137 results about "Activity level" patented technology

The invention belongs to the technical field of livestock feeding management, and particularly relates to a livestock breeding feeding precise management method and system based on an AI technology. A fixed feeding mode based on a growth stage and a self-adaptive dynamic correction algorithm based on environment deviation and activity fluctuation are fused; a multi-dimensional data-driven feeding amount decision model is constructed, dependence of a single parameter is broken through, accurate feeding can be performed according to real-time monitoring data by adopting a self-adaptive feeding mode when the environment or activity amount fluctuates and deviates, the nutritional requirements of livestock are better met, and the feeding efficiency is improved. When data acquisition is abnormal or the environment and activity amount are stable and appropriate, a fixed feeding mode is adopted, and the fixed feeding mode can be periodically updated according to a self-adaptive feeding mode, so that the feeding accuracy and efficiency are improved, the feed waste is reduced, the stability of feed feeding is guaranteed, and the feeding efficiency is improved. And the feeding effect can be brought into an optimal state.

To provide a system that includes: means that proposes recipes that take into consideration allergies, food preferences, and activity levels of a child, gets information about special offers at nearby supermarkets, and proposes recipes that use affordable and seasonal ingredients; and means that accumulates images of food ingredient lists, when allergic symptoms appear, AI will suggest which ingredients are suspected.SOLUTION: The system includes: means for proposing recipes that take into account allergies, food preferences, and physical activity levels of a child; means of getting information about special offers at nearby supermarkets, and means of proposing recipes that use affordable and seasonal ingredients; and means that accumulates images of the ingredients of foods consumed, and when allergic symptoms appear, AI suggests which ingredients are suspected.SELECTED DRAWING: Figure 1

Neurophysiologic assessment system includes an ingestion data hub for generating clean data from heart rhythm data, a neuroscience processing unit for generating primary metrics from the clean data, a contextual analysis unit for receiving and analyzing external contextual data, a behavior analysis unit for generating secondary metrics from the clean data, primary metrics, and external contextual data, and a workflow management unit for controlling the ingestion data hub, and neuroscience processing, contextual analysis, and behavior analysis units. Secondary metrics include at least one of emotional wellbeing, energy, mood, and peak immersion value for a given time frame. The external contextual data include at least one of location, proximity of related persons, time of day, day of a week, weather conditions, traffic conditions, measured activity levels, calendar events, biofeedback, survey results and information provided by the participant, tracked usage of software applications, engagement with social media, and sleep patterns.

The invention discloses a live broadcast switching method and system based on AI face recognition, and the method specifically comprises the steps: obtaining the video stream data of a plurality of cameras in a live broadcast image, and extracting the character feature information in the video stream data of each camera; based on the character feature information, determining the activeness of each character in the live broadcast picture, and determining a plurality of key characters from the plurality of characters by comparing the activeness of each character with an activeness threshold; obtaining audience interaction data of the live broadcasting room, and determining the attention degree of each key person according to the audience interaction data; determining a priority sequence of each key person according to the attention, and determining optimal shooting angle information according to the priority sequence; and based on the optimal shooting angle information, dynamically selecting the video stream data of the optimal camera position as a target live broadcast picture and outputting the target live broadcast picture. According to the invention, the accuracy and real-time performance of live broadcast picture switching are improved, and the personalization and interactivity of live broadcast contents are enhanced.

The invention relates to the technical field of communication terminal control, and particularly provides a communication terminal control method, which comprises the following steps: in response to a remote control mode, initializing a grid map of a current area; acquiring human body track data in the current area in a first preset time period; determining track grid map information based on the grid map and the human body track data; determining the activeness of the current user based on the track grid map information; and based on the activity degree of the current user, the temperature of the air conditioner is controlled, and therefore the limitation of fixed temperature setting of a traditional air conditioner is broken through, intelligent matching of temperature adjustment and the real-time state of the human body is achieved, and the temperature control precision and the use comfort are remarkably improved.

