal metabolic rate of infants and young children based on weight information and gender, and calculates the exercise consumption of infants and young children based on heart rate, activity level, body temperature, weight and fasting time. Finally, the total energy consumption of infants and young children is calculated based on the sum of basal metabolic rate and exercise consumption.

[0053] For example, an infant's daily basal energy requirement is calculated using a linear regression formula, and then combined with the body surface area formula. The corrected BMR is calculated as: BMR = BMR ÷ BSA (unit: kcal / m² / day), which helps improve the adaptability of infants and toddlers of different body types. Here, W represents weight and H represents height.

[0054] In some embodiments, the energy consumption model determines the basal metabolic rate of the infant to be assessed based on the acquired weight and gender information, including: determining a basal metabolic rate calculation formula for the infant to be assessed based on the acquired gender information; and calculating the basal metabolic rate of the infant to be assessed based on the weight and the basal metabolic rate calculation formula.

[0055] When the sex of the infant to be evaluated is male, the formula for calculating the basal metabolic rate is: When the sex of the infant to be evaluated is female, the formula for calculating the basal metabolic rate is: Where BMR_kj represents the basal metabolic rate in kilojoules per day, and W represents body weight. For example, for a female infant weighing 7.2 kg, BMR_kj≈(58.317×7.2-31.1)×4.184≈1560.2 kJ / day.

[0056] Estimating exercise-induced metabolism (also known as exercise expenditure) requires combining heart rate and body temperature, within the existing heart rate-metabolic rate model. Based on this, and taking into account the influence of environmental factors on body temperature changes (ΔT), the actual metabolic rate of infants can be expressed as y·(1+ΔT·10%), and the final calculation result is then converted into calories. According to experiments, multiplying the actual total energy expenditure by 20% can approximately equal the infant's exercise expenditure.

[0057] In one specific embodiment, determining the exercise expenditure of the infant to be assessed based on the obtained heart rate, activity level, body temperature, weight, and duration of fasting includes: determining the basal metabolic rate of the infant to be assessed based on the heart rate; correcting the basal metabolic rate based on the activity level and body temperature to obtain a corrected metabolic rate; and determining the exercise expenditure of the infant to be assessed based on the corrected metabolic rate, weight, and duration of fasting.

[0058] The formula for calculating basal metabolic rate (per kilogram of body weight) is: For every 1°C deviation of actual body temperature from normal body temperature (36.5°C), the exercise metabolic rate is corrected by 10%, i.e., the exercise metabolic rate corrected based on body temperature = m1 × (1 + (T - 36.5) × 0.1). The exercise metabolic rate corrected based on exercise level = m1 × ac, where exercise level is divided into low, medium, and high levels; where ac = 0.8 for low exercise level, ac = 1 for medium exercise level, and ac = 1.2 for high exercise level. Therefore, the formula for calculating the corrected exercise metabolic rate based on body temperature and exercise level is m2 = m1 × (1 + (T - 36.5) × 0.1) × ac. Finally, the formula for calculating exercise expenditure is: TEE_kj = (m2×4.184 / 1000×W×H1×60); where m1 represents the basal metabolic rate, R represents the heart rate, m2 represents the modified metabolic rate, T represents the temperature, ac represents the activity level, TEE_kj represents exercise expenditure, W represents body weight, and H1 represents the duration of fasting. Understandably, for infants who have not yet started solid foods, the duration of fasting is the interval since the last feeding; for infants who have started solid foods, the duration of fasting is the minimum of the interval since the last feeding and the interval since the last solid food intake.

[0059] In summary, the energy expenditure model determines the basal metabolic rate (BMR_kj) of infants and young children based on their weight and gender, and calculates the energy expenditure (TEE_kj) based on their heart rate, body temperature, activity level, weight, and duration of fasting. This model dynamically adjusts the energy expenditure estimate using real-time collected physiological and behavioral data (such as heart rate, activity level, and body temperature), thereby more accurately quantifying the total energy requirements of infants and young children over a specific time period.

