59 results about "Body composition" patented technology

A programmatically generated AI avatar includes a customizable personality module, acting as the embodied interface for a powerful AI “mind” that delivers personalized coaching to improve user health, well-being, and longevity. The system uses machine learning, large language models, and biometric modeling to synthesize real-time, multi-modal health data—including sleep, nutrition, glucose, mood, and activity—and generate forward-prescribed KHAs. Unlike human coaches, it continuously adapts based on context and behavior, targeting the root cause: metabolic dysfunction—namely by restoring healthy, sustainable body composition through the preservation or building of lean muscle mass and reduction of excess fat. KHAs can also be shared with friends or programmatically generated AI avatars, allowing for coordinated action, emotional support, and accountability through social connection—further reinforcing positive behavior and adherence. The system's reinforcement learning engine incorporates both individual response data and anonymized population-level insights to optimize recommendations over time, learning which interventions are most effective for users with similar physiological and behavioral profiles. First validated with Olympic athletes—resulting in measurable improvements and medal-winning outcomes—this system offers a scalable, emotionally intelligent coaching enginethat exceeds human capability, designed for the ultimate purpose of supporting sustainable health, resilience, and human thriving.

The invention belongs to the technical field of medical image artificial intelligence and body composition analysis, and particularly relates to an MRI-based whole body muscle fat quality evaluation system, which comprises an MRI image data acquisition module, an image preprocessing module, an AI segmentation module, a quantitative calculation module, a database comparison module and a visual report generation module, according to the scheme, an improved U-Net framework is adopted, a KAN layer is embedded behind each Stage of a Swin Transform backbone network, fixed nonlinear activation in a traditional MLP is replaced, high-precision and interpretable modeling of local strength changes is achieved, and the boundary recognition capacity is remarkably improved; according to the scheme, a multi-level fusion mechanism combining SDI and KAN is introduced, the mechanism effectively strengthens a tissue related region and inhibits irrelevant or noise response, high-order nonlinear correction is performed on fused features by using a KAN layer, and complex intensity distribution at a muscle-fat junction is accurately described.

Described are systems and methods to determine one or more regional body composition values for one or more regions of a body based on a processing of one or more two-dimensional images that include a representation of the body. Regional body composition values may include any of a fat tissue mass, a lean muscle mass, a bone mineral density, a skeletal muscle mass, etc., which may be determined for any one or more regions of the body, such as the right arm, left arm, right leg, left leg, trunk, android, gynoid, etc.

The application discloses an intelligent diet management method and system based on multi-source health data fusion, and relates to the field of health diet management. In order to solve the defects of the existing diet management system, such as data fragmentation, manual input dependence, incapability of generating personalized diet plans and incapability of forming a closed-loop feedback, basic information, medical information and body composition data of a user are acquired; initial health parameters are generated according to the basic information, the medical information and the body composition data of the user, wherein the initial health parameters include basal metabolic rate, total energy consumption and total energy requirement; and the initial health parameters are updated according to dynamic input real-time data, so as to realize intervention and management on diet behaviors, wherein the dynamic input real-time data includes diet data and exercise data. The application is mainly used for intervention and management on diet behaviors according to the results of multi-source health data fusion.

The application belongs to the technical field of data recognition, and provides a body age measuring method and device, the body age measuring method comprising: obtaining basic body data and current body composition data of a user to be detected; calculating a matching degree of the user to be detected in a matching library according to the basic body data and the current body composition data; and calculating a body age of the user to be detected according to the matching degree. The body age measuring method provided by the application can effectively overcome the problem in the prior art that only a single or small number of indexes are used to evaluate the body condition and the real age of the body cannot be fully reflected.