An air conditioner and a method for operating an air conditioner are provided. The air conditioner may include a case having a space formed therein and an open bottom; a panel disposed under the case and having an inlet and a plurality of outlets disposed around a circumference of the inlet; a fan disposed in the case and configured to generate an airflow from the inlet to the plurality of outlets; an airflow direction controller disposed at the plurality of outlets and configured to control an airflow direction of air flowing through the plurality of outlets in a plurality of directions; a camera disposed at one side of the panel and directed toward an indoor space; and a controller configured to control the airflow direction controller based on images corresponding to the indoor space and captured by the camera. The controller may be configured to determine an activity level of an occupant for each of a plurality of areas of the indoor space based on a plurality of images corresponding to the indoor space; determine a direction of air discharged from the plurality of outlets based on the determined activity level; and control the airflow direction controller according to the direction of the air which is determined for the plurality of outlets.

The invention relates to the technical field of medical information, and particularly discloses a heart disease rehabilitation follow-up visit data management system and method based on data tracking, and the system collects health state data and activity level data of a patient, analyzes the data, and calculates a heart rate fluctuation index and a blood pressure fluctuation index; the heart rate and the blood pressure stability of the patient are evaluated; the activity time ratio of each patient is calculated, and a fitness score is calculated through a comprehensive formula and used for judging whether the health state of the patient is suitable for the current activity level or not; according to the fitness score, the patients are classified into two types of suitable activities and non-suitable activities; for patients suitable for activities, the system suggests to maintain the current activity level and properly reduces the monitoring frequency; for patients not suitable for activities, the monitoring frequency is enhanced, and rehabilitation ability scores are obtained through comprehensive analysis; finally, according to comparison of the rehabilitation ability score and a preset threshold value, whether a treatment scheme needs to be adjusted or not is determined.

Management of a diabetic condition may be performed by detecting a mealtime and / or an increased level of activity associated with a user. The mealtime is detected based one or more mealtime indicators that may indicate a likelihood of an occurrence of a mealtime. Each mealtime indicator provides additional context around the likelihood of a mealtime. To assist in managing the diabetic condition, a user's elevated activity levels may be detected. The activity level of a user is detected based on one or more activity indicators. Each activity indicator provides additional context around the likelihood of an increased level of activity by the user. Management of the diabetic condition may be performed proximate a mealtime or a user exercising to increase the efficacy of management of the diabetic condition.

Techniques provided herein employ a mesh network of wireless communication-enabled devices to monitor activity in a geographical area, such as a neighborhood or a parking lot. To this end, the mesh network monitoring system collects data about the devices found in the mesh network and establishes an expected activity level, which is used as a reference for comparing and classifying a current activity level. If the current activity level deviates significantly from the expected activity level, it may be classified as an unusual event. Upon detecting an unusual event, the mesh monitoring network may output a notification sent to the users of the devices in the mesh network. The mesh network monitoring system may help drivers determine availability of parking spots on a parking lot.

Systems and techniques are provided for detecting drowsiness of a driver in a vehicle. In aspects, a driver is monitored by capturing an image sequence of an interior of the vehicle via a camera system. The image sequence is then analyzed to extract a characteristic pattern of the driver. An activity level of the driver is determined based on at least one of the image sequence or an output signal provided by another sensor of the vehicle. At least one of the extracted characteristic pattern and the activity level of the driver is selected as a basis for determining a drowsiness signal indicative of the drowsiness of the driver.