[0060] In some embodiments, the energy required to replenish the energy consumed during exercise can be further determined by multiplying the amount of exercise consumed by a coefficient of 0.2, i.e. .

[0061] Step S30: Input the obtained nutrient intake information into the energy intake model to obtain the current total energy intake of the infant to be evaluated.

[0062] This step is based on an energy intake model to obtain the current total energy intake of the infant to be evaluated. The input information of the energy intake model includes milk type, total milk amount fed, complementary food type, total complementary food amount fed, age in months, whether complementary food has been added, etc., while the output data is the current total energy intake.

[0063] For infants and young children, the total energy intake is the sum of the energy from milk and the energy from complementary foods. If the infant or young child is less than 3 months old, the energy intake from complementary foods is zero.

[0064] For example, inputting the obtained nutrient intake information into an energy intake model to obtain the current total energy intake of the infant to be evaluated includes: determining the milk energy density based on the milk type, determining the milk intake energy based on the milk energy density and the total amount of milk fed; determining the complementary food energy density based on the complementary food type, determining the complementary food intake energy based on the complementary food energy density and the total amount of complementary food fed; and obtaining the current total energy intake of the infant to be evaluated based on the milk intake energy and the complementary food intake energy.

[0065] Specifically, the formula for calculating milk energy is: milk_energy = (milk energy density × total milk volume fed) / 100. For example, if the milk type is formula, the corresponding milk energy density is 285. If the total milk volume fed is 150ml, then milk_energy = (285 × 150) / 100 = 427.5kJ. When the infant's age is greater than 3 months, the formula for calculating complementary food energy is: food_energy = (complementary food energy density × total complementary food volume fed) / 100. For example, if the complementary food type is rice cereal, the corresponding complementary food energy density is 1460. If 25g of formula has been fed, then food_energy = (1460 × 25) / 100 = 365kJ. Furthermore, the current total energy intake can be calculated using the following formula: The value of "hasFood" indicates whether complementary foods are added. For example, if the milk intake is 150ml of formula milk and the complementary food intake is 25g of rice cereal, the final calculated total energy intake is approximately 792.5kJ.

[0066] Step S40: Input the obtained basic physiological information, nutritional intake information, total energy consumption and current total energy intake of the infant to be evaluated into the feeding needs assessment model to obtain the feeding needs assessment results of the infant to be evaluated.

[0067] This step can be specifically obtained based on the nutritional needs assessment module. That is, after obtaining the basal metabolic rate BMR_kj, exercise expenditure TEE_kj, and current total energy intake based on steps S20 and S30, the above information is further input into the feeding needs assessment model. The feeding needs assessment model combines the age-specific nutritional standards to assess the infant's milk needs, complementary food needs, and energy balance status, so as to determine the feeding needs assessment results of the infant to be assessed.

[0068] In some embodiments, the nutritional intake information includes the amount of milk and complementary food fed at the last feeding. The basic physiological information, nutritional intake information, total energy expenditure, and current total energy intake of the infant to be assessed are then input into a feeding needs assessment model to obtain the feeding needs of the infant to be assessed. This step may specifically include the following sub-steps: determining the infant's milk intake requirement based on their age in months, duration of fasting, amount of milk fed at the last feeding, and total milk intake already fed; the milk intake requirement result includes a suggested milk intake; and determining the infant's milk intake requirement based on their age in months, duration of fasting, amount of milk fed at the last feeding, and total milk intake already fed. The complementary food intake, complementary food type, and total complementary food intake are used to determine the complementary food intake requirements of the infant to be assessed. The complementary food intake requirements include the recommended complementary food intake and the recommended complementary food type. The infant's hunger level and feeding status are determined based on the infant's total energy expenditure and current total energy intake. The feeding status is defined as needing immediate feeding, needing to be fed as soon as possible, not needing feeding, reducing the next feeding amount, or extending the feeding interval. The infant's feeding needs assessment results are determined based on the milk intake requirements, complementary food intake requirements, energy balance, and hunger level.

