405 results about "Health evaluation" patented technology

A system, an apparatus and a method for human health evaluation utilizing the TMT mapping technology is disclosed. The method comprises scanning body areas of a patient utilizing an infrared camera, detecting abnormalities in the body of the patient, analyzing abnormalities of the patient against information stored in a database, and reporting results to the patient in a pre-determined format. The method provides an earlier discovery of disease by mapping and analyzing abnormal temperatures changes in the body, which can help prevent the disease from progressing at an early stage.

Some adult devices are ostensibly marketed to improve female sexual experience female by offering exercises to address relaxed vaginal muscles from birth, age, surgery etc. and for reducing incontinence. However, such devices suffer from variable placement by the user both in terms of orientation and penetrative depth such that the “results” are not reproducible and captured data used to provide feedback to the user and/or providing visual/audible prompts is flawed. Accordingly, it would be beneficial to provide a device with reproducible placement and data for enhancing the usability/benefit of the exercise regimen. It would be further beneficial for the device to either provide this exercise regime as part of a wider assessment of sexual wellness or as part of a sexual stimulation activity thereby reducing the focus on “exercise” to derive the benefits of improved pelvic muscle control.

The invention relates to a human-body health function-status evaluating model, relates to an evaluating method for comprehensively evaluating the functional level of a human body and belongs to the category of health evaluation. The construction of the evaluating model comprises the establishment of seven modules, i.e. a brain-cognizing function module, a metabolic function module, a traditional-Chinese-medicine symptom-identifying module, a psychological function module, a social-adapting function module, a cardio-pulmonary function module and a movement function module and the establishment of a specific testing project, an index system and a specific index under each module and a testing-project evaluating standard. The score evaluation of the whole module is finally obtained through each-step index evaluation, weight determination and calculation step by step. The integral comprehensive evaluation and the evaluating result of each module are all shown by corresponding evaluation reports. Functional-status levels in the aspects of physiology, psychology and social adaptation of the human body can be obtained through the health function-status evaluation of the human body, so that potential health hazards are found in advance, and intervention treatment is carried out as early as possible, so as to guarantee the physical and psychological function-status health of the human body.

The invention provides an intelligent battery state of health (SOH) detection method used for an electric vehicle sharing charging pile. The intelligent battery SOH detection method comprises steps that power battery data of user application is tracked, and the power battery data is categorized and stored; the actual measurement current, the end voltage, and the surface temperature of the power battery data are used as input samples, and the training data set of the power battery data is established, and then an LSSVM regression model is acquired; a power battery SOH training model is established according to parameters, and is used for health estimation of a current charging battery unit; a battery current maximum capacity is used as a SOH evaluation index, and a power battery SOH model is established, and is optimized; voltage, current, temperature, and time information of a database are transmitted to a monitoring platform by a communication protocol, and the monitoring platform is used to estimate the SOH of the battery. By adopting a big data analysis method, the establishing of the battery data model is completed, and during a charging process, SOH of energy storage systems of all of users is evaluated.

The invention discloses a multiparameter biological information testing platform and a testing method, which adopts a movement human body as a testing object, acquires kinematic parameters, macroscopic action force of a human body and a supporting surface, distribution characteristics of sole pressure, bioelectric information of muscle groups of the human body and the like of all sections synchronously, monitors dynamic change characteristics of cardiopulmonary functions of the human body and provides theory and platform support for relevant studies and applications. The multiparameter biological information testing platform comprises a biological testing channel and integrated analysis software, wherein the testing channel comprises a synchronous clock server, a gait tactile information testing unit, a surface myoelectric acquisition unit, a high-speed image acquisition unit, an acceleration/angle testing unit and a heart rate/pulse testing unit. Under the uniform control of a center computer, all subfunction instruments are interconnected by an Ethernet interface, and realize accurate synchronization of time domains of all parameters by a clock synchronous server to form a comprehensive testing platform; each unit equipment also can be equipped with self-analysis software and a man-machine interface to form an independent instrument. The invention provides a multiparameter biological information acquiring integrated testing device and a testing method for the aspects of gait analysis, sports science research, movement function and health evaluation, basic tests and the like.

