1390 results about "Body weight" patented technology

The invention provides a live pig health monitoring method based on multi-source information fusion, and the method comprises the steps: collecting the sound data of a live pig in a natural environment, carrying out the classification and preprocessing of the sound data, forming a sound sample data set, inputting an LSTM neural network model, and carrying out the training, and obtaining a sound detection model; acquiring a live pig attitude image to obtain an attitude sample data set, and inputting the live pig attitude sample data set into the YOLOv5s model for training to obtain an attitude detection model; inputting live pig sound data collected in real time, preprocessing the data, and inputting the data into the sound detection model to obtain sound features; inputting live pig attitude images collected in real time into the attitude detection model to obtain attitude features; measuring the body temperature of the live pig by using an infrared temperature sensor, measuring the weight of the live pig by using a weight sensor, and fusing the sound feature, the posture feature, the body temperature and the weight to obtain a fusion vector; and inputting the fusion vector into a random forest classifier for decision making, and determining the health state of the live pig. According to the method, multi-modal data are fused, comprehensive evaluation and diagnosis of the health condition of the live pigs are facilitated, and the accuracy and robustness of the whole monitoring system are further improved.

The invention relates to the technical field of health early warning, in particular to a human health early warning method and system based on physical examination data analysis, which comprises the following steps: collecting physical examination data of a human body, analyzing index changes of blood pressure, blood sugar, cholesterol and body mass index of the human body, sorting the physical examination data of the human body through time sequence sorting, and generating a time sequence sorting result. According to the method, time sequence sorting and spatial dimension evaluation are performed on the physical examination data, so that the health risk can be accurately identified and the early warning level can be dynamically evaluated, the data analysis precision is improved, the risk prediction dimension is increased, early warning is more timely and accurate, and the accuracy of early warning is improved by performing layout evaluation on the physical examination data points in a finite dimension space. Potential health abnormalities can be identified on multiple levels, and multi-dimensional analysis provides a new way for identifying complex health problems, so that health management is more active and predictable, health monitoring and risk management are optimized, and the health condition of a patient is improved.

The invention relates to the technical field of disease prediction, in particular to an intelligent risk prediction method based on a neural network, and the method comprises the steps: collecting blood glucose and body mass index data, carrying out the clustering analysis, and constructing a multi-risk group feature; a risk transfer track before attack is recognized by combining a historical index change path and time sequence analysis; and calculating an individual risk coefficient by using deep learning, and comparing the individual risk coefficient with a risk threshold to generate early warning information, thereby realizing dynamic accurate evaluation. According to the method, by collecting the blood glucose level and body weight index data and conducting standardization processing, risk group division based on health index clustering can be achieved, a group recognition system with health feature differentiation is constructed, and the structured understanding of the individual health trend is enhanced. And on the basis of the clustered group, extracting a fluctuation path of individual historical indexes by means of a time sequence mode, identifying key transfer characteristics before disease attack, and enhancing the traceability of the disease formation process.

The invention relates to the technical field of rehabilitation medicine, in particular to a body carving slimming method for fat metabolism based on bioelectricity feedback and acupoint stimulation. The invention provides a body carving slimming method based on bioelectricity feedback and acupoint stimulation. The body carving slimming method comprises the four steps of obtaining, processing, acupoint stimulation and outputting. Bioelectricity signals and weight data of body parts of a user are collected through a bioelectricity and weight detection device. The muscle activity state and fat distribution are analyzed, a posture improvement value is calculated, and a personalized body carving training scheme is generated. In an acupoint stimulation link, electrical stimulation is performed on a specific acupoint according to the scheme, bioelectricity feedback is monitored in real time, and stimulation parameters are dynamically adjusted. And generating a personalized report containing the posture change and the training effect evaluation, and providing suggestions to the user. According to the method, the effect, safety and individuation are remarkably improved, and a new direction is opened up for development of the body carving and slimming field.

A cushion promotes healthy blood flow within the body when the patient is sitting / lying down. A pressure controlling support automatically balances user weight, detects application of user weight, or otherwise detects when the user is at-risk for pressure sores. Pressure is dynamically redistributed by inflation / deflation of individual bladders, rebalancing user support. The cushion prevents the user from applying their weight to impede their blood flow at an at-risk location or from cramping their musculature. The cushion also massages the user's musculature, by moving a pressure difference about selected bladders, promoting blood flow and reducing seating fatigue. The cushion detects changes in pressure at each bladder, to detect / predict user fidgeting / movement and adjust pressure in response thereto, to support the user's new position.