The invention relates to the technical field of electroencephalogram characteristic index calculation, and discloses a chronic pain electroencephalogram index calculation algorithm, which comprises a data preprocessing stage, a multi-layer perceptron architecture design, a model training stage, a model evaluation stage and a multi-scale information fusion stage. The data preprocessing stage further comprises normalization and data division; the architecture design of the multi-layer sensor comprises an input layer, a hidden layer and an output layer; the model training stage comprises a loss function and optimization algorithm, forward propagation, loss calculation, back propagation and parameter updating one-set repeated training; in the model evaluation stage, evaluation needs to be carried out on a test set, and hyper-parameters are adjusted. According to the method, the connection strength or the activity level of different regions of the brain under different threshold values is reflected, the association between the brain nerve activity and the chronic pain can be described more comprehensively by fusing the connection strength or the activity level, the pain related mode hidden in the association can be mined, the limitation of single feature analysis is avoided, and comprehensive evaluation of the chronic pain is facilitated.

To provide a method for analyzing coagulation characteristics of a blood specimen. To provide a method for analyzing a blood specimen, including: acquiring a waveform related to a coagulation rate or coagulation acceleration of a sample obtained by mixing a subject blood specimen with a reagent for measuring coagulation time; extracting multiple parameters characterizing the waveform related to a coagulation rate or a coagulation acceleration; and determining an activity level or activity abnormality of a coagulation factor in the subject blood specimen on the basis of the multiple parameters.

The invention provides a sleep detection method, a related device and a communication system. According to the method, the sleep time of the user is determined by combining data obtained through various types of detection such as heart rate detection, activity amount statistics, bed-getting-on action detection, walking feature detection, ambient light detection, ambient sound detection and use condition detection of electronic equipment such as a mobile phone and / or a tablet computer, and the sleep time detection accuracy is improved. In addition, the method also combines heart rate data, activity data, and walking characteristics and action characteristics of getting on and off the bed to determine the time of getting on and off the bed of the user.

A force sensing system for determining if a user input has occurred, the system comprising: an input channel, to receive an input from at least one force sensor; an activity detection stage, to monitor an activity level of the input from the at least one force sensor and, responsive to an activity level which may be indicative of a user input being reached, to generate an indication that an activity has occurred at the force sensor; and an event detection stage to receive said indication, and to determine if a user input has occurred based on the received input from the at least one force sensor.

The invention provides an activity level evaluation system and method based on a flexible micro-fluidic sensor, the system comprises the flexible micro-fluidic sensor, an environment sensor, a power supply module, a signal conditioning circuit, a micro-control unit, a Bluetooth module and a display module, and the method comprises the following steps: preparing the flexible micro-fluidic sensor; and calibrating the flexible micro-fluidic sensor, assembling the activity level evaluation system based on the flexible micro-fluidic sensor, and evaluating the activity level. Human or animal physiological parameter data are obtained through an advanced flexible microfluidic sensing technology, environmental parameter data obtained by combining an environmental sensor are processed by a microcontroller to obtain a vitality level comprehensive value M, and a vitality level result is displayed, so that the convenience and comfort of detection are improved, and the detection accuracy is improved. And accurate evaluation of the activity level of human or animals is realized.

Systems and methods are disclosed to an ambulatory medical device. The ambulatory medical device comprising an activity sensor configured to produce an activity signal representative of activity level of a patient, a heart sound sensor configured to produce a heart sound signal, and a control circuit. The control circuit is configured to detect a change in activity level of the patient using the activity signal, enable monitoring of the heart sound signal in response to detecting the change in activity level, measure intensity of an S3 heart sound in the heart sound signal, and produce an indication of pulmonary hypertension (PH) when the measured intensity of the S3 heart sound exceeds a PH detection threshold intensity.

The invention provides an activity level evaluation method and related equipment, and belongs to the technical field of terminals. The method comprises the following steps: screening a first heart rate of a user under low activity intensity and a second heart rate of the user under medium and high activity intensity according to walking heart rates in heart rate data of the user in the past one week; acquiring a weekly activity level assessment result of the user according to the first heart rate and the second heart rate by using an activity level assessment hierarchical model, the activity level assessment hierarchical model including a first activity level assessment model corresponding to low activity intensity and a second activity level assessment model corresponding to medium and high activity intensity, the activity acquisition module is used for acquiring the corresponding activity amount according to the heart rate, and the unit of the activity amount is Meide MET multiplied by time. According to the method, an activity level analysis result of a user is obtained by taking weekly activity data as an analysis unit through a personalized hierarchical model, so that the problem that an activity level evaluation result cannot be in butt joint with an international standard and is inaccurate is solved.

