342 results about "Health condition" patented technology

The invention discloses a precise numerical control machine tool operation state intelligent control method and system, and particularly relates to the technical field of numerical control machine tools. Multi-dimensional operation data, including working temperature, load, current, pressure, cutting force and tool wear data, of a machine tool are collected in real time, a Z-score algorithm is adopted for data preprocessing, abnormal values are extracted, a prediction model is constructed and trained based on a machine learning algorithm, abnormal data are analyzed in real time, and the abnormal values of the machine tool are analyzed in real time. And accurately identifying the operation state of the machine tool and evaluating the health condition. According to the health state evaluation result, an intelligent control strategy is automatically generated, and the feeding speed, the spindle rotating speed and the cutting depth of the machine tool are dynamically adjusted, so that the operation state of the machine tool is optimized, potential faults are found and dealt with in time, the machining quality is improved, the faults are reduced, the production efficiency and the equipment stability are improved, and the maintenance cost is reduced.

Camera and / or other sensor analysis of skin, used to diagnose and monitor health conditions. A computer, receiving skin data from a user, where the skin data is images and / or other data of the skin. The computer processes the skin data identify skin conditions, their status, and to compare the skin data with information indicative of health conditions that are not skin diseases. This can be done by finding similar skin data to other data received from other people who have specified health conditions and / or by looking for changes from previous images. The skin data can be captured by a smart phone camera (alone or with digital peripheral attachments) or a dedicated capture device such as a periscope, one way mirror, or cubicle. An augmented reality marking system can be used to mark areas on the user's skin to compare against other previous skin images and / or data.

The invention provides a hip joint impact syndrome intelligent diagnosis method, system and device based on multi-modal data fusion and a computer readable storage medium. The intelligent diagnosis method for the hip joint impact syndrome based on multi-modal data fusion comprises the following steps: acquiring a hip joint X-ray image and health condition text information of a patient; wherein the health condition text information comprises general information, medical history information, symptom information and physical examination information of the patient; inputting the hip joint X-ray image and the health condition text information into a preset hip joint impact syndrome diagnosis model, and outputting a hip joint impact syndrome diagnosis result; according to the hip joint impact syndrome diagnosis model, text features and image features are extracted and fused for diagnosis. According to the embodiment of the invention, the hip joint impingement syndrome can be diagnosed more accurately.

The invention provides a power module scheduling method, apparatus and device, and a storage medium. The method comprises the steps of obtaining one or more health parameters of each power module in a plurality of power modules of a charging pile; based on the one or more health parameters of each power module, determining a total health degree corresponding to each power module; determining a scheduling sequence of the plurality of power modules based on the total health degree of each power module; and scheduling the power modules to charge the target equipment according to the scheduling sequence of the plurality of power modules. According to the scheme, the total health degree of each power module determined based on the one or more health parameters of each power module can accurately reflect the health condition of the power module, so that the power modules are scheduled according to the scheduling sequence of the plurality of power modules determined based on the total health degree to charge the target equipment; the use of each power module can be balanced, and the service life of the charging pile is prolonged.

Camera and / or other sensor analysis of skin, used to diagnose and monitor health conditions. A computer, receiving skin data from a user, where the skin data is images and / or other data of the skin. The computer processes the skin data identify skin conditions, their status, and to compare the skin data with information indicative of health conditions that are not skin diseases. This can be done by finding similar skin data to other data received from other people who have specified health conditions and / or by looking for changes from previous images. The skin data can be captured by a smart phone camera (alone or with digital peripheral attachments) or a dedicated capture device such as a periscope, one way mirror, or cubicle. An augmented reality marking system can be used to mark areas on the user's skin to compare against other previous skin images and / or data.

The invention discloses a blood glucose management method, a user interface and a related device, and the method can determine a first meal time based on a historical blood glucose value of a user, and determine a second meal time based on one or more of the meal time input by the user, the limb movement of the user and the heart rate. Third meal time is determined based on the first meal time and the second meal time, and the blood glucose health condition of the user is evaluated according to the third meal time. Therefore, according to the method, the dining time of the user can be predicted in combination with the dining time, determined in various modes, of the user in the historical diet event, and the electronic equipment can evaluate the blood glucose condition of the user more accurately.