The invention discloses a remote home health care system. The home health care system comprises a fusion sorting subsystem used for receiving physical sign data parameters collected by a sensor in real time, conducting fusion sorting processing on the physical sign data parameters and diagnosing and feeding back the body condition of a user in real time according to physiological data and physiological models in a physiological model library, a resource optimization subsystem used for regularly optimizing the physiological data in a physiological database, generating an individualized physiological model for the user according to the historical physiological data in the physiological database, storing the physiological model in the physiological model library, and updating the physiological models in the physiological model library according to the latest physiological data in the physiological database and a comprehensive assessment subsystem used for predicting the physical sign change tread and the physical sign dynamic change range of the user according to the physiological data in the physiological database and the physiological models in the physiological model library and assessing the health of the user according to the physiological data and a predicating result.

An aerospace vehicle integration performance verification system based on data sharing is divided into a preposition equipment area and a rear end equipment area. The rear end equipment area is divided into a test service area and an operation application area. The preposition equipment area, the test service area and the operation application area are connected through using an optical fiber network. The preposition equipment area is an information interaction link of an aircraft and the rear end equipment area and is formed by subsystem test equipment. The test service area is a core area of the aerospace vehicle integration performance verification system and comprises a test processing server, a data subscription server, a data interpretation server, a database server, a health monitoring and assessment server and a disk array. The operation application area is formed by a control operation platform and a data monitoring terminal. Through using various kinds of services provided by the test service area, functions of remote control/control instruction sending, parameter interpretation and health evaluation rule editing, test flow bookbinding, data display, data query, data playback and test report generation are realized.

The invention relates to a method for diagnosing a transformer fault in a transformer station. The method comprises the steps of: (1), data acquisition, i.e., an oil chromatogram sensor installed on the transformer acquiring an oil sample and performing chromatography to obtain the concentration values of hydrogen, methane, ethane ,ethane and acetylene; (2), data processing, i.e., selecting concentration values three times of standard deviations; (3), health assessment; (4), three-ratio method diagnosis; (5), characteristic gas method diagnosis; (6), Duval's triangle method diagnosis; and (7), diagnosis result, i.e., performing comprehensive determination on a transformer first fault diagnosis result, a transformer second fault diagnosis result and a transformer third fault diagnosis result, and then selecting a conclusion with the highest confidence as a transformer fault diagnosis result according to a confidence rule. According to the invention, by taking current operation condition of electrical network equipment as a basis, the equipment operation state is analyzed in real time and fault diagnosis is carried out on abnormity equipment so that power supply reliability is ensured, maintenance cost is lowered, and maintenance risks are reduced.

The invention discloses an airborne Aircraft Communication Addressing and Reporting System (ACARS) and a malfunction diagnosis and health management method thereof. The airborne system comprises a communication unit, a communication management unit, comprehensive modularized avionic equipment and a control/display unit. The comprehensive modularized avionic equipment comprises a data acquisition module, a data processing module, a status monitoring module and a health evaluation and malfunction diagnosis module. The airborne system communicates with a ground control center to achieve real-time information transmission between a plane and the ground; and meanwhile, the airborne system is provided with the data acquisition module, the data processing module, the status monitoring module and the health evaluation and malfunction diagnosis module, the Aircraft Communication Addressing and Reporting System (ACARS) can be subjected to health condition monitoring and malfunction diagnosis, and therefore the safety and the reliability of the Aircraft Communication Addressing and Reporting System (ACARS) are further improved, and the flight safety is ensured.

The invention discloses a mobile medical care remote monitoring system and a data transmission method thereof. The mobile medical care remote monitoring system comprises a mobile terminal and a mobile medical care data center system which are in communication connection through a service platform. The data transmission method comprises the following steps of: evaluating physiological status data of the human body, further sending a control instruction of further providing status data to the mobile terminal when the health status of a patient is worsened, and sending a control instruction of reducing status data to the mobile terminal when the health status of the patient gets right; carrying out health evaluation by adopting multiple types of status data; processing multiple types of physiological status data of the human body by adopting a data fusion technology, and mapping the processed physiological status data into new parameters representing the health status of the patient; and smoothening the data by adopting a forgetting factor. According to the mobile medical care remote monitoring system and the data transmission method thereof, the data transmission quantity of the mobile terminal of the patient is self-adaptively adjusted, the processing capacity of the mobile medical care remote monitoring system is improved, the unnecessary mobile communication flow cost is saved and the popularization and generalization of a mobile medicine heath care system are facilitated.

