71 results about "Activity level" patented technology

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.

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.

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.

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.

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.

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.

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.

A notification device 200 comprises: a storage unit 210, which stores first information in which a first range of activity levels in a case where a worker is in one state is associated with a second range of heart rates in a case where the worker is in the first state; a sensing unit 221, which senses the worker's activity level per unit of time during work and the worker's heart rate per unit of time during work; and a notification control unit 222, which reports second information relating to the first state when the sensed activity level is within the first range and the sensed heart rate is within the second range.

A system for treating disordered breathing of a human being includes an implantable transvenous stimulation lead having at least one stimulation electrode and a sensor configured to detect activity level of the human being. The system includes an energy source, a pulse generator and circuitry, the circuitry operative to receive a signal indicative of the activity level of the human being from the sensor, wherein the circuitry is configured to cause the energy source and the pulse generator to deliver spaced apart stimulation signals to the at least one stimulation electrode while the activity level of the human being is sufficiently low to be indicative of sleep. Spaced apart stimulation pulses from the electrode are configured to extend a duration of a time of at least one breath being defined as the time from an onset of inhalation to the onset of inhalation of a successive breath.

Activity level and fall detection using accelerometer data is described. In one or more implementations, measurements of a user generated by a wearable monitoring device during an observation period are obtained, the measurements including accelerometer data. Physical steps taken by the user are detected based on peaks in the accelerometer data above a threshold, and a step count is generated based on the detected physical steps within predetermined time epochs. Activity level classifications of the user for the predetermined time epochs are generated based on the step count. The step count and the activity level classification for the predetermined time epochs may then be output, such as a notification or in a user interface. Fall predictions may be generated and output by processing the accelerometer data using machine learning models trained to correlate patterns in accelerometer data to fall events.

The present disclosure relates to a method, device, and program for providing a service to determine the activity level of a disease on the basis of responses to question information designed to evaluate the activity level of a disease that a user possesses, thereby allowing for quick intervention by a doctor according to the determined activity level. The method includes: collecting symptom information for various diseases; generating multiple pieces of question information and a list of answers for evaluating the activity level for each of the various diseases on the basis of the collected symptom information; acquiring information about the disease that a user possesses; providing the user with question information and an answer list corresponding to the disease that the user possesses; and determining the activity level of the disease that the user possesses on the basis of the answers to the question information obtained from the user.

The invention relates to the technical field of anorexia risk prediction, and discloses an anorexia risk prediction system based on multi-modal data, which comprises a multi-dimensional monitoring module and an intelligent evaluation module. According to the system, health management data and daily life management data of all individuals are obtained through a multi-dimensional monitoring module and are classified to form a data set, and an intelligent evaluation module evaluates the actual energy demand required by the individuals for maintaining the current body weight, generates basic energy consumption, evaluates the individual physical activity level coefficient, generates an energy intake gap, and obtains the health management data and the daily life management data. Metabolic characteristics of different ages, genders and groups are fully considered, the multi-dimensional assessment precision is high, the intelligent assessment module sets a fixed monitoring period, dynamically tracks the change trend of health key indexes, accurately quantifies and assesses the health injury degree of an individual caused by anorexia behaviors, generates injury indexes, quantifies risk levels, and improves the assessment accuracy. Intendencies of individuals to different anorexia subtypes are distinguished, corresponding early warning signals and feeding suggestions are output, and grading early warning screening efficiency is high.

The invention provides an infant feeding demand assessment method and device. The method comprises the following steps: acquiring basic physiological information, activity data and nutrition intake information of a to-be-assessed infant; the obtained basic physiological information, activity data and nutrition intake information are input into an energy consumption model, and the energy consumption model determines the basal metabolic rate of the infant based on the weight and gender information and determines the exercise consumption of the infant based on the heart rate, the activity level, the body temperature, the weight and the non-eating duration; total consumed energy of the infant is determined based on the basal metabolic rate and the exercise consumption; the current total intake energy of the infant is obtained through the energy intake model; and inputting the acquired basic physiological information, nutrition intake information, total consumed energy and current intake total energy into a feeding demand evaluation model to obtain a feeding demand evaluation result of the to-be-evaluated infant. According to the invention, real-time feeding demand evaluation and personalized evaluation of infants can be realized, and the accuracy of feeding suggestions is improved.