The invention discloses a GIS equipment expansion joint hidden danger intelligent detection system based on deep learning, and relates to the field of intelligent monitoring, and the system comprises an acquisition preprocessing module, a multi-modal data fusion module, a defect detection and classification module, an intelligent hidden danger evaluation module and an optimization feedback module. According to the invention, data of a plurality of sensors are combined, and the health condition of the equipment is comprehensively evaluated through a data fusion technology. The multi-source data fusion can effectively improve the accuracy of a fault detection model, avoids misjudgment caused by limitation of a single data source, and provides more comprehensive and accurate equipment health state evaluation. Through real-time monitoring and early warning, long-term health assessment can be carried out on the equipment, and serious faults of the equipment in the using process are avoided.

The invention relates to the technical field of health assessment, in particular to a traditional Chinese medicine health assessment method and system based on intelligent analysis, and the method comprises the steps: carrying out the multispectral image collection of the face and tongue picture of a user, carrying out the color gradation quantification processing and texture feature extraction of the obtained image data, and obtaining a face color gamut feature matrix and a tongue picture texture feature vector; and based on the tongue picture-complexion associated features and a syndrome description text input by the user, performing intelligent classification pre-judgment on traditional Chinese medicine syndrome types to obtain an initial syndrome label set, and based on user physique data, correcting the initial syndrome label set to obtain a syndrome feature fusion vector. Through the health fluctuation index and the health trend early warning signal, the change of the health condition of the user can be dynamically evaluated, and a personalized health intervention scheme is generated on the basis, so that the fluctuation of the health condition can be reflected in real time, intervention measures can be taken in time, and potential health risks can be prevented.

The disclosure relates to methods, compositions, and combinations for detoxification in a patient comprising performing therapeutic plasma exchange (TPE) on the patient. The disclosure also relates to methods, compositions, and combinations for removing toxins in a patient as a result of chronic exposure to the toxins, comprising performing one or more TPE sessions on the patient and administering an oral composition to the patient. The methods, compositions, and combinations of the disclosure may also be used to replenish biomarkers indicative of a healthy state of the body in order to improve immune system function or patient longevity, and / or reduce oxidative stress or inflammation. The methods, compositions, and combinations of the disclosure may also be used to reduce the level of atherosclerosis, improve cognitive function, prevent early cancer development, promote immune health, and / or treat health conditions or diseases such as autoimmune diseases, cancers, Alzheimer's disease, Parkinson's disease, chronic fatigue syndromes, or fibromyalgia. Additionally, the methods, compositions, and combinations of the disclosure may comprise an intravenous supplementation, wherein each TPE session is followed by administration to the patient of an IV composition. The disclosure further relates to oral compositions and IV compositions for use in the methods, compositions, and combinations of the disclosure.

A machine learning prediction system can analyze a dataset of users with self-reported symptoms and associated data from a wearable device to impact measure the impact of an acute health condition (such as the flu) at the population level. The machine learning prediction system can train a machine learning model to recognize individual acute health condition patterns based on differences in user activity with respect to the characteristics of determined baseline periods. For example, per-individual normalized change with respect to baseline aggregated at the population level can be used to determine individual acute health condition patterns and predict the onset of certain acute health conditions using a trained machine learning model. In response to predictions, the machine learning prediction system can take interventions to manage the impact of a predicted acute health condition on an individual.

The invention relates to the technical field of data processing, and discloses an operation and maintenance task processing intelligent distribution management system and method based on data analysis, and the system comprises a data collection module; a life cycle analysis module; a task plan making module; an operation and maintenance personnel task distribution module; and a path planning and dynamic adjusting module. Based on data analysis, in combination with the equipment operation state, the skill of the operation and maintenance personnel and the load condition, the execution sequence and route of the operation and maintenance tasks are optimized through intelligent allocation and route planning, task allocation and route can be dynamically adjusted according to the health condition of the equipment, the task priority and the real-time information of the operation and maintenance personnel, and the operation and maintenance efficiency is improved. The operation and maintenance task is efficiently and accurately completed, and the overall working efficiency and the resource utilization rate are improved.