[0069] In some embodiments, determining the hunger level and feeding status of the infant to be assessed based on the total energy consumed and the current total energy intake includes: determining the energy balance state based on the difference between the total energy consumed and the current total energy intake of the infant to be assessed; and determining the hunger level and feeding status of the infant to be assessed based on the energy balance state.

[0070] Specifically, a feeding standard library based on age can be used as the benchmark for all assessments and recommendations. This, combined with the total amount of milk fed today and the interval since the last feeding, determines whether feeding is necessary. This determination process can be performed using the `calculateMilkNeed` function. The feeding standards and determination logic are shown in the table below: In addition to the above, the remaining milk requirement for today is further calculated as `remainNeed = Math.max(0, Daily Milk Standard – Total Milk Feeded Today)`. For example, the feeding demand assessment model, based on the input age in months, last milk feeding amount, total milk fed today, and the interval since the last feeding, yields the milk requirement result. The milk requirement result can be represented in the following format (`needFeed=true / false, suggestSingleMilk, remainNeed`), where `true / false` indicates whether feeding is needed / not needed, `suggestSingleMilk` represents the suggested milk amount, and `remainNeed` represents the remaining milk amount.

[0071] In the above embodiments, needFeed is an indicator of whether the infant needs to be fed at present, which is determined based on a comprehensive assessment of factors such as the infant's age in months, the interval since the last feeding, the amount of milk given last time, and the total amount of milk given today. For example, for infants aged 0-1 months, if the interval since the last feeding is ≥2 hours or the last feeding amount is <30ml, then needFeed = true (feeding is needed). Similarly, for infants aged 7-12 months, if the total milk intake today is <500ml and the interval since the last feeding is ≥4.5 hours, then needFeed = true (feeding is needed). suggestSingleMilk (value, unit: ml) represents the recommended single feeding amount (ml) based on the infant's age. Values ​​within a reasonable range are randomly generated for different age ranges to ensure that the feeding amount meets the developmental needs of that stage. For example, for infants aged 0-1 months, the recommended single feeding amount is a random value between 30-60ml; for infants aged 4-6 months, the recommended single feeding amount is a random value between 150-200ml. remainNeed (value, unit: ml) represents the amount of milk (ml) that needs to be added to meet the daily milk intake standard. It is calculated by combining the daily milk intake standard and the amount of milk consumed today. If the result is negative, it is taken as 0. For example, if the daily milk intake standard for a 4-6 month old baby is 1000ml and the baby has consumed 800ml today, then remainNeed = 200ml (an additional 200ml is needed to meet the standard).

[0072] In addition, for infants older than 3 months, the nutritional needs assessment module uses a feeding standard library as a benchmark to assess their complementary food needs based on their age, duration of fasting, amount of complementary food given last time, type of complementary food, and total amount of complementary food given so far. Specific results of the complementary food needs assessment may include whether complementary food needs to be added, the type of complementary food to be added, and the amount to be added. Examples of complementary food standards are as follows: For infants aged 4-6 months: ≤1 time per day, starting with 5g of rice cereal. Do not exceed 1 time per day. If the number of times exceeds 1 time, it indicates "too many complementary food feedings." For infants aged 7-12 months: 2-3 times per day, covering grains + vegetables + fruits + meat. If the interval between the last feeding is ≥6 hours, it indicates "complementary food can be introduced." In addition to the above, the type of complementary food can also be checked: If only rice cereal / fruit puree / vegetable puree is consumed and the number of times is <2 times, it indicates "gradually add animal-based complementary foods (chicken puree / fish puree)."