The invention discloses a bridge health evaluation method, and relates to the technical field of bridges. The bridge health evaluation method includes acquiring timing-sequence based bridge health monitor data from a bridge health evaluation system, and generating a training sample set on the basis of pre-divided bridge health state levels; performing training by the training sample set to acquirea neural network model; inputting the newly-collected bridge health monitor data into the neural network model, and outputting the predicated bridge health state level. The bridge health evaluation method has the advantages that the newly-collected bridge health monitor data are input into the neural network model, the predicated bridge health state level is outputted, and the bridge health stateis evaluated and predicated effectively.

The invention relates to a substation equipment state intelligent evaluation system and method based on big data. The intelligent evaluation system adopts a B/S mode, the data collection module obtains the real-time operation data of the substation equipment, Basic parameters, Overhaul data, etc, the data processing module processes the real-time running data, the substation state evaluation module receives the data collected by the data collection module and the data processed by the data processing module, and the AI state evaluation and prediction method is used to evaluate the health of substation equipments, the data standardization module carries on the data standardization processing to the overhaul data, the display early warning module monitors and warns the data of the data processing module. Compared with the prior art, the invention has the advantages of strong synchronization ability, increased data comprehensive cross analysis and processing ability, forward-looking and the like for evaluating and predicting the health status of the main equipment of the substation.

The invention discloses an airplane rotation actuator drive unit adaptive fault detection, isolation and confidences assessment method. Firstly, in dependence on the structure of a rotation actuator drive unit, establishing a two-stage observer based on a radial basis function (RBF) nerve network, wherein a first stage RBF nerve network observer is used for estimating system desired output values and generating residual errors, and a second stage RBF nerve network observer is used for generating adaptive threshold values; then performing fault isolation based on output information of the observer; training a self-organizing mapping (SOM) nerve network by utilizing residual errors under a normal state; and finally utilizing residual errors to be detected and assessed as input of the SOM nerve network and performing normalization processing to obtain confidences values (CVs) indexes between 0 and 1. The airplane rotation actuator drive unit adaptive fault detection, isolation and confidences assessment method has high practical engineering application values.

The invention belongs to the technical field of medical testing, and particularly relates to a multifunctional human physiological parameter testing device, which comprises a frame body and a control center arranged in the frame body. The frame body is provided with a detection component, the detection component is used for detecting multiple human physiological parameters, is electrically connected with the control center, is controlled by the control center, and comprises a body height detector, an electronic weight scale, a thermometer, a blood pressure detector, an electrocardio and body composition tester, and a blood oxygen tester, the body height detector is fixedly arranged at the upper end of the frame body and is used for detecting the body height, the electronic weight scale is arranged at the bottom of the frame body and is used for detecting the weight, the thermometer is fixedly arranged in the middle of the frame body and is used for detecting the temperature; the blood pressure detector is used for detecting the blood pressure, the electrocardio and body composition tester is used for detecting the heart rate and body composition, and the blood oxygen tester is used for detecting the blood oxygen. Therefore, when an examinee is located in the testing device, multiple human physiological parameters can be tested, a health assessment form can be obtained, multiple testing instruments can be eliminated for the examinee, the detection efficiency can be improved, the detection time can be saved for the examinee, and one-stop convenient services can be provided for the examinee.

The invention provides a system and method for fault prediction and on-line evaluation of health state of marine diesel generator, which includes a shell, a displayer, an alertor, a power supply and adata processing device, wherein the data processing device include a deep learning integration module, a full life cycle history database, and a fault multimodal expert system database. The deep learning integration module utilizes an integrated learning method, and includes multiple supervised and unsupervised deep learning network models. The fault multimodal expert system database includes allfault feature databases and corresponding fault category labels, and also comprises a memory, a GPU, a CPU, an external device control interface, a data acquisition module and a wireless signal transceiving device, and realizes automatic monitoring and evaluation of an equipment. The system has the advantages of more accurate and convenient fault prediction, state on-line monitoring and the health evaluation.