The invention discloses a human body figure management method based on multi-modal data fusion, and the method operates in at least two working modes, comprises a general mode and a high-precision mode, and comprises the steps: collecting the multi-modal data of a user, the multi-modal data at least comprises three-dimensional body model data, body composition physiological data and user portrait data containing user health taboo and athletic ability; determining a current working mode on the basis of analysis of the three-dimensional body model data, extracting three-dimensional morphological characteristics according to the current working mode, performing fusion analysis on the three-dimensional morphological characteristics and the body composition physiological data, and generating a quantitative defect list; and based on the quantized defect list and the user portrait data, querying a knowledge graph, and generating a personalized body-building diet scheme. The system robustness is improved, the resource efficiency is optimized, the reliability of the evaluation result is guaranteed, the generation rationality of the personalized scheme is enhanced, and a series of problems caused by data quality fluctuation and splitting are effectively solved.

The present invention provides a body composition estimation program and information processing device that estimate body composition based on measurable values ​​without invasiveness. [Solution] Terminal 1 includes a lean body mass estimation means for estimating lean body mass based on the user's age, gender, height, and weight; a muscle mass estimation means for estimating muscle mass based on the user's age, gender, height, and weight; a sarcopenia determination means for determining the likelihood of sarcopenia based on at least one of lean body mass and muscle mass; a survival rate evaluation means 104 for evaluating the survival rate based on at least one of lean body mass and muscle mass; and a standard index calculation means 105 for calculating a standard index for insurance enrollment based on at least one of lean body mass and muscle mass.

A body composition measuring device configured to perform impedance measurements on a user; compare the measured impedance with a reference datum; and generate an error signal on the basis of the comparison.

The system according to this embodiment aims to suggest the optimal dietary content based on individual body composition and dietary preferences. [Solution] The system according to the embodiment comprises a collection unit, a reception unit, a proposal unit, and a provision unit. The collection unit collects data confirmed by a body composition analyzer. The reception unit receives input on the ideal body shape and dietary preferences. The proposal unit analyzes the information collected by the collection unit and the reception unit and proposes the optimal diet. The provision unit provides the diet proposed by the proposal unit.

The invention is suitable for the technical field of electronic measurement, and particularly relates to an eight-electrode biological impedance body fat scale and a measurement method thereof, and the method comprises the steps: obtaining regional standard impedance, electrode standard contact area, regional real-time impedance and electrode real-time contact area; according to the regional standard impedance, obtaining an upper limb and trunk impedance proportion reference and a lower limb and trunk impedance proportion reference; calculating the contact area deviation based on the real-time electrode and standard contact area, calculating the impedance fluctuation amplitude based on the real-time region and standard impedance, and forming a deviation quantized value set; correcting the abnormal regional impedance based on the upper limb and trunk impedance proportion reference, the lower limb and trunk impedance proportion reference and the deviation quantized value set to form a compensated regional impedance set; and substituting the compensated regional impedance set and pre-recorded age, gender and height parameters into the biological mathematical model to obtain body composition data for reducing the influence of the posture deviation. According to the embodiment of the invention, the accuracy of body composition measurement results can be improved.

A plurality of body composition data corresponding to clothing sizes representing sizes of clothes worn by customers and body composition data of customers measured by a measuring device are established, a clothing size of a customer is estimated, a degree of fitness of the estimated clothing size to the customer is calculated, a salesclerk confirms the estimated clothing size and the degree of fitness displayed on a terminal device, and selection assistance of clothes for the customer is performed.

Provided are a method and an apparatus for analyzing a body composition by using a medical image. The apparatus for analyzing the body composition trains a first artificial intelligence model by using training data labelling a body tissue region, such as muscle or fat, in a medical image for training, and then, segments a body tissue from an examination medical image by using the first artificial intelligence model and outputs body composition information based on a region, a volume, or a weight of the body tissue of the examination medical image. The disclosure is a technique developed through the Seoul Business Agency's 2020 support project for artificial intelligence (AI) technology industrialization (CY20053), “AI Verification and Industrialization of Computed Tomography (CT) Image-based Opportunistic Screening of Metabolic Syndrome, Osteoporosis, and Muscle Reduction.”