[0073] In the above embodiments, the feeding needs assessment model mainly makes the following judgments: 1) Milk volume standard judgment: Based on the age of the infant to be assessed, a preset daily milk volume standard is automatically matched (e.g., 0-1 month: 450ml; 1-3 months: 800ml; 4-6 months: 1000ml; 7-12 months: 500ml); by comparing the "total milk volume fed" with the standard value, and combining the percentage difference (within ±5% is acceptable, ±5% to ±10% is slightly abnormal, and beyond ±10% is severely abnormal), the states such as "severely insufficient", "acceptable", and "severely excessive" are dynamically marked on the visual scale axis. 2) Feeding timing judgment: A feeding interval threshold is set for each age group (e.g., 0-1 month: 2 hours; 1-3 months: 3 hours). If the "time since last feeding" is ≥ the threshold for that age, it is determined that "feeding is needed". 3) Determination of complementary food introduction: Follow the rule that "complementary food-related functions are only displayed when the baby is older than 3 months"; for infants aged 1-3 months, the complementary food section is not displayed, only the milk intake is displayed; for infants aged 4-6 months, the core logic is "milk as the main food, complementary food as the supplement", if the number of complementary food feedings is greater than 1, it will prompt "may affect milk intake"; for infants aged 7-12 months, the logic changes to "complementary food as the main food"; if no complementary food is added today or the interval between complementary food feedings is too long (≥6 hours), it will prompt to arrange complementary food.

[0074] Furthermore, the nutrition needs assessment module also assesses energy balance and hunger levels based on the total energy expenditure and current total energy intake of the infants to be assessed.

[0075] For example, energy balance can be assessed based on the following logic: energyBalance = intakeEnergy - TEE_kj * 0.2 - BMR_kj; where energyBalance represents the energy balance state, intakeEnergy represents the current total energy intake, TEE_kj represents the basal metabolic rate, and BMR_kj represents the total energy expenditure through exercise. The hunger level corresponds to the energy balance state, and their relationship is shown in the table below.

[0076] In summary, the feeding needs assessment model of the nutrition needs assessment module generates feeding needs assessment results that include milk feeding needs, complementary food feeding needs, and energy balance status.

[0077] In some embodiments, the infant feeding needs assessment method may further include the following steps: obtaining the status feedback data of the infant to be assessed after feeding based on the feeding needs assessment results, and determining the decision strategy of the feeding needs assessment model based on the hunger level and status feedback data of the infant to be assessed.

[0078] For example, status feedback data includes, but is not limited to, the infant's emotional state after feeding (crying, drowsiness, vomiting, playing happily, normal, etc.), the amount of food remaining (remaining milk or complementary food), and adverse reactions. In some embodiments, the infant's hunger level can be divided into extreme hunger, moderate hunger, and mild hunger; extreme hunger is characterized by incessant crying, body wriggling, strong rooting reflex, and low activity energy; moderate hunger is characterized by intermittent crying, frequent but irregular sucking movements, and an eager response to food sources; mild hunger is characterized by slight sucking, low mood, distraction, and early interest in food.

[0079] Specifically, state level standards for each hunger level can be predefined. For example, extreme hunger can be divided into two levels with scores of 60-80 and 81-100 respectively. In some embodiments, the state levels of each hunger level can be based on the infant's state after or during feeding. For example, a score of 60-80 corresponds to a stable sucking rhythm, calm emotions, and relaxed limbs, while a score of 81-100 corresponds to a state of voluntarily stopping eating, a satisfied expression, complete relaxation, and entering a peaceful sleep. When determining the decision strategy of the feeding needs assessment model based on the hunger level and state feedback data of the infant to be assessed, the state level of the infant is determined based on the obtained state feedback data. Further, the decision strategy of the feeding needs assessment model is determined based on the state level of the state feedback data.

[0080] In the above embodiments, the evaluation results and post-feeding status feedback data are continuously compared to achieve closed-loop optimization. For example, if the model gives a suggestion in a "mildly hungry" state, but the infant quickly reaches "complete satiety" and shows satisfaction after feeding, the decision path is strengthened; conversely, if the suggestion given in a "extremely hungry" state leads to resistance or uneaten food after feeding, the decision path will be adjusted.