The integration of exercise and gaming is a growing trend, as evidenced by the popularity of interactive and virtual reality games that encourage physical activity. Existing systems often confine the user to a specific location or type of exercise equipment or user device and fail to extend the interactive experience to other environments in a cohesive manner. Various aspects of the present disclosure provide a gaming environment in which a user can experience different aspects of the environment based on the context via which the user is accessing the environment. The system may, for example, uniquely adapts game play to the context of the user's activity level and environment to enhance engagement and promote physical health without distracting from the primary activity or creating unsafe conditions for the user. Other embodiments may provide integration with physical exercise hardware to substantially eliminate spoofing and other cheating that plague some mobile games.

The invention discloses a system for monitoring and guiding early-stage activities of critically ill patients. The system for monitoring and guiding the early-stage activity of the critically ill patient comprises an intelligent bracelet worn on an arm of the patient and used for monitoring physical sign data of the patient in real time, and a wearable virtual reality device used for establishing communication with the intelligent bracelet; the wearable virtual reality device comprises a storage module used for storing information adaptive to the early activity level of a patient, a display module used for displaying early activity level guiding scene information, and a processing module used for recording the time, the completion standard degree, the completion speed and the completion speed of the patient completing a corresponding early activity level action instruction. And the control module is used for comparing the difference between the actually measured evaluation index and each preset index, and monitoring and guiding the action posture of the early activity of the patient. Through the system, the labor intensity of medical staff is greatly reduced, and the requirements of modern medical services are met.

Methods, systems, and devices for evaluating a user's metabolic balance are described. A system may include a wearable device and a glucose monitoring device. The system may acquire physiological data from the wearable device, and blood glucose data from the glucose monitoring device. The system may be configured to determine physiological characteristics of the user based on the physiological data, such characteristics associated with a sleep quality of the user, a stress level of the user, an activity level of the user, a recovery of the user, or any combination thereof. Similarly, the system may identify metabolic characteristics of the user, such as changes in the user's blood glucose data. By overlaying and comparing the physiological data and the blood glucose data, the system may be able to evaluate how the user's physiological characteristics affect or impact the user's metabolic characteristics, or vice versa.

A method for monitoring hydration of a living body of a user includes: obtaining an individual physiological data of the user; obtaining a sensor data associated with the living body of the user; determining, based on the sensor data, an estimated net amount of water intake of the living body and an estimated physical activity level of the living body; calculating daily water requirements for the living body based on the individual physiological data and the estimated physical activity level; comparing the calculated daily water requirements for the living body with the estimated net amount of the water intake of the living body; and providing at least one individual recommendation based on a result of the comparing, the at least one individual recommendation being associated with a recommended amount of water for the user to take.

A reinforcement learning process with self attention is used for insulin dosing decisions in an automated medical system. The State-Action-Reward-Next State (SARS) sequence is used. The state represents the current condition, including recent continuous glucose monitoring readings, insulin doses, meal information, and potentially other relevant factors like time of day or physical activity levels. Based on this state, the agent takes an action by deciding on an insulin dose. It then receives a reward, a numerical value quantifying the quality of the action, based on resulting glucose levels and their proximity to the target range. This leads to a new state, and the process repeats. Through this iterative process, the algorithm updates the neural network weights, allowing the agent to learn which actions lead to better outcomes in different states.

This application provides a control method, device, processor, and air conditioning system for an air conditioner. The method includes: upon receiving an activation command, acquiring environmental information and human body information. The environmental information includes indoor temperature information and air conditioner operating mode information. The human body information includes the human body temperature, activity level, and location information of a target object within a predetermined space. The predetermined space is the space where the air conditioner is located, the indoor temperature is the temperature within the predetermined space, and the operating mode is either heating mode or cooling mode. Based on the human body information, determining the human comfort temperature corresponding to the target object; and based on the human comfort temperature, operating mode, location information, and indoor temperature, controlling the air conditioner to activate and adjusting the air conditioner's airflow direction, wherein the airflow direction is either away from or towards the target object. This application solves the problem in the prior art where the air conditioner requires manual adjustment of the airflow direction when first turned on, resulting in a low degree of automation.

The present invention relates to a system and a method for evaluating motion imitation. According to an embodiment of the present invention, a user's motion performance accuracy is evaluated in real time and the result is converted into a score and provided to the user, thereby promoting motivation for motion performance and improving physical activity. In addition, according to the present invention, a user's motion performance state can be more accurately and quickly analyzed on the basis of image analysis and joint coordinate extraction technology, thereby stably evaluating a motion regardless of physical conditions and motion environments of various users such as seniors and infants.