A method for recommending a dietary supplement and providing weight-loss exercise and meal schedules may comprise the steps of: acquiring customer data including body composition measurement data and physical constitution test data; acquiring service data including dietary supplement data and exercise and meal schedule data; inputting the customer data and the service data to a tagging artificial intelligence model so as to acquire a keyword for the customer data and a keyword for the service data, respectively, from the tagging artificial intelligence model; inputting the keyword of the customer data and the keyword of the service data to an association analysis artificial intelligence model so as to acquire the service data matching the customer data; and on the basis of the service data matching the customer data, recommending a dietary supplement and providing weight-loss exercise and meal schedules for each customer.

The present application relates to a kind of knee joint muscle function physiological age assessment characterization method, comprising the following steps: collecting the phenotype parameter of subject, establishes community sample database, and phenotype parameter includes the parameter in four categories of body composition, knee joint muscle function, cognitive function and life habit;Correlation analysis is carried out to each phenotype parameter with actual age, and the candidate phenotype parameter significantly related with age is screened;Based on candidate phenotype parameter, establish knee joint muscle function physiological age model;By calculating multi-domain standardization score, construct radar chart to carry out individual deviation characterization.The physiological age assessment characterization method provided by the present application can simultaneously output physiological age estimation result and multi-dimensional function deviation information, provide systematic technical support for early risk identification, health stratified management, individualized intervention of user, compared with prior art, in evaluation precision, information integrity and application adaptability All have obvious promotion, with good popularization and application prospect.

The application discloses a biological age evaluation method, comprising the following steps: obtaining a key protein index of a person to be evaluated, inputting an improved biological age evaluation model I, and obtaining the biological age of the person to be evaluated; the improved biological age evaluation model I is obtained based on an elastic network regression algorithm by taking proteomic data and body composition age of an individual as training data. The application also discloses a construction method of the model, i.e., a two-step method. The application allows a user to calculate the biological age according to the proteomic data, realizes personalized monitoring of muscle aging state, and has great guiding significance in identifying individuals with early muscle function decline and formulating personalized and accurate anti-aging schemes.

This application discloses an exercise prescription generation device, method, equipment, and medium, relating to the field of sports health management technology and applied to computer devices. It includes: a feature extraction module that simultaneously collects body composition and muscle strength data from obese subjects, and obtains body composition and muscle strength features through preprocessing and feature extraction; a preliminary generation module that performs hierarchical judgment on the two types of features to determine the obesity type and muscle strength level, and generates a preliminary exercise prescription based on the combination results; a prescription generation module that uses the body-muscle combination index to determine aerobic exercise parameters and determines resistance training parameters based on the muscle strength level, generating a target exercise prescription for the current execution cycle; an exercise review module that obtains the review results after the subject executes the prescription; and a prescription adjustment module that adjusts the prescription based on the review results to obtain the target exercise prescription for the next execution cycle. This effectively solves the problems of single-dimensional exercise prescription assessment, insufficient personalization, inaccurate intensity matching, and lack of quantitative decision-making and dynamic adjustment.

We provide an information provision system that delivers the necessary information to each user based on body composition measurements. [Solution] The body composition measurement system 100 includes a purpose setting unit 211 for setting the purpose of body composition measurement, a body composition analyzer 30 for measuring body composition, and an information providing unit 221 that provides information according to the purpose set by the purpose setting unit 211 based on the body composition measurement by the body composition analyzer 30.

This product is an electrode clip used in conjunction with a body composition analyzer to measure the subject's body fat percentage, etc. As shown in the "Reference Diagram Showing the State When Connected to a Body Composition Analyzer," connect this product to the body composition analyzer and clip it onto the subject's ankle or wrist to measure body fat percentage, etc.