The invention discloses an SNP molecular marker related to the backfat thickness character of a pig living body with the weight of 100 kg and application of the SNP molecular marker. SNP typing data is obtained by integrating re-sequencing data of the pig and comparing the re-sequencing data of the pig to a pig reference genome Sscrofa11.1, whole genome analysis is conducted through a mixed linear model, 5053 SNP sites related to the backfat thickness of the pig living body with the weight of 100 kg are screened out, and the SNP molecular marker related to the backfat thickness character of the pig living body with the weight of 100 kg is obtained. The correlation between the SNP sites and the backfat thickness character of the pig living body with the weight of 100 kg reaches a remarkable level, a new molecular marker is provided for auxiliary selection and improvement of the backfat thickness character of the pig living body with the weight of 100 kg, and the molecular marker has important significance for auxiliary breeding of pigs.

The invention discloses an application of an HERP gene knockout mouse model in obesity and metabolic disorder diseases. The invention finds that compared with a wild type high-fat group, HERP gene knockout can cause phenotypes such as early obesity, more serious obesity degree, increase of fat weight ratio, aggravation of adipose tissue inflammation, dyslipidemia and glucose metabolism disorder of mice during high-fat feeding. And the HERP gene is knocked out, so that the adipocyte differentiation is increased. The HERP gene knockout mouse is more sensitive to nutrition, obesity can occur more quickly during high-fat feeding, symptoms such as fat amplification, fat inflammation and glucose and lipid metabolism disorder are more serious, and the HERP gene knockout mouse can be used for molecular mechanism research and drug screening of obesity, fat tissue and glucose and lipid metabolism disorder. It is further found that cilostazol can significantly relieve mouse obesity and lipid metabolism disorder caused by HERP gene defects, but has no obvious weight losing effect on normal genotype mice, and a new strategy is provided for precise treatment.

This application discloses a rapid detection method for screening of dwarfism in children, which belongs to the field of intelligent medical technology. It includes the following steps: Step 1, accurately sampling through capillary effect, and automatically diluting the sample to ensure accurate concentration; Step 2, introducing the collected sample into a multi-channel microfluidic detection chip to achieve parallel quantitative detection of endocrine hormones; Step 3, real-time acquisition and amplification of weak biomolecule recognition signals to effectively improve the signal-to-noise ratio; Step 4, multi-dimensional analysis of the test results to achieve quantitative evaluation of growth and development, body mass index and sexual development indicators and risk prediction of endocrine diseases; Step 5, automatically integrating the analysis results and generating a standardized test report; Step 6, establishing a quality control mechanism throughout the entire detection process, including real-time monitoring of sample quality, tracking of detection process parameters, result consistency evaluation, and full traceability of detection data.

The invention relates to a multi-modal data feature layer fused sow weight estimation method, which relates to a detection method, and comprises the following steps: acquiring point clouds of sows at different angles through a sow point cloud acquisition device, and taking sow time sequence data such as variety, fetal number and reproduction stage and reconstructed sow real-time three-dimensional point clouds as input; a dual-branch network fused in a feature layer is established, meanwhile, deep features are automatically extracted from one-dimensional data and three-dimensional point clouds, time sequence data features and real-time data features are fused, and current body weight estimation of the sow and body weight curve estimation of the whole breeding stage are completed. Through the method, the accuracy of weight estimation is improved, the final output of the method is the weight real-time value of the current reproduction stage and the weight prediction value of the whole reproduction stage, and the real-time weight value is beneficial for obtaining the physical health condition of the sow at the current stage and adjusting the feeding strategy; therefore, the sows can reach the optimal health state and maintain the optimal production performance, and the minimum feed cost is maintained.

Provided are compositions comprising compounds or precursors to compounds which may be used for a variety of therapeutic applications including, for example, treating and / or preventing a disease or disorder related to reduced or inadequate mitochondrial activity, including aging or stress, diabetes, obesity, and neurodegenerative diseases. The compounds relate generally to urolithins and precursors thereof, including but not limited to ellagitannins and urolithin A. In certain embodiments the compositions are presented in or as food products or nutritional supplements. These same compounds and compositions can also be used advantageously in generally healthy individuals to increase or maintain metabolic rate, decrease percent body fat, increase or maintain muscle mass, manage body weight, improve or maintain mental performance (including memory), improve or maintain muscle performance, improve or maintain mood, and manage stress.

Augmented gear for a user comprises a plurality of weights integrated into the augmented gear, wherein said plurality of weights are a selected fraction of the user's body weight. An insulating material traps the user's body heat under the augmented gear. The augmented gear is also configured to compress against the user's body in three dimensions. The combination of weight, insulation, and compression provides the user with synergistic performance.