The invention belongs to the technical field of sleep quality analysis, and particularly relates to a sleep quality analysis system and method based on a medical bed sensor, so as to solve the technical problem that an existing method excessively depends on duration statistics and neglects sleep continuity and periodic rhythmicity. The analysis method comprises the following steps: S1, acquiring sign signal data acquired by a sensor on a medical bed in a sleep cycle, and dividing the sign signal data into a plurality of continuous time slices; s2, extracting physiological indexes of respiratory rate, heart rate and body movement amplitude in each time slice, and calculating variation depth of the corresponding time slice; s3, generating a variation depth baseline; calculating an unsteady state disturbance factor according to the occurrence frequency and the duration of the micro-awakening disturbance fragment; and S4, generating a sleep quality comprehensive score. According to the analysis method, the comprehensiveness and objectivity of the evaluation result are improved, and the sleep health condition is reflected more truly.

The invention provides a fan tower drum deformation real-time monitoring and early warning system, method and equipment based on Internet of Things safety, and relates to the technical field of wind power generation. The system comprises a sensor module used for collecting deformation data of a fan tower, and the deformation data comprises strain data, inclination data, micro-strain data, vibration data, wind load spectrum and temperature and humidity parameters of distributed optical fibers; the data analysis and early warning module is used for inputting the standard deformation data into the deformation prediction model and outputting a deformation prediction value; inputting the standard deformation data into a health assessment unit to obtain a health score; and sending red early warning information under the condition that the variable quantity of the deformation predicted value within the target duration is greater than a first threshold value and / or the health score is less than a second threshold value. According to the method, composite early warning is carried out through the abnormal modes of the associated multiple parameters, and the health condition of the fan tower can be judged more accurately.

The embodiment of the invention discloses an ovarian health assessment method and related equipment, the method is applied to first electronic equipment, the first electronic equipment can display a first interface, and the first interface comprises a first control; receiving a first operation acting on the first control; acquiring first data, wherein the first data comprises heart rate variability data of the user in a preset time period; according to the physical sign data of the user, determining an ovary health assessment result; the user sign data comprises first data; the ovarian health assessment result is used for indicating the ovarian health condition of the user in a preset time period; after the preset time period, a second interface is displayed, and the display content of the second interface comprises the ovarian health assessment result. By adopting the method, the ovarian function abnormity of the user can be found in time.

The invention relates to the field of digital twin driving, and discloses an electric actuator energy consumption optimization method and system based on digital twin driving, and the method comprises the steps: collecting the current, torque, rotating speed, temperature, vibration and environment wind speed data of an electric actuator in real time, carrying out the online recognition of the thermal-friction coupling parameters of the actuator through a multi-scale sliding window method, and carrying out the online recognition of the thermal-friction coupling parameters of the actuator; the operation state of the actuator is dynamically updated in combination with the load damping change and the long-term health condition; the load evolution trajectory of the actuator is extracted, transient fluctuation and long-term degradation trend analysis are combined, and the energy consumption deviation and the performance bottleneck existing in the operation process of the actuator are recognized; according to the method, related actuator components and mutual influences thereof are comprehensively analyzed, parameters, feature weights and updating frequencies of the digital twin model are dynamically adjusted, and a real-time energy consumption optimization control strategy is generated. The method has the advantage that the real-time response capability and the long-term self-adaptive precision are improved.

The invention discloses a progressive dynamic pressure gradient bladder function regulation and control system and method, and aims to solve the problems of high infection rate, bladder injury risk, complicated operation, lack of dynamic pressure regulation and control and the like in the existing bladder management technology. According to the system, the urinary bladder internal pressure, the urine flow rate and the residual urine volume are monitored in real time through the urodynamic monitor, and the pressure gradient is dynamically adjusted according to the health condition of a patient. Progressive pressure training is adopted in the system, the bladder function is gradually enhanced, meanwhile, an emergency adjustment strategy is introduced, and the safety of a patient is ensured. In addition, the system also integrates machine learning and reinforcement learning algorithms, and realizes personalized treatment according to the treatment history and real-time feedback optimization adjustment strategy of the patient. The system has the advantages of precise regulation and control, personalized treatment, improvement of the comfort level of the patient and the like, and the bladder rehabilitation effect of the spinal cord injury patient is remarkably improved.

