15 results about "Body condition" patented technology

A method for predicting a cardiac index (CI) for a patient includes receiving a set of a measurements from the patient that characterizes an anatomical condition, a physical condition, a physiological condition, or a combination thereof. The method also includes receiving a non-invasive physiological measurement from the patient. The method also includes performing feature extraction on the non-invasive physiological measurement to produce one or more extracted features. The method also includes combining the set of measurements and the extracted features to produce a dataframe. The method also includes predicting the CI for the patient. The CI is predicted using a prediction model based upon the dataframe.

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 system according to this embodiment aims to monitor changes in physical condition or abnormalities during bathing in real time and to respond quickly. [Solution] The system according to the embodiment comprises a monitoring unit, a detection unit, a notification unit, and a safety measures unit. The monitoring unit monitors body temperature, heart rate, and movement. The detection unit detects abnormalities based on the data monitored by the monitoring unit. The notification unit sounds an alarm or wakes the user with vibration based on the abnormality detected by the detection unit. The safety measures unit automatically takes safety measures if the user does not respond to the notification unit.

The application discloses a body state monitoring method and a wristband type emergency monitoring ring, relates to the technical field of biological signal processing, and the body state monitoring method comprises the following steps: emitting red light of a preset first wavelength to the wrist part of a human body, collecting reflected light signals, obtaining a waveform physiological signal, determining a monitoring index of the human body, inputting the monitoring index into a warning model, obtaining a stress state probability of the human body, judging whether a warning is triggered or not based on the stress state probability and a preset probability threshold, and if the warning is triggered, issuing an alarm and sending corresponding body state data to a preset medical platform. The wristband type emergency monitoring ring can be worn on the wrist of a player to realize convenient detection, and through real-time monitoring of physiological data of the human body and a warning model, stress state detection and prediction are realized, so that the body state of the player can be monitored conveniently, in real time and accurately, and the effect of body monitoring of the player is improved.

Provided is a fecal gas analysis method for Bristol stool type classification and body condition analysis, and more particularly, to a fecal gas component ratio analysis method capable of classifying Bristol stool types and analyzing body conditions based on the component ratio of each fecal gas. The fecal gas component ratio analysis method for Bristol stool type classification and body condition analysis enables classification of Bristol stool types regardless of measurement time, subject, diet, age, or stool weight, and also allows identification of an individual's dietary habits. Therefore, the analysis method can be applied to personal health monitoring based on Bristol stool type classification.

A system is provided.SOLUTION: A system for managing a physical condition and an action of a dog, comprising: means for measuring an activity amount, a heart rate, and position information of an animal using a sensor; terminal means for receiving data acquired from the sensor; server means for analyzing the data received from the terminal means and evaluating a health condition of the animal; and means for notifying a user of an analysis result of the server means via the terminal means.SELECTED DRAWING: Figure 1

The invention provides a pathological multi-information comprehensive diagnosis device based on multi-agent cooperation, which comprises the following steps: acquiring update information corresponding to each specified information channel, distributing each update information to a corresponding agent for information storage in combination with a corresponding information attribute, generating an information map corresponding to each agent in a specified period, the information atlas is modified according to management content uploaded by doctors, a multi-agent platform of each doctor is constructed, when the doctors submit the patient information, relevant diagnosis information of the patient information is searched in the multi-agent platform, simulation diagnosis is conducted on the patient information through the relevant diagnosis information, and a plurality of physical conditions are obtained; meanwhile, the diagnosis effectiveness corresponding to each physical condition is determined and displayed, efficient integration of pathological information, personalized intelligent agent management, accurate query and diagnosis effectiveness quantification are achieved, and scientific and reliable pathological diagnosis auxiliary support is provided for doctors.

The invention discloses a wild animal ecological insight and behavior analysis method, electronic equipment and a storage medium, and the method comprises the steps: processing an obtained wild animal video stream, and obtaining a dynamic three-dimensional primitive sequence and a target contour image through dynamic primitive decomposition and anti-shielding restoration; biological characteristics are extracted and coded, and individual identity re-identification is realized through triple constraint; based on the three-dimensional primitive sequence and the identity label, driving a parameterized grid model to fit a posture through three-dimensional reconstruction, and quantifying a body size parameter and a body condition score; constructing a kinematic model based on the three-dimensional skeleton sequence, and analyzing and identifying motion abnormity through micro-motion slicing; based on body size parameters, body condition scores and abnormal results, physiological state deduction and spectral domain trend extraction are carried out, three-dimensional space interaction behaviors are analyzed, and multiple individual results are aggregated to evaluate population health risks. According to the invention, non-contact and automatic health monitoring of wild animal individuals is realized.