The application discloses an activity level evaluation method, system and device and electronic equipment. The method comprises the following steps: receiving video data and artificial scoring data of a target object in an activity process; extracting activity features in the video data through an activity analysis model, and analyzing the activity features and the artificial scoring data to obtain an analysis result, wherein the model weight of the activity analysis model is determined according to a first weight and a second weight, the first weight is used to represent the influence degree of the activity features on the activity level of the target object in the activity category, and the second weight is used to represent the influence degree of the activity category of the activity features on the activity level of the target object; and generating an activity level evaluation report of the target object according to the analysis result. The application solves the technical problem of low evaluation accuracy in the field of computer vision analysis, because the user activity level evaluation method in the related art is highly subjective and difficult to be applied on a large scale.

The invention relates to an activity amount detection method and device, electronic equipment and a medium. The activity amount detection method comprises the following steps: acquiring multiple pieces of motion information of a user, wherein parameters corresponding to the motion information are different; determining a plurality of exercise intensities according to the exercise information; and determining the current activity amount according to each exercise intensity. The current activity amount of the user is determined according to the motion information of the multiple dimensions, the problems that part of the motion information is inaccurate and the motion intensity of part of the dimensions cannot reflect the motion condition of the user are avoided, and therefore the accuracy of activity amount detection is improved.

The invention provides a method for acquiring a maximum heart rate, which is applied to first electronic equipment and comprises the following steps: judging that a motion record exists in the first electronic equipment, the motion record comprises data recorded in a process of performing at least one type of motion, judging that various types of data are updated at least once in a first duration, and if the data are updated at least once in the first duration, determining that the data are updated at least once in the first duration. The multiple types of data comprise the physical activity level, the maximum oxygen uptake and the resting heart rate, the physical activity level represents the strength of physical strength consumed within the second duration, and the first maximum heart rate is obtained based on the multiple types of data and a preset model. The maximum heart rate obtained based on various types of data has higher accuracy.

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

Systems and methods are provided for delivering closed-loop or partially closed-loop baroreflex activation therapy (BAT) to treat conditions associated with autonomic dysfunction. A pulse generator delivers stimulation while physiological data, such as ECG, heart rate variability, bioimpedance, and physical activity levels, is collected from one or more sensors. The data is analyzed to assess autonomic nervous system activity, and stimulation parameters are dynamically adjusted in response. In some embodiments, adjustments are made on a beat-to-beat basis using ECG input. Artificial intelligence algorithms may be used to predict patient-specific responses, optimize therapy, and evaluate effectiveness. The method may further include integrating patient-reported symptoms, wirelessly transmitting data, or adjusting stimulation duty cycle based on time of day. The system may further incorporate patient-reported symptoms, a clinician dashboard for remote monitoring, and a multi-channel lead. Stimulation may be delivered non-invasively or via an implantable device.

The application provides a product carbon footprint accounting method and device, relates to the technical field of carbon footprint accounting, and comprises the following steps: establishing a full life cycle carbon footprint accounting model of a product to be accounted based on the production process characteristics of the product; collecting activity level data of the product to be accounted at each stage of the full life cycle according to a pre-generated activity level data collection template; and performing carbon footprint accounting on the product to be accounted according to the activity level data, the full life cycle carbon footprint accounting model and a pre-constructed factor database. The product carbon footprint accounting method and device provided by the application effectively reduce the difficulty of carbon footprint accounting and shorten the accounting time, improve the completeness and accuracy of the activity level data, and thus realize efficient and accurate accounting of the full life cycle carbon footprint of power equipment.

Described herein are apparatuses and methods for classifying a patient as being asleep or awake. Such an apparatus can include an accelerometer and a processor. The accelerometer, alone or in combination with the processor, is used to determine an activity level of the patient and a posture of the patient. The processor is configured to classify the patient as being asleep in response to both (i) the posture of the patient being recumbent or reclined for at least a sleep latency duration, and (ii) the activity level of the patient not exceeding an activity threshold for at least the sleep latency duration; and classify the patient as being awake in response to at least one of (iii) the posture of the patient being upright for at least an awake latency duration, or (iv) the activity level of the patient exceeding the activity threshold for at least the awake latency duration.

Methods, systems, and devices for evaluating a user's metabolic balance are described. A system may include a wearable device and a glucose monitoring device. The system may acquire physiological data from the wearable device, and blood glucose data from the glucose monitoring device. The system may be configured to determine physiological characteristics of the user based on the physiological data, such characteristics associated with a sleep quality of the user, a stress level of the user, an activity level of the user, a recovery of the user, or any combination thereof. Similarly, the system may identify metabolic characteristics of the user, such as changes in the user's blood glucose data. By overlaying and comparing the physiological data and the blood glucose data, the system may be able to evaluate how the user's physiological characteristics affect or impact the user's metabolic characteristics, or vice versa.