1. Name of the designed product: body component measuring instrument. 2. Use of the designed product: the product is used to measure the body weight, body fat rate, etc. of a user. 3. Design points of the designed product: in shape. 4. Picture or photograph best indicating the design points: perspective view 1. 5. The left view is symmetrical to the right view, and the left view is omitted. 6. Other circumstances needing explanation: referring to Fig. 1, the state of the operation display part being detached from the main body is shown, in which state the user stands on the foot electrode of the main body, and holds the hand electrodes of the operation display part with both hands, thereby measuring the body weight, body fat rate, etc. of the user. In Fig. 2, the gray part is transparent.

This description relates to a body composition measurement device (100) configured to: perform impedance measurements on a user (U); compare the measured impedance to a reference value; and generate an error signal based on the comparison. Figure 8

The invention provides a postoperative patient compliance monitoring method and device based on biological impedance analysis, and relates to the technical field of medical monitoring, the method comprises the following steps: measuring patient physiological data of postoperative body composition parameters of a patient in real time through a physiological monitoring device integrated with a biological impedance analysis module worn by the patient; exercise monitoring equipment collects exercise amount data of a patient in real time, the collected physiological data and exercise data of the patient are uploaded to a cloud platform through a wireless communication module to analyze multi-dimensional data of the patient, and the postoperative rehabilitation progress of the patient is evaluated; and performing compliance evaluation on movement, diet, nutrition intake and eating behaviors of the patient based on a real-time analysis result, feeding back compliance conditions and improvement suggestions in real time through a patient terminal device, performing personalized intervention and guidance when the compliance of the patient is insufficient, and adjusting a rehabilitation scheme. According to the method, the patient can be helped to better manage postoperative recovery, and personalized diet, exercise and rehabilitation guidance is provided.

A system is provided.SOLUTION: A system comprising: means for a user to input a selfie image and body composition measurement data; means for transmitting the selfie image and the body composition measurement data to a server; means for the server to perform face mapping on the selfie image and analyze body characteristics of the user based on the body composition measurement data; means for the server to compare the analysis result with a latest fashion trend database and propose an optimal fashion, hairstyle, and makeup to the user; and means for transmitting and displaying the proposal to a terminal of the user.SELECTED DRAWING: Figure 1

This description relates to a body composition measurement device (100) configured to: perform impedance measurements on a user (U); compare the measured impedance to a reference data; generate an error signal based on the comparison.

This invention provides a compound nutritional powder with post-exercise recovery function and its preparation method, relating to the field of food processing technology. The preparation method of the compound nutritional powder with post-exercise recovery function includes the following steps: weighing raw materials according to a certain proportion and mixing them evenly to obtain the compound nutritional powder with post-exercise recovery function; the raw materials, by weight, include: 20-50 parts glucose powder, 20-40 parts maltodextrin, 10-25 parts white thorn fruit powder, 2-10 parts soybean peptide powder, and 2-8 parts yak collagen peptide powder. This invention, by compounding glucose powder, maltodextrin, white thorn fruit powder, soybean peptide powder, and yak collagen peptide powder in a specific proportion, combined with vacuum freeze-drying, cell wall breaking, grading and sieving of white thorn fruit powder, and ultraviolet irradiation treatment of some raw materials, achieves the goals of rapid energy supply after exercise, promoting muscle tissue recovery, improving body composition, and enhancing product safety and stability, and has good prospects for the development and application of sports nutrition foods.

The invention discloses a colorectal cancer postoperative risk assessment method, device and equipment and a storage medium, and relates to the technical field of colorectal cancer postoperative assessment, and the colorectal cancer postoperative risk assessment method comprises the following steps: based on a multi-head attention mechanism, segmenting a centrum horizontal CT image of a preoperative and postoperative third lumbar vertebra of a target object, and obtaining a centrum horizontal CT image of a second lumbar vertebra of the target object; obtaining a skeletal muscle area SMA, a visceral fat area VFA and a subcutaneous fat area SFA corresponding to preoperative and postoperative operations; respectively calculating a skeletal muscle index SMI and a visceral fat to subcutaneous fat ratio VSR according to SMA, VFA and SFA before and after the operation; according to the gender of the target object and the preoperative and postoperative SMI and VSR, judging whether the target object is sarcopenia and / or visceral fat obesity; and dividing risk levels according to preoperative and postoperative judgment results. Based on a multi-head attention mechanism, automatic accurate segmentation and risk assessment of the colorectal cancer postoperative body composition are realized, and the analysis efficiency and accuracy are remarkably improved.