A data processing system is configured to identify treatment responsive to a health risk determined from feature data provided by one or more networked data sources. A classification engine generates a feature vector based on a natural language processing (NLP) of input data representing words provided by a user. Features of the feature vector represent health risk factors. Machine learning logic classifies the features to generate a classification metric indicating whether the features are indicative of health risks or not indicative of health risks. A prediction value is generated indicating a likelihood of each health risk factor for the patient. The patient can be diagnosed with a health condition or disease based on the identified health risks.

A method and a system assisting in monitoring the health condition of persons. A security body scanner is configured for a scan of a body of a person for security reasons with the further feature of comprising a communication component that is configured for providing health data of the person on the basis of the body scan.

The invention belongs to the technical field of traditional Chinese medicine health diagnosis and treatment, and particularly relates to a health data detection system, method and equipment based on traditional Chinese medicine diagnosis and treatment. According to the method, tongue image information, pulse condition information and complexion information of a patient are comprehensively collected, deep analysis and comprehensive evaluation are carried out in combination with modern science and technology means, the health condition of the patient can be reflected more accurately, the accuracy and comprehensiveness of traditional Chinese medicine diagnosis and treatment are improved, and in addition, the diagnosis and treatment accuracy of the patient is improved through trend evaluation and correlation analysis of abnormal causes. According to the method, the development trend of the health condition of the patient can be predicted, correlation analysis among different causes can be introduced according to the correlation degree and the processing priority of the abnormal causes, the cause processing strategy is further optimized, the health risk caused by improper cause processing is avoided, and the patient experience is improved. Therefore, a doctor can formulate a more accurate and effective treatment scheme, the means of traditional Chinese medicine diagnosis and treatment are enriched, and the objectivity and scientificity of traditional Chinese medicine diagnosis and treatment are improved.

The disclosure provides a method for providing telehealth services using touchless health vitals and artificial intelligence optimized assessment in real-time. The method includes obtaining real-time video and audio data of a user through a video capturing unit. Health vital signs data of the user are obtained from the real-time video and audio data using a touchless vital monitoring module. A real-time voice tone analysis is performed using a trained data model to identify a plurality of factors associated with the voice of the user and a health condition is determined based on comparing the plurality of factors with a predefined threshold associated with historic conversion data of the user. Health insights for the user are derived based on the health vital signs data and the health condition of the user. The health insights are used by the health care professional for further diagnosis and treatment for the user.

Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and / or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user's body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects.

The invention provides a control method for a pet washing and protecting machine and an intelligent pet washing and protecting machine, and the control method for the pet washing and protecting machine comprises the steps: determining a washing and protecting mode, a washing and protecting liquid formula and a drying mode which are matched with a target pet in combination with body parameters and health parameters of the target pet; according to the method, the target pet is cleaned and nursed, and adaptive adjustment is performed according to the emotion of the pet in the cleaning and nurse process, so that personalized and refined cleaning and drying requirements of different pets and pets under different health conditions and emotion conditions can be met, and the physical and psychological health of the pets is guaranteed while the cleaning and nurse effect is improved.

To provide a health condition estimation system for toilet users, which appropriately estimates health conditions of people.SOLUTION: In a health condition estimation system for toilet users disclosed herein, a condition estimation device comprises log information acquisition means (an acquisition unit) for acquiring a toilet log indicative of a usage status of a toilet apparatus, and condition estimation means (an estimation unit) for estimating a health condition of a toilet user based on the toilet log acquired by the log information acquisition means. The condition estimation means estimates an intestinal condition, including constipation or diarrhea, on the basis of a defecation record included in the toilet log.SELECTED DRAWING: Figure 4

Disclosed herein are methods, non-transitory computer readable media, systems, and kits for performing a multiple tiered analysis for identifying individuals with a health condition for monitoring, treating, and / or enrolling the individuals in a clinical trial. Specifically, the multiple tiered analysis involves a first screen, which eliminates a large proportion of individuals who are identified as not at risk for a health condition, and a subsequent second analysis which detects presence of a health condition in the remaining individuals. The second analysis includes an intra-individual analysis, which involves combining sequence information from target nucleic acids and reference nucleic acids obtained from the individual. The target nucleic acids include signatures that may be informative for determining presence or absence of the health condition and the reference nucleic acids include baseline biological signatures of the individual. Altogether, the multiple tiered analysis achieves improved performance and accurate identification of individuals with the health condition.