[0081] In other embodiments, feeding recommendations can be further generated based on the obtained feeding needs of the infant to be assessed using a feeding recommendation generation module. In this module, based on the nutritional needs assessment results, three types of structured recommendations are generated: "milk intake + complementary food + comprehensive." All text with "recommendation:" is highlighted in red (code warning class, color:#e74c3c) to ensure quick user identification.

[0082] For example, when generating milk volume suggestions, the suggested text is obtained based on the input parameters needFeed, suggestSingleMilk, remainNeed, todayMilkTotal (total milk volume fed today) and the daily milk volume standard. For example, when feeding is needed (i.e., needFeed=true), the output milk volume suggestion text is "Feeding needed: Suggested single feeding {suggestSingleMilk} ml, today's milk volume is {todayMilkTotal} ml, and a supplement of {remainNeed} ml (daily standard {dailyStandard} ml) is needed"; when feeding is not needed (i.e., needFeed=false), the output milk volume suggestion text is such as "Feeding not needed: Suggested to observe hunger signals (looking for the nipple / sucking fingers / crying), and a supplement of {remainNeed} ml is needed today."

[0083] When generating complementary food suggestions, the system outputs suggested text based on the input parameters: age in months, needFeed, hunger level, and hasFood. For example, for infants aged 4-6 months, the output complementary food suggestion text is such as "Suggestion: Start adding iron-fortified rice cereal at 6 months, gradually increasing from 5g / day, once a day, not a substitute for milk." For infants aged 7-12 months, the output complementary food suggestion text is such as "Suggestion: 2-3 complementary foods per day, supplemented with minced meat / fish puree to supplement protein, transitioning to finely chopped texture, without adding salt or sugar; and if no complementary food has been added today, the output complementary food suggestion text is as follows: "Suggestion: No complementary food has been added today, arrange 1-2 times (e.g., 25g rice cereal + 10g vegetable puree)."

[0084] In addition, the feeding suggestion generation module can further generate the following comprehensive suggestions: Infants aged 0-3 months: "Infants aged 0-3 months should be exclusively fed with formula and complementary foods are prohibited. Recommendation: Currently, they need to be fed {suggestSingleMilk} ml of formula and ensure a daily intake of {dailyStandard} ml." For infants aged 4-6 months: "Milk is the main source of energy for infants aged 4-6 months (accounting for 70%). It is recommended to prioritize feeding milk. At 6 months, egg yolk can be added (from 1 / 8 of an egg to 1 whole egg)." For infants aged 7-12 months: "From 7-12 months, complementary foods should be introduced as the main meals, and the milk intake should be fixed at 500ml / day. It is recommended to introduce complementary foods at the next feeding, along with 20g of meat puree, to exercise chewing ability."

[0085] Furthermore, the feeding suggestion generation module can output the evaluation results in the form of "numerical + visualization + text" through the results output and feedback module.

[0086] The output values ​​include basal metabolic rate, total energy expenditure, and energy balance. The output basal metabolic rate is shown as "Basal metabolic rate: ${BMR_kj.toFixed(2)} kJ / day (kJ / day)", the output total energy expenditure is shown as "${last feeding interval} total energy expenditure per hour: ${TEE_kj} kJ (kJ)", and the output energy balance is shown as "energy balance: ${energyBalance.toFixed(2)} kJ (kJ)". Hunger level: ${hunger level} ".

[0087] For visualization output, the following methods can be used: Milk intake target scale axis (code renderMilkGauge function): Scale range: 0 ~ standard value × 1.5 (e.g., 0 ~ 1200ml for 1-3 months); Standard value marker: black vertical line + "Standard: 800ml" label; Current value marker: colored square (green / yellow / red) + "Current: 600ml" label; Range labels: "Severely insufficient", "Slightly insufficient", "Meets", "Slightly excessive", "Severely excessive".