A personal monitoring system includes one or more passive biometric sensors and a communication device. A passive biometric sensor is operable to sense a body condition of a body in accordance with a sense signal at a sense frequency to produce sensed data of a body condition. The passive biometric sensor is further operable to transmit an e-field signal via the body regarding the sensed data, wherein the e-field signal is in accordance with an e-field transmit / receive frequency. The communication device is operable to receive the e-field signal via the body. The communication device is further operable to recover the sensed data from the received e-field signal.

1. The name of the design product: veterinary stethoscope. 2. The use of the design product: for assisting veterinarians to determine the physical condition of animals. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view 1.

The invention discloses a yak non-contact three-dimensional body condition phenotype data acquisition system and method, and belongs to the field of yak breeding. The system comprises a multi-sensor fusion module, a deep learning processing unit, a three-dimensional point cloud processing unit, an embedded edge computing device and a user interaction and management platform. Through a multi-sensor space registration and attitude adaptive correction mechanism, yak stress response caused by manual intervention is thoroughly eliminated. The system can complete millimeter-level three-dimensional reconstruction in a natural standing state of yaks, ensures that body size parameters reflect a real growth state, and provides a reliable basis for breeding screening. Modules of deep learning individual recognition, attitude filtering, point cloud reconstruction and the like are integrated, and end-to-end processing from data acquisition to body condition scoring is realized. The analysis time of a single yak is obviously shorter than that of a traditional method, the pasture operation efficiency is greatly improved, and the labor cost is reduced.

The invention discloses a cattle backfat thickness measurement and evaluation system and method. The system comprises a multi-mode body condition data acquisition module, a three-dimensional point cloud data generation module, a multi-mode body condition feature fusion network module, a three-dimensional point cloud backfat measurement and calculation model module, an intelligent cattle backfat monitoring cloud platform module and a cattle backfat thickness evaluation output module. The method comprises the following steps: acquiring multi-source body condition data through a multi-mode body condition data acquisition module, and acquiring three-dimensional point cloud data through a three-dimensional point cloud data generation module; the multi-mode body condition feature fusion network module processes multi-source data to generate fusion feature data, and the three-dimensional point cloud backfat measurement and calculation model module processes point cloud data to generate backfat feature data; the intelligent cattle fat monitoring cloud platform module integrates the two types of data to generate comprehensive analysis data; and the cattle backfat thickness evaluation output module calculates and outputs a backfat thickness result. According to the method, multi-source data cooperative processing is realized, the measurement accuracy and efficiency are improved, and the method is suitable for accurate evaluation of the cattle backfat thickness in a large-scale breeding scene.

The invention relates to the field of artificial intelligence and health management, in particular to a multi-modal health state assessment method fusing tongue image, heart rate and text, which takes the tongue coating condition as the main judgment basis, measures the heart rate of a user, and combines the body condition manually input by the user, the text information such as past medical history and the like to assess the health state of the user. A DeepSeek large model is used for giving a health state evaluation result, a user is assisted to effectively judge the physical condition of the user, in a tongue picture analysis module, YOLOv8 is used for positioning a tongue body area, and a ResNet18-Transform mixed architecture model is used for tongue coating classification; in the heart rate measurement module, a cascade classifier is used for carrying out face detection, and after it is determined that a user directly faces a camera, the heart rate is measured through an Euler video amplification algorithm; and in a suggestion generation module, a DeepSeek large model is guided through cue word engineering to analyze the multi-modal information, and a targeted health state evaluation result is generated.

One embodiment of the present disclosure provides a method for assessing the condition of the body by using a computer system, the method comprising: capturing, from multiple directions, static images of a subject in a standing posture; obtaining, through marker-less posture estimation, skeleton information about the body of the subject from the static images of the subject captured from the multiple directions; and assessing three-dimensional postures of multiple body sites of the subject on the basis of said skeleton information.

A system and method for calculating an estimate of a body condition score (BCS) for a bovine animal is described. The system comprises a visual spectrum camera configured to collect visual spectrum data of the animal in an area of interest, an infra-red camera configured to collect near infra-red spectrum data of the animal related to soft tissue distribution around the area of interest, and one or more neural networks trained using a first training dataset comprising combined imaging data for each of a plurality of animals and corresponding BCS's for the plurality of animals, in which the combined imaging data for each animal comprises the visual spectrum data and the near infra-red spectrum data for the animal. The system also includes a processor configured to: receive the combined imaging data for the animal and apply the one or more neural networks to the combined imaging data for the animal to calculate an estimate of a BCS for the animal.