The invention provides a breeding environment regulation and control method for promoting rapid maturation of sexual glands of lateolabrax japonicus, and relates to the technical field of lateolabrax japonicus breeding environment regulation and control, and the method specifically comprises the following steps: under different breeding environment parameter combinations, respectively carrying out lateolabrax japonicus breeding tests, constructing a lateolabrax japonicus development prediction model, and obtaining growth state parameters and sexual gland development parameters of lateolabrax japonicus; the method comprises the following steps: establishing a functional relation among body length, body height, body weight and growth character coefficients, establishing a functional relation among gonad weight, gonad index and gonad development coefficients, generating gonad maturation coefficients, performing iterative optimization on the gonad maturation coefficients by adopting a genetic algorithm, screening out individuals corresponding to the gonad development degree reaching the IV stage, and establishing a functional relation among body length, body height, body weight and growth character coefficients. And taking the individual corresponding to the maximum value of the gonad maturation coefficient as an optimal breeding environment parameter combination. According to the method, the optimal breeding environment parameter combination is found out through iterative optimization of the genetic algorithm, so that the aim of promoting rapid maturation of sexual glands of lateolabrax japonicus is achieved, and the breeding efficiency and benefits are improved.

Disclosed herein are methods for treating a subject with T2DM, obesity, or overweight with at least one weight related comorbidity using a glucagon-like peptide-1 (GLP-1) receptor non-peptide agonist (NPA) compound selected from Compound 1, Compound 1a, Compound 2, Compound 3, pharmaceutically acceptable salts thereof, and hydrates of the compounds and pharmaceutically acceptable salts, by oral administration to maintain body weight loss or reduced HbA1c levels resulting from a prior treatment with a GLP-1 RA. Also disclosed herein are uses of a GLP-1 receptor NPA compound for the manufacture of a medicament for treating a subject with T2DM, obesity, or overweight with at least one weight related comorbidity to maintain body weight loss or reduced HbA1c levels resulting from a prior treatment with a GLP-1 RA.

Disclosed are methods and devices for obtaining patent hemostasis of the radial artery by compressing the uninstrumented ulnar artery to increase radial artery flow. The device comprises a band having an inflatable bladder for applying blunt pressure to the ulnar artery. The method comprises applying a pressure to the homolateral ulnar artery and applying a pressure to the radial artery at the access site to obtain hemostasis at the access site. The method further comprises administering an anticoagulant to a patient at a dose ranging from about 20 units per kg of body weight to about 30 units per kg of body weight.

The invention relates to a body weight dynamic-based nutrition state outcome prediction model construction method and system, and belongs to the field of medical informatization. The method comprises the following steps: firstly, establishing a crowd data set containing individual weight information and nutrition state data, and carrying out data preprocessing, including calculating a weight loss percentage and defining an end label; then, the data set is divided into a training set and a test set, and key features related to nutrition state outcome are extracted from the training set through feature screening; and based on the screened features and the training set, constructing a plurality of machine learning classifiers, and selecting an optimal model according to performance indexes of the classifiers. And finally, predicting the test set by using the optimal model, and evaluating the performance of the model. According to the method, the weight dynamic information is utilized, other information assistance is not needed, high-performance prediction of common bad nutrition state outcome can be achieved, and the method has high practical value.

The invention discloses a meat rabbit body weight and body size automatic measuring system based on machine vision, and relates to the technical field of breeding data analysis. The automatic measurement platform is in communication connection with an image capture module, a meat rabbit feature extraction module, a posture transformation module, a body size measurement module, a weight measurement module, a data calibration verification module and a user interaction module, and all the modules are in electric signal connection; and the image capturing module is used for capturing image data of the meat rabbit from different angles. According to the meat rabbit body weight and body size automatic measurement system based on machine vision, measurement of the body weight and body size of a meat rabbit, monitoring of the growth condition of the meat rabbit and capturing of the change trend of the body weight and body size are realized through an image processing technology, so that managers can find abnormal growth or potential health problems of the meat rabbit in time and take corresponding intervention measures, and the management efficiency is improved. Therefore, the feeding management strategy is optimized, and the growth performance and health condition of the meat rabbits are improved.