A system includes a processor that collects data representing activity levels, sleep patterns, and food intake from an information collection device attached to a dog, transmits the collected data to an analysis server, wherein the analysis server inputs the collected data into a generative artificial intelligence model and analyzes the data, transmits analysis results to a terminal and notifies a user, receives user input regarding questions or symptoms of the dog and generates advice using the generative artificial intelligence model, transmits the generated advice to the terminal for display to the user, and provides online consultation reservation with a veterinarian.

The invention provides a method and system capable of adjusting an exercise prescription in real time for a metabolic disease group, and the method comprises the following steps: obtaining the body data of a user, and determining the exercise risk level of the user through a metabolic disease risk assessment model according to the body data of the user; acquiring activity data of the user, and performing quantitative analysis according to the activity data of the user to obtain a physical activity level score of the user; obtaining function data of the user, and determining the motor function level of the user according to the function data of the user; matching an exercise prescription for the user according to the exercise risk level, the physical activity level score and the exercise function level of the user; monitoring data of the user in the exercise process according to the exercise prescription are obtained, and the exercise prescription of the user is adjusted according to the adjustment rule base. The corresponding exercise prescription is formulated according to the actual situation of the user, so that the formulated exercise prescription is more suitable for the user, the adjustment mechanism of the exercise prescription is perfected, and the actual body change of the user in the exercise process is accurately adapted.

A method and system for guiding joint replacement procedures based on functional stability analysis of a joint. The method comprises communicatively connecting to a plurality of sensors worn by an individual at muscles in a joint area and performing an initial measurement that evaluates strength and activity level of the muscles. The initial measurement includes a recording of data values from the plurality of sensors during a preoperative testing procedure. The initial measurement is compared with reference data, wherein the reference data includes measurements of healthy people with normal muscle function. The method further comprises generating joint replacement recommendations based on the comparison.

A motion detector that can automatically adjust a dwell time used by the motion detector to prevent unnecessary transmissions as an activity level of an area increases or decreases. The motion detector determines the activity level in the area and if the activity level is increasing, the dwell time is reduced and vice-versa.

A device includes a memory and processing circuitry coupled to the memory and configured to: receive, from a medical monitoring device, a set of one or more patient parameters; determine an exercise tolerance level based on the set of one or more patient parameters and based on at least one comorbidity of the patient; determine that a present activity level for the patient exceeds the exercise tolerance level for the patient; and send a notification to the patient in response to determining that the present activity level exceeds the exercise tolerance level for the patient.

This invention relates to the field of environmental data processing technology, specifically disclosing a closed-loop management method for carbon footprint data quality control and evaluation. It includes: loading product category rules for accounting logic verification; performing integrity checks, anomaly detection, and physical balance verification on activity level data; performing multi-dimensional quantitative scoring on emission factor data based on time, geography, technology, and source characteristics; calculating the proportion of primary activity level data in real time and adjusting the entry threshold for emission factor data; calculating the data quality score for dimensions and the overall product, and performing tiered feedback based on the data quality score and carbon footprint contribution weight to trigger data optimization. This invention solves the problems of idle primary activity level data proportion indicators and lack of traceability in quality evaluation in existing technologies by integrating methodological logic, data cleaning, dynamic threshold adjustment, and recursive quality evaluation into a closed-loop architecture, thus achieving proactive control and continuous improvement of carbon footprint data quality.