1. Name of the product in this design: Graphical User Interface for Human Body Composition Analysis Testing of Electronic Equipment. 2. Intended use of this design: for use in an electronic device. 3. The key design feature of this product lies in the design of its graphical user interface. 4. Images or photos that best illustrate the design points: Interface change state diagram 5. 5. Purpose of the Graphical User Interface: This interface is used for body composition analysis testing. The specific interaction process is as follows: Enter the power-on password in the main view (initial power-on password input interface) to enter interface state diagram 1. In interface state diagram 1 (main operation interface), click "Test" to enter interface state diagram 2. In interface state diagram 2 (test backend interface), select an existing test record on the left and click "Test" again to enter interface state diagram 3. In interface state diagram 3 (weight test interface), after measuring weight, click "Next" in the lower right corner to enter interface state diagram 4. In interface state diagram 4 (test prompt interface), prepare for the test, click "Next" in the lower right corner to enter interface state diagram 5. In interface state diagram 5 (measurement data dynamic analysis interface), after the test is completed, interface state diagram 6 is directly displayed. Click the "Evaluation and Suggestion" button in interface state diagram 6 to display interface state diagram 7. Click the "Segment Component" button in interface state diagram 7 to display interface state diagram 8. Click the "Obesity Analysis" button in interface state diagram 8 to display interface state diagram 9.

The application discloses a kind of three-dimensional full-automatic human body composition analysis method, system and medium based on CT image, method includes: acquisition CT image data and mark;Spine segmentation model is constructed and is trained, the spine segmentation model is in the jump connection part of pre-set U-Net network joins attention module and learns the overall information of spine, to make that spine segmentation model obtains better segmentation effect;Construct body composition segmentation model, and the same loss function and depth supervision method as spine segmentation model is used to train the body composition segmentation model;Based on the spine positioning result and body composition segmentation result obtained in well-trained spine segmentation model and body composition segmentation model, calculate human body composition related index and mutual relationship based on spine positioning result and body composition segmentation result.The application realizes full-automatic process by intelligent positioning to spine, simultaneously provides selectable interface, and it is convenient for user to carry out the analysis of specific organ or tissue.

1. The name of the design product: vibration fat-reducing instrument (BD-X7). 2. The use of the design product: for body massage and fat reduction. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

An object of a system according to an embodiment is to propose training, meals, and a sleep environment that are optimal for an individual user.SOLUTION: A system includes an image analysis part, a body composition meter cooperation part, a meal proposal part, and a sleep proposal part. The image analysis unit analyzes a body shape intended by the user and a photograph of the user. The body composition meter interlocking unit measures a muscle mass and a fat mass based on the data analyzed by the image analysis unit. The meal suggestion unit suggests a meal menu and time based on the data measured by the body composition meter link unit. The sleep suggestion unit suggests a sleep environment based on the data measured by the body composition meter link unit.SELECTED DRAWING: Figure 1

Disclosed are a complex of 3-hydroxy-3-methylbutyric acid and salt thereof as well as preparation method thereof. The complex effectively solves the problems of low solubility, poor stability, acid / salt load, excessive calcium intake and gastrointestinal side effects associated with existing products, has good taste comfort, and improves flavor. In addition, it has the advantages of better increasing muscle weight, improving muscle performance, joint function, body composition or enhancing health. It can be better used as a dietary or nutritional supplement.