[0088] For text output, the following method can be used: Milk intake requirement suggestion: "Age-based milk intake standard: ${stageRule}" "${milkRecommend}"; Recommendations for introducing complementary foods: "${foodRecommend}" (highlighted in red); Recommendations for comprehensive feeding: "${comprehensiveRecommend}" (highlighted in red).

[0089] In addition to the above, users can also modify and provide feedback on the output results. For example, users can modify the input parameters based on the output results (such as adjusting the age and today's milk intake), and click the "Calculate Energy Requirements and Feeding Suggestions" button again to trigger the process loop and achieve dynamic adjustment.

[0090] The infant feeding needs assessment method described in the above embodiments calculates the basal metabolic rate (BMR) of infants by gender and corrects for the exercise metabolic rate using a dual correction method based on body temperature and activity level, thus reducing the calculation error of the infant's exercise expenditure. Furthermore, this infant feeding needs assessment method takes less than 1 second from "data collection → calculation → suggestion," requires no periodic physical examinations, and provides early warnings 2-3 feeding cycles in advance. The method features lightweight form input, requires no large equipment, is compatible with mobile phones / computers, and improves ease of use by 80%. Additionally, all output "suggestion" text is highlighted, solving the problem of low efficiency in obtaining user information.

[0091] Specifically, the infant feeding needs assessment method of this application breaks through the limitations of adult formulas and achieves precise BMR / REE calculation exclusively for infants: the four-dimensional dynamic parameters of "age in months - body temperature - height - weight" are incorporated into the BMR / REE calculation model. Through a dedicated algorithm, individual physiological parameters are integrated to accurately quantify basal metabolism and resting energy consumption. The error is reduced by more than 40% compared to the scaled version of the adult formula, covering infants and young children of all ages from 0 to 3 years, providing a scientific data foundation for individualized nutrition programs.

[0092] Constructing a real-time closed-loop monitoring system to provide early warnings of energy balance: Designing a real-time closed-loop formula for "energy intake - basal energy consumption - behavioral energy consumption", and using the obtained data, calculating total energy expenditure (TEE) and energy surplus status in real time based on the "steady-state elasticity" theory, providing early warnings of energy deficit / surplus 2-3 feeding cycles in advance, effectively avoiding overfeeding or underfeeding due to delayed assessment, and reducing the long-term risk of obesity.

[0093] Filling the gap in trace element monitoring and achieving visualized management of comprehensive nutrition: Based on the "Chinese Dietary Reference Intakes (2022 Edition)," this application establishes an automatic mapping mechanism of "milligram-level trace elements - gram-level food ingredients," linking essential nutrients such as calcium (250mg / day for 7-12 months), iron (10mg / day), and iodine (115μg / day) with food intake, generating a synchronous visualized curve of "calories - trace elements" on two axes. This completely solves the problem of confusion between the nutritional differences between adult foods and infant complementary foods, meets the special needs of infants for key nutrients, and clearly distinguishes the nutritional differences between adult and infant foods through an infant-specific food database, completely overcoming the limitation of "only counting calories and ignoring key nutrients."

[0094] Adapted to home settings, enhancing the convenience and continuity of feeding management: Embedded in a lightweight program format within the home environment, it eliminates the need for large, fixed equipment and specific measurement locations, improving ease of operation by 80% compared to fixed equipment. Through deep integration with lightweight hardware such as smart baby food scales and wearable heart rate monitoring devices, it achieves automatic synchronization and continuous data collection, balancing ease of operation with data accuracy, and adapting to the actual needs of high-frequency home feeding scenarios.

[0095] Establish a dynamic intervention mechanism to enhance the scientific nature of feeding decisions: Based on real-time energy balance data, the system automatically outputs suggestions on feeding timing, appropriate milk volume, and types / quantities of complementary foods before each feeding. Combining the WHO's "critical 1000-day window of life" theory, nutritional intervention is upgraded from "phased adjustments" to "real-time dynamic guidance," helping parents accurately judge the nature of hunger signals, ensuring that feeding decisions meet the dynamic needs of infant growth and development, and reducing the risk of nutritional imbalance caused by experience-based feeding.

