891 results about "Body weight" patented technology

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.

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.

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.

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.

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.

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.

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.

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 relates to the technical field of beef cattle breeding, and particularly provides a beef cattle meat percentage prediction method and system based on dynamic physiology and AI three-dimensional body size fusion, and the method comprises the following steps: obtaining the real-time three-dimensional body size data of a target beef cattle, inputting a pre-training AI weight estimation model to obtain the real-time weight data, and carrying out the timestamp association; acquiring dynamic physiological data, and integrating the dynamic physiological data with the body size and weight data associated with the time sequence into a multi-source time sequence data set; multi-source data space-time alignment is completed through a time sequence attention fusion model, time sequence causal association of body weight, physiology and body size changes is mined through an attention mechanism, and a fusion association feature set is generated; and inputting the feature set into a meat percentage prediction model, and outputting a result containing a meat percentage prediction value and a causal association basis. The method breaks through the limitation of traditional static prediction, dynamic high-precision prediction is realized, the causal basis can support the breeding decision, and the precise breeding level and breeding benefits are improved.

The invention relates to the technical field of child health assessment, in particular to a child body fat rate adaptive prediction method and system based on trajectory feature collaboration.The method comprises the following steps that a child physical examination data set is obtained, height and weight changes are analyzed, difference ratio screening samples are calculated, waistline change slope assessment stability screening samples are extracted, and a child body fat rate prediction result is obtained; calculating a sign proportion difference to adjust a training weight, identifying an age group residual difference to adjust model parameters, and adjusting a prediction slope generation result in combination with a body fat trend direction and a body weight trend direction. According to the method, samples are screened through height and weight tracks, abnormal data are eliminated in combination with fluctuation continuity of waistline change slope, a feature weighting coefficient is set according to proportion deviation of height, weight and muscle amount, and a response coefficient is adjusted through a distance relation between a grouping mean value of age group residual errors and a concentration interval. And the change path is judged by utilizing the consistency of the body fat and body weight prediction trend, so that non-trend prediction offset is avoided, and the stability of the model and the sample adaptability are improved.

A combination therapy including both intranasal and oral solid-form preparations is described. In combination, the intranasal and oral delivery pathways provided an enhancement in appetite suppression and associated weight loss in comparison to either intranasal or oral solid-form therapy alone. It was unexpected that the observed substantial increase and increase in rate of weight loss would be observed for the combination therapy, which on average provided a nearly 12% reduction in total body weight over the three-month trial.

The invention relates to the technical field of animal husbandry, and discloses a pig weight measuring and calculating scheme based on body size fusion depth data, comprising the following steps: step 1, depth image acquisition: using depth camera equipment to shoot a pig depth image, overlooking to shoot the back of the pig, ensuring that the whole pig is in the image, and acquiring a depth image; pictures with complete postures of the pigs are screened out from the videos, and invalid video frames with no pigs appearing or the edges of the pigs and the edges of the images intersected are removed at the same time. Feature extraction is carried out by fusing the pig body size and the depth image, the body state of the pig can be captured more accurately, the accuracy of the weight estimation artificial neural network is improved, compared with a method for manually driving the pig to weigh and weigh, the depth camera equipment and the computer vision technology are utilized, manual labor is not needed, pig stress response is removed, and the weight estimation accuracy of the weight estimation artificial neural network is improved. The cost is reduced, and the weight of the pig can be quickly and accurately obtained through the pre-trained weight estimation network, so that the weight estimation of the pig is more convenient and efficient.

An article for performing exercise that may include an attacher piece to attach to an elevated object and an extender piece to extend a horizontal distance from the elevated object while the attacher piece is attached to the elevated object and while the extender piece is connected to the attacher piece. The article may also include a weight suspension piece to suspend a body of weight therefrom while the weight suspension piece is connected to the extension piece. The article may also include a supporter piece configured to extend from at least one of the extender piece and the weight suspension piece to apply force against the elevated object, thereby providing additional support for the suspension of the body of weight from the weight suspension piece.

The invention discloses a method for constructing a polycystic ovarian syndrome (PCOS) rat model with reduced sex hormone binding globulin (SHBG) on the basis of ruminococcus aureus with the preservation number of ATCC29149, and belongs to the technical field of animal models. According to the present invention, the bacterial strain is subjected to anaerobic culture to prepare the bacterial liquid, the dosage is 0.2-1 mL / 100 g, the intragastric administration frequency is one time per day to two times per week, and the time lasts for 4-8 weeks, such that the SHBG synthesis of the rat liver is induced to decrease, and the PCOS pathological characteristics such as testosterone level increase, estrus cycle disorder, ovarian polycystic change, insulin resistance and the like are initiated; the problem that a traditional hormone induction method does not conform to the physiological status is solved, the modeling period of a high-fat diet induction method is shortened, and an efficient experimental tool is provided for PCOS mechanism research and drug development.