This invention provides a method for predicting individual mortality rates based on activity data from wearable devices, comprising the following steps: acquiring multi-source characteristic data of the target individual, wherein the multi-source characteristic data includes at least activity data and baseline characteristic data, the activity data being collected by the wearable device worn by the target individual over a continuous monitoring period, and the baseline characteristic data including at least one of demographic characteristics, health characteristics, living environment characteristics, and lifestyle characteristics; processing the activity data to calculate an average activity data feature value representing the overall activity level of the target individual; inputting the average activity data feature value and the baseline characteristic data together into a trained nonlinear machine learning prediction model, and the prediction model outputting a predicted mortality risk value for the target individual within a preset future time window. This invention integrates the average activity data feature value with traditional baseline characteristic data, enabling risk assessment to be updated synchronously with an individual's daily activity level.

The invention belongs to the field of artificial intelligence and big data, and relates to an activity level quality evaluation method, which comprises the following steps: acquiring activity level data, and extracting data element information from the activity level data; inputting the data element information into a pre-trained activity quantity quality evaluation model to generate a target activity prediction score; comparing the target activity prediction score with a standard score; and based on a comparison result, generating a prediction judgment result of whether the target activity is successful or not. The invention further provides an activity level quality evaluation device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and a factor index list and / or a pre-trained activity level quality evaluation model and the like can be stored in a block chain. According to the method, the activity quality can be effectively evaluated.

An activity support apparatus supports an activity of a worker at a disaster site. The activity support apparatus comprises a vibration data acquisition unit that acquires vibration data of vibrations generated by the worker, an activity level estimation unit that estimates an activity level of the worker based on the vibration data acquired by the vibration data acquisition unit, and a notification unit that notifies the activity level estimated by the activity level estimation unit.

This health promotion device offers a simple and low-cost configuration that proposes health improvement plans tailored to the user's needs by improving their physical activity levels. [Solution] The system includes a systolic blood pressure receiving means 11 that receives the user's systolic blood pressure value, a vascular age calculation means 12 that calculates the vascular age corresponding to the systolic blood pressure value received by the systolic blood pressure receiving means 11 based on the correlation between the systolic blood pressure value and vascular age, and a health promotion proposal means 15 that proposes a health promotion plan by improving the amount of physical activity so that the vascular age calculated by the vascular age calculation means 12 is below a predetermined age.

Factors such as activity level and sensor positioning can lead to varying results for peak detection algorithms, causing false peaks or causing true peaks to be missed, affecting calculation of Inter-

Generally described, one or more aspects of the present application relate to enabling determination of a predicted surgical efficacy of a proposed surgical intervention and a predicted pattern of post-operative recovery for the patient. More specifically, the present disclosure provides a system that can analyze the patient data of a plurality of patients data, generate analytics data indicating the post-operative recovery of the plurality of patients, and store the analytics data in association with the biological traits of the patients and the types of surgical interventions that the patients had. Subsequently, the system can analyze the patient traits and activity data of a patient, and output, based on the previously generated analytics data, a prediction of how efficacious a given surgical intervention might be for that patient and / or how the patient might recover from the given surgical intervention.

The invention discloses a method for evaluating early activity of a critically ill patient. The method for evaluating the early activity of the critically ill patient comprises the following steps: acquiring sign data of the patient, analyzing the sign data of the patient, and matching a corresponding early activity level; recording related evaluation indexes such as time, completion standard degree, completion speed and error frequency when the patient completes the corresponding early activity level action instruction, comparing the difference between the actual evaluation index and each preset index, and correcting and guiding the action posture of the early activity of the patient; and collecting physical sign data of the patient after completing the action instruction of the corresponding early activity level, comparing the difference of the physical sign data of the patient before and after the early activity, and evaluating the influence on the physical condition of the critical patient after completing the corresponding early activity. By means of the evaluation method, multi-dimensional evaluation can be conducted on the execution efficiency of the early activity of the patient, the evaluation result is objective, and errors generated by manual evaluation are reduced.