An assistance method for assisting a user in understanding the health condition of a subject, the assistance method comprising: acquiring a care record of the subject including text data in a first period (S11); determining the presence or absence of a physical condition abnormality in the subject from the text data using a natural language processing model (S12); and outputting presentation information, based on the result of determination of the presence or absence of the physical condition abnormality, to an information terminal of the user (S17).

A driver support system includes: an acquisition unit that acquires biometric data of a driver of a moving object; an evaluation unit that evaluates a health condition of the driver; and an interactive response unit that executes an interaction operation for interactive response with the driver using an HMI device mounted on the moving object, the evaluation unit being configured to; when estimating based on the biometric data for the driver that the health condition of the driver is poor, instruct the interactive response unit to execute the interaction operation, thereby acquiring a response input, which is a response of the driver to a response facilitating output that facilitates the driver to respond in the interaction operation; and determine the health condition of the driver based on a degree of suitability of the response input to the response facilitating output.

The invention belongs to the technical field of medical equipment, and particularly discloses a pregnancy monitoring method and system based on multi-mode signals, and the method comprises the following steps: synchronously collecting multi-mode physiological signals of a fetus and a maternal body; based on the synchronously collected multi-modal physiological signals, multi-channel feature extraction is carried out; on the basis of the extracted multi-channel features, screening out a feature subset with the most discriminant ability by using feature engineering; and inputting the feature subset into a pre-trained machine learning model, and outputting starting and ending of single fetal movement time, duration, fetal movement type and strength and maternal physiological features. By adopting the technical scheme, multi-mode synchronous acquisition is realized, high-sensitivity and high-specificity detection on fetal movement events and physiological characteristics and states of a mother are realized by adopting a characteristic engineering and machine learning model, non-invasive and harmless real-time monitoring on health conditions of the fetus and the mother is realized, and when the mother or the fetus is abnormal, intelligent remote alarm is realized, so that the safety of the fetus is improved. And a guarantee can be better provided for the health of fetuses and maternal bodies.

The invention relates to the technical field of equipment management, in particular to a dynamic evaluation method and system for the health condition of a refrigerating unit, and the method comprises the steps: constructing a refrigerating capacity and energy efficiency ratio prediction model through a gradient lifting regression tree algorithm, and training a high-precision reference through the full utilization of historical data; a stable and reliable prediction reference and a data analysis basis are provided for subsequent dynamic evaluation; a static model is converted into a dynamic model responding to a real-time working condition, real-time evaluation on the performance of the refrigerating unit is achieved, and meanwhile, the sensitivity and accuracy of state monitoring are effectively improved by combining degradation degree cooperative calculation; the real-time score of the refrigerating unit is compared with the preset judgment threshold value, so that the health state of the refrigerating unit can be quickly and accurately judged; when it is detected that the refrigerating unit is in the abnormal state, the model updating period and the sensor sampling frequency can be dynamically adjusted, and it is ensured that more accurate and timely data are obtained at the critical moment.

Disclosed are a method, system, and apparatus of a biometric sensor of a tactical gear to monitor health and stress of a wearer. In one embodiment, personal protective equipment includes a language translator module integrated in a tactical gear, a biometric sensor, and a responsive device integrated in the tactical gear. A wearer bi-directionally communicates with an individual in an ambient environment using any language other than a primary language spoken by the wearer when the language translator module is activated. The biometric sensor detects the health condition of the wearer. The responsive device vibrates to notify the wearer when the biometric sensor detects an elevated stress level of the wearer of the tactical gear. The biometric sensor is detachable from the tactical gear and placeable on an injured person nearby to the wearer through an armband extendable from the biometric sensor when it is removed from the tactical gear.

Disclosed are a method, system, and apparatus of a biometric sensor of a tactical gear to monitor health and stress of a wearer. In one embodiment, personal protective equipment includes a language translator module integrated in a tactical gear, a biometric sensor, and a responsive device integrated in the tactical gear. A wearer bi-directionally communicates with an individual in an ambient environment using any language other than a primary language spoken by the wearer when the language translator module is activated. The biometric sensor detects the health condition of the wearer. The responsive device vibrates to notify the wearer when the biometric sensor detects an elevated stress level of the wearer of the tactical gear. The biometric sensor is detachable from the tactical gear and placeable on an injured person nearby to the wearer through an armband extendable from the biometric sensor when it is removed from the tactical gear.