The invention provides an airway atomization flow intelligent drug delivery control method and system, and relates to the technical field of medical instruments.The method comprises the steps that basic information of the age, the weight and the illness state severity of a patient is obtained, and physiological parameters of the respiratory rate and the tidal volume of the patient are collected in real time through a sensor; inputting the basic information and the physiological parameters into a fuzzy adaptive control algorithm, and initializing an individual administration rule base according to the basic information; based on the real-time change trend of the respiratory rate and the tidal volume, three initial control index values including an atomization flow value, a drug concentration value and a time interval are dynamically generated through a membership function. According to the invention, through the full-process design of data acquisition, intelligent modeling, accurate execution and data closed loop, intelligentization of atomization treatment is realized.

The invention discloses a mulberry leaf extract for reducing body weight based on blood sugar regulation and a preparation method thereof, and belongs to the technical field of natural product extraction. The mulberry leaf extract is mulberry leaf DNJ, and the extraction and preparation steps of the mulberry leaf extract comprise pretreatment, composite enzymatic hydrolysis, ultrafiltration purification, resin adsorption and freeze-drying molding. By optimizing enzymolysis conditions and a separation and purification process, the extraction rate (gt; and therefore, a foundation is laid for industrial production. DNJ reduces blood sugar and body weight by promoting secretion of GLP-1, when DNJ is combined with GLP-1RA for use, a remarkable synergistic effect is shown, and the effects of reducing blood sugar and losing weight are further enhanced. The invention provides a natural and safe blood glucose reducing and weight losing active component and a preparation method thereof, provides a novel solution for treating diabetes and obesity, and has important social and economic values.

The invention discloses an application of ganoderma lucidum spore oil in preparation of a medicine or health food for improving sarcopenia. Ganoderma lucidum spore oil can effectively improve weight loss and muscle hypofunction induced by glucocorticoid, and improve the holding power and exercise tolerance level of the body; meanwhile, the skeletal muscle mass and the muscle fiber cross sectional area can be increased, and the skeletal muscle tissue morphological structure is improved; in addition, the ganoderma lucidum spore oil can improve the oxidation resistance of the body and skeletal muscle and reduce the oxidative stress level, so that the skeletal muscle injury related to aging is relieved on the whole. Therefore, the ganoderma lucidum spore oil has a definite application value in the aspect of improving the skeletal muscle function.

The invention relates to a probiotic preparation containing a BL11 strain and capable of improving obesity-related metabolism and senescence indexes of middle-aged and elderly people and application of the probiotic preparation. The strain in the probiotic preparation is composed of a bifidobacterium longum subsp. Longum BL11 strain and a pediococcus acidilactici PA53 strain. The two strains can cooperate with each other and promote each other, and have a synergistic effect in the aspect of improving obesity-related metabolic indexes, which is specifically embodied in that: the weight increase and body fat rate of mice fed with high fat diet can be reduced; the low-density lipoprotein level, the total cholesterol level and the triglyceride level are reduced, and the high-density lipoprotein level is improved; fasting blood-glucose, glycosylated hemoglobin level and insulin resistance index are reduced; chronic inflammation is relieved; meanwhile, the composition also has excellent performance in the aspect of improving senescence-related indexes, the content of malondialdehyde in serum can be reduced, the activity of superoxide dismutase and glutathione peroxidase can be improved, and the activity of telomerase can be improved.

The invention belongs to the technical field of intelligent feeding for cow breeding, and discloses a cow feed proportioning optimization method based on artificial intelligence. Body weight, movement, heart rate, temperature and humidity and feed component sensors are arranged in dairy cow individuals and a breeding environment, physiological data and environmental data are collected, and the physiological data and the environmental data are transmitted to edge computing equipment and a cloud platform through a wireless network to be preprocessed and stored. And the artificial intelligence analysis module is used for generating a personalized feed formula of each cow based on a machine learning and / or deep learning model in combination with an optimized objective function, and carrying out environmental adaptability adjustment according to temperature, humidity and feed component changes. The system controls the automatic feeding equipment to perform quantitative feeding according to the heads, and utilizes feedback data of milk amount, body weight and exercise amount to update health state indexes and continuously correct feed proportion. On the premise of meeting individual nutritional requirements of dairy cows, the feed utilization rate and the production performance are improved, the feed cost and the disease risk are reduced, and the feed is suitable for fine management of large-scale pastures.

The present invention relates to the use of petrelintide to reduce body fat or inhibit gain of body fat whilst preserving lean mass.

The invention relates to the technical field of health assessment, in particular to an orthopedic rehabilitation process real-time monitoring and assessment method, which comprises the following steps of: based on gait biomechanical parameters, identifying feature points, optimizing nodes in combination with body weight, stride frequency and stride change, extracting node correction parameter groups, analyzing muscle force change of knee joints and ankle joints, and evaluating the rehabilitation process of the orthopedics department. And combining the gait stability and the joint movement to obtain a correlation index proportion sequence. Parameters such as stride frequency, stride and body weight are combined with automatic recognition of feature points in a gait cycle, the time sequence sensitivity and individual adaptability of data are enhanced by dynamically correcting a feature point judgment standard, muscle force recovery and gait stability indexes are synchronously integrated and quantified in different stages, and the accuracy and the accuracy of gait recognition are improved. The linkage relation between the indexes can be adjusted according to real-time data, accurate tracking of a function recovery path is further supported, and the rehabilitation progress can be reflected by a dynamic structure of multi-dimensional parameters.