The embodiment of the invention discloses a feeding method and device capable of accurately regulating and controlling the feed intake of sows. The method comprises the following steps: identifying an individual identity through an electronic ear tag, and collecting backfat thickness, body condition score and weight data by using an inspection robot; dynamically calling a standard feeding curve based on the fetus number and the body condition score, and finely adjusting the target feed intake in combination with the body weight change trend; a quantitative or interactive feeding mode is adopted in the gestation period, feeding is carried out with different meals of wet mixed feed in the lactation period, and the feed-water ratio is dynamically adjusted; meanwhile, a data closed loop is constructed, a feeding strategy is optimized through big data analysis, and abnormal individuals are visualized. According to the scheme, precise self-adaptive regulation and control of the feeding behavior of the sow in the whole breeding cycle are achieved, and the feed efficiency and the breeding performance are remarkably improved.

The invention relates to a weight loss intervention method and device for chronic renal failure and obesity patients based on an individualized prescription. The method comprises the following steps: constructing a multi-modal dynamic time sequence feature vector of a patient; identifying and quantifying potential causal effects of different weight loss intervention measures on physiological outcomes of renal functions, electrolyte balance, anemia states, bone mineral metabolism and weight indexes of the CKD patient according to a dual robust estimator; dynamically constructing a weight loss intervention measure causal model according to the potential causal effect of the physiological outcome of each patient and the physiological and pathological background; and inputting the multi-modal dynamic time sequence feature vector of the patient into a weight loss intervention measure causal model, and generating a daily diet scheme, an exercise scheme and corresponding high-confidence risk early warning and causal explanation of the patient. The method overcomes the limitation that the traditional method only pays attention to correlation and cannot clearly determine the intervention effect, ensures that the causal atlas and the intervention scheme are optimized according to the real-time change state of the patient, and realizes a real dynamic prescription.

The invention relates to the technical field of data analysis, and particularly discloses a Down's syndrome screening system based on multiple key indicators, which comprises the following steps: analyzing historical sample data including pregnant woman age, body weight, race background, pregnancy history record, serum PAPP-A concentration, free beta-hCG concentration, neck transparent layer thickness and the like; mining a chromosome abnormality risk distribution rule; standardizing detection data by adopting a principal component analysis method, grouping pregnant woman features by utilizing a clustering algorithm, and determining a feature offset coefficient; establishing a personalized index reference interval by combining factors such as fetal structure abnormality, chromosome abnormality and family genetic disease history; generating personalized risk probability distribution by fusing individual features and ultrasonic measurement data; according to the method, the risk value is calculated and the dynamically adjusted risk prediction curve is generated according to the real-time detection data and the personalized reference interval, so that an accurate Down's syndrome risk assessment basis is provided for clinical decisions.

This is a mobility aid for disabled persons, including a front frame, a rear frame, and a handle frame. The front frame comprises two front legs having front wheels at the bottom ends thereof. The rear frame is attached to the front frame and includes a saddle seat and a rear leg having a rear wheel attached thereto. The handle frame includes a handle horizontal tube and a vertical handle member depending therefrom. The vertical handle member is attached to the front frame. The handle horizontal tube includes an elbow support at each end and a hand rest support plate having a pair of hand rest spheres. A patient can sit on the saddle seat with their elbow resting on the elbow support so that some or most of their body weight is supported by the saddle and elbow support, while the feet can walk freely.

The invention discloses a postoperative monitoring system and method for a metabolic weight loss surgery patient, and the system comprises a multi-source data collection module which is used for obtaining physiological parameters, behavior data and environment data of the patient in real time, the physiological parameters comprise body weight, blood sugar and body composition indexes, and the behavior data comprise exercise amount and diet records; the environment data comprises temperature, humidity and geographic position; the central processing platform is connected with the multi-source data acquisition module and comprises a data fusion unit for performing space-time alignment and dimension reduction processing on the multi-source heterogeneous data by adopting a feature level fusion algorithm; the dynamic risk assessment unit is used for constructing a patient personalized metabolism model based on the fused data, and dynamically generating nutrition loss and complication recurrence risk indexes through a machine learning algorithm; and the intelligent early warning module triggers a graded early warning signal according to the risk index, generates a personalized intervention scheme and pushes the personalized intervention scheme to the doctor-patient terminal.

The present disclosure relates to methods for treating obesity and / or methods for reducing and maintaining body weight and / or body fat in a patient in need thereof.