[0096] Accordingly, the present invention also provides an infant feeding needs assessment system, which includes a processor, a memory, and a computer program stored in the memory. The processor is used to execute the computer program, and when the computer program is executed, the system implements the steps of the method as described in any of the above embodiments.

[0097] For example, an infant feeding needs assessment system includes a data acquisition module 110, a data preprocessing module 120, an energy calculation module 130, a feeding needs assessment module 140, and a suggestion generation and output module 150.

[0098] The data acquisition module 110 is used to collect basic physiological information, activity data, and nutritional intake information of the infants to be assessed, input by the user. This module has a complementary food zoning display control function and a complementary food details display control function. The complementary food zoning display control function controls whether the complementary food zoning is displayed based on the infant's age in months, and the complementary food details display control function controls whether the complementary food details are displayed based on whether complementary food has been added today. For example, the controls of the data acquisition module include numerical input boxes (such as age in months, weight), drop-down selection boxes (such as gender, milk type), and labels, etc.

[0099] The data preprocessing module 120 is used to verify data validity, fill in missing values, and standardize data format to ensure that the data can be used for calculation. The energy calculation module 130 specifically includes a basal metabolic rate (BMR) calculation submodule, an exercise expenditure calculation submodule, and a total energy expenditure submodule. The BMR calculation submodule selects the BMR formula according to gender and calculates the BMR based on weight; the exercise expenditure calculation submodule calculates the basal exercise metabolic rate based on heart rate and corrects it by body temperature and activity level; the total energy expenditure submodule calculates the total energy expenditure of infants and young children using the BMR and exercise expenditure.

[0100] The feeding needs assessment module (140 months) assesses the milk intake status, complementary food needs, energy balance, and hunger level at each age, generating assessment results. The suggestion generation and output module (150 months) generates suggestions highlighted in red based on the assessment results, outputting the results in a "numerical + visualization + text" format.

[0101] This invention also provides a computer-readable storage medium and a computer program product having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the above embodiments. The computer-readable storage medium may be a tangible storage medium, such as random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, register, floppy disk, hard disk, removable storage disk, CD-ROM, or any other form of storage medium known in the art.

[0102] Those skilled in the art will understand that the exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention. When implemented in hardware, it can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this invention are programs or code segments used to perform the desired tasks. The programs or code segments can be stored in a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried in a carrier wave.

[0103] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0104] In this invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or in place of features of other embodiments.

[0105] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, various modifications and variations of the embodiments of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method of assessing the feeding needs of an infant or young child, characterized in that, The method comprises: obtaining basic physiological information, activity data and nutritional intake information of an infant to be evaluated, the basic physiological information comprising age, height, weight, gender and body temperature, the activity data comprising heart rate and activity level, and the nutritional intake information comprising milk type, total amount of milk fed, complementary food type, total amount of complementary food fed and non-feeding duration; inputting the obtained basic physiological information, activity data and nutritional intake information of the infant to be evaluated into an energy consumption model, the energy consumption model determining basal metabolic rate of the infant to be evaluated based on the obtained weight and gender information, determining motion consumption of the infant to be evaluated based on the obtained heart rate, activity level, body temperature, weight and non-feeding duration, and determining total consumed energy of the infant to be evaluated based on the basal metabolic rate and motion consumption; inputting the obtained nutritional intake information into an energy intake model to obtain current total intake energy of the infant to be evaluated; inputting the obtained basic physiological information, nutritional intake information, total consumed energy and current total intake energy of the infant to be evaluated into a feeding demand evaluation model to obtain feeding demand evaluation result of the infant to be evaluated.