The invention discloses a hospital static therapy-based static therapy informatization tracking method and system, and relates to the technical field of static therapy information tracking, and the method comprises the following steps: a medical worker sets an initial venous transfusion flow rate for a patient according to the illness state, weight, age and drug characteristics of the patient and a treatment target; during intravenous infusion of the patient, heart rate information of the patient is obtained in real time through monitoring equipment; the method comprises the following steps: preprocessing acquired original heart rate data, extracting key features, and performing anomaly analysis on the extracted heart rate features in a short-time monitoring window; by acquiring the heart rate information of the patient in real time and combining the machine learning model, the venous transfusion flow rate is dynamically adjusted, and personalized management is achieved. When the heart rate is abnormal, the system automatically reduces the flow rate, the heart burden is reduced, and the safety is improved; under the conventional heart rate, the flow speed is increased, and the infusion efficiency is improved. The intelligent adjusting mechanism not only improves the treatment effect, but also reduces the workload of medical staff and improves the nursing efficiency.

A gravity center transfer trainer comprises a balance training plate, a shell, a left spring, a right spring and a balance pointer, the balance training plate is hinged to the shell, and the balance pointer is connected with the shell; during patient gravity center transfer training, a patient stands on the balance training plate, a doctor instructs the patient to train according to the condition of the patient, the gravity center transfer condition of the patient is visually displayed through the balance pointer, the patient visually views gravity center transfer data of the patient, and the patient can perform gravity center transfer training by observing whether the balance pointer is aligned with the middle zero balance point identifier or not. The patient can clearly know whether the gravity center is on the rotating axis of the human body or not, so that the patient can better cooperate with a doctor for training, and the gravity center transfer training effect is improved; the defect that a patient and a doctor cannot visually see whether the gravity center of the patient is transferred to the central axis of the human body of the patient according to data of a weight scale is overcome, and the problem that gravity center transfer of the human body cannot be visually seen when the weight scale is used for gravity center transfer training is solved.

This disclosure relates to the once weekly dosing regimen of a dual GLP-1R and GCGR agonist, formulations, and methods of using the same for treatment of chronic weight management, obesity and / or blood glucose control, including but not limited to dual agonist peptide product of SEQ ID NO. 1.

The invention discloses a sheep weight and size measuring system and method, and relates to the technical field of animal husbandry breeding intelligent management. Firstly, the invention discloses a sheep weight and body size measuring system, which comprises a PLC (Programmable Logic Controller), a computer, a channel module, a blocking module, an identity recognition module, an entrance module, an image acquisition module, a weighing module and a grouping module, wherein the PLC is in communication connection with the computer. Secondly, the invention discloses a method for measuring the weight and the body size of the sheep, and the method comprises the following steps: S1, driving the sheep into a guide channel at the entrance of the system, and arranging a queue; and S2, a worker starts a blocking module to communicate the recognition channel with the guide channel, and after the first sheep enters the recognition channel, the blocking module is started again to block the space between the recognition channel and the guide channel and block the next sheep. The device has the advantages of automation, high precision and non-contact, so that personal errors and sheep stress are reduced, and the working efficiency is improved.

The invention relates to gestational weight gain prediction. The disclosed concepts are directed to providing protocols, solutions, concepts, designs, methods and systems related to improved prediction of gestational weight gain (GWG). Specifically, during the early stage of pregnancy (e.g., during the first 30 days of pregnancy, or during the first three months of pregnancy), a data sequence describing the weight of a pregnant subject at least twice a day (e.g., after waking up and before falling asleep) is used to determine the historical GWG curve of the subject. Since the energy balance in pregnancy is defined as energy intake equal to energy expenditure plus dynamic energy storage, a particular GWG prediction model is used to generate historical GWG curves, rather than a universal weight gain model. From the historical GWG curve, a future GWG value of the subject may be predicted. The future GWG value may be used to assess pregnancy risk scores, and / or to generate lifestyle recommendations for the subject.

The invention provides novel Weizwinia coagulans BCLD23 which is preserved in CGMCC (China General Microbiological Culture Collection Center) and has a preservation number of CGMCC No.28334 and is used for reducing body weight and application of the novel Weizwinia coagulans BCLD23. The Witzia ciliaris BCLD23 can degrade cholesterol, reduce cholesterol and triglyceride in body serum and reduce body weight, and can be applied to preparation of medicines, food and health care products.

The invention provides an application of a GluN3B inhibitor in preparation of drugs for preventing or treating obesity and related metabolic syndromes. The invention provides application of a GluN3B inhibitor in prevention and treatment of obesity. A food-induced obesity model rich in fat (the proportion is 45%) is taken as a research object, and the GluN3B gene knockout or knockdown can effectively inhibit the weight gain of mice. In-vivo animal experiments show that the knockout or knockdown of the GluN3B gene can activate brown adipose tissues to remarkably promote energy consumption of mice, which is an important reason for causing slow weight growth of the mice.