2. The infant feeding needs assessment method of claim 1, wherein, The nutritional intake information comprises last feeding milk amount and last feeding complementary food amount, the obtained basic physiological information, nutritional intake information, total consumed energy and current total intake energy of the infant to be evaluated are inputted into the feeding demand evaluation model to obtain the feeding demand evaluation result of the infant to be evaluated, which comprises: determining milk amount demand result of the infant to be evaluated based on age, non-feeding duration, last feeding milk amount and total amount of milk fed of the infant to be evaluated, the milk amount demand result comprising recommended feeding milk amount; determining complementary food amount demand result of the infant to be evaluated based on age, non-feeding duration, last feeding complementary food amount, complementary food type and total amount of complementary food fed of the infant to be evaluated, the complementary food amount demand result comprising recommended feeding complementary food amount and recommended feeding complementary food type; determining hunger degree and feeding state of the infant to be evaluated based on total consumed energy and current total intake energy of the infant to be evaluated, the feeding state being immediate feeding, feeding as soon as possible, no feeding, reducing next feeding amount or prolonging feeding interval; determining feeding demand evaluation result of the infant to be evaluated based on milk amount demand result, complementary food amount demand result, energy balance state and hunger degree of the infant to be evaluated.

3. The infant feeding needs assessment method of claim 2, wherein, determining hunger degree and feeding state of the infant to be evaluated based on total consumed energy and current total intake energy of the infant to be evaluated, comprising: determining energy balance state based on difference between total consumed energy and current total intake energy of the infant to be evaluated; determining hunger degree and feeding state of the infant to be evaluated based on the energy balance state.

4. The infant feeding needs assessment method of claim 2, wherein, inputting the obtained nutritional intake information into an energy intake model to obtain current total intake energy of the infant to be evaluated, comprising: determining milk energy density based on the milk type, and determining milk intake energy based on the milk energy density and total amount of milk fed; determine a complementary food energy density based on the complementary food type, and determine a complementary food intake energy based on the complementary food energy density and a total complementary food amount fed; determine a current total energy intake of the infant to be evaluated based on the milk intake energy and the complementary food intake energy.

5. The infant feeding needs assessment method according to claim 1, wherein, The energy consumption model determines a basal metabolic rate of the infant to be evaluated based on the obtained body weight and gender information, including: determining a basal metabolic rate calculation formula of the infant to be evaluated based on the obtained gender information; calculating the basal metabolic rate of the infant to be evaluated based on the body weight and the basal metabolic rate calculation formula; When the gender of the infant to be evaluated is male, the basal metabolic rate calculation formula is: When the gender of the infant to be evaluated is female, the basal metabolic rate calculation formula is: ; wherein, represents the basal metabolic rate, and W represents the body weight.

6. The infant feeding needs assessment method according to claim 2, wherein, The method includes: obtaining state feedback data of the infant to be evaluated after feeding based on the feeding demand evaluation result, and determining a decision strategy of the feeding demand evaluation model based on the hunger level and the state feedback data of the infant to be evaluated.

7. The infant feeding needs assessment method according to claim 1, wherein, determining the motion consumption of the infant to be evaluated based on the obtained heart rate, activity level, body temperature, body weight, and non-feeding duration, including: determining a basal motion metabolic rate of the infant to be evaluated based on the heart rate; correcting the basal motion metabolic rate based on the activity level and the body temperature to obtain a corrected motion metabolic rate; determining the motion consumption of the infant to be evaluated based on the corrected motion metabolic rate, the body weight, and the non-feeding duration.

8. The infant feeding needs assessment method according to claim 7, wherein, The calculation formula of the basal exercise metabolic rate is: The calculation formula of the corrected exercise metabolic rate is, The calculation formula of the exercise consumption amount is: Wherein, m1 represents the basal exercise metabolic rate, R represents the heart rate, m2 represents the corrected exercise metabolic rate, T represents the temperature, ac represents the activity level, represents the exercise consumption amount, and W represents the body weight. represents the length of time without eating.

9. An infant feeding needs assessment system, the system comprising a processor, a memory and a computer program stored on the memory, characterised in that, The processor is configured to execute the computer program, and when the computer program is executed, the system implements the steps of the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method according to any one of claims 1 to 8.

Images