The invention discloses a NanoSat satellite house-keeping health management system based on a Bayes network model. The system includes a whole satellite level health management system, sub-system level health management modules, and part level health management units. The whole satellite level health management system is intended for conducting health evaluation and fault recovery on the whole satellite electronic system. Each sub-system level management module is intended for monitoring, diagnosing and evaluating each sub-system and constituting a comparatively independent sub-system level diagnosis evaluation module. Each part level health management unit is intended for processing and transmitting data acquired by a part or a sensor; the whole satellite level management system is connected to a plurality of sub-system level health management modules which are connected to a plurality of part level health management unit. According to the invention, the system establishes a hierarchical and distributed satellite house-keeping health management system architecture, can realize automatic management function of a satellite, and prolongs service life and safe operation of the satellite.

The invention provides a system and a method for evaluating health conditions based on an internet of things. The method comprises the following steps of: receiving health questionnaire survey information of a user from a medical terminal device; acquiring physical sign data of the user by virtue of a physical sign sensor arranged on the medical terminal device; obtaining a health condition evaluation model from a health evaluation model library according to the health questionnaire survey information and the physical sign data; acquiring geographical position information of the user by virtue of a position sensor arranged on the medical terminal device; matching an environment information platform of an area in which the user is positioned according to the geographical position information, acquiring environment information of the user from the environment information platform, and correcting the health condition evaluation model according to the environment information to obtain a health evaluation report of the user; and adding health improvement suggestions from a doctor into the health evaluation report, and sending the health evaluation report to the medical terminal device. The system and the method provided by the invention can be used for evaluating the health condition of the user in combination with environmental factors of the user, so that the accuracy of an evaluation result is improved.

The invention discloses a fault prediction and health processing method and a test system of a power MOSFET. The method comprises specific steps of selecting an MOSFET device with the normal performance and features to be a test sample; by testing three parameters of the drain and source electrode voltage, the drain electrode current and the device housing temperature of the normal device in the aging process, analyzing the test data and establishing a prior deterioration model E based on a feature parameter Rds(on); determining a failure threshold value; using test data of an actual to-be-detected device to train the model E; correcting the feature parameter of the model; and by calculating and predicting the remaining life of the MOSFET device, outputting a health estimation result and carrying out health processing on the device. According to the invention, there is no need to use a large test device and a complex experiment environment, so the prediction accuracy is high; the performance of the prediction algorithm is high; and probability of false prediction can be greatly reduced.

The present invention discloses an AI (artificial intelligence)-based eye health assessment method and belongs to the artificial intelligence medical detection technical field. The method includes thefollowing steps that: a plurality of fundus images and eye basic data are acquired, the acquired data are structurized, eye feature attributes are analyzed, health indexes are provided according to the eye feature attributes; and the fundus image of a user is pre-processed through an image processing algorithm, and feature extraction is performed on the pre-processed fundus image; and an eye health assessment model is constructed through using a deep learning algorithm; and the eye health assessment model is imported through a cloud computing platform, a health report is generated, and an health index is outputted. With the method adopted, the health statuses of eyes can be detected conveniently; a direct feedback can be provided for a user; and disease prevention and daily health management can be facilitated.

The invention discloses an aero-engine service life prediction method based on label-free, unbalanced and initial value uncertain data, which comprises the following steps of firstly, carrying out feature screening on an engine training data set by utilizing a correlation index and a trend index; then, obtaining a health state label through quantum fuzzy clustering, training a multivariable deep forest classifier, and obtaining an aero-engine health assessment model; meanwhile, training a long-short cycle memory neural network (LSTM) time sequence prediction model by utilizing the engine training data set; and finally, obtaining the maintenance time and the final residual service life (RUL) of the engine at different health stages by using the engine test data set according to the trainedhealth assessment model and the time sequence prediction model. According to the method, the defects of no label, imbalance and initial value uncertainty of observation data are overcome, and a technical reference is provided for maintenance decisions of the aero-engine in different subsequent health stages.

The invention discloses a fault early warning and life prediction method of escalator equipment. The method calculates the health status of an escalator system according to each module status of the escalator, the escalator health status is compared with the escalator abnormality time fitting function, the escalator operation time is obtained, and the remaining life of the equipment can be calculated according to a failure threshold of the escalator corresponding to the escalator operation time. According to fault early warning and life prediction method of escalator equipment, all kinds of algorithms adopted are designed based on equipment index analysis, the escalator index in algorithms is changed to other equipment indexes, the real time index data of the corresponding detection equipment is collected, so that the health evaluation status and the remaining life of the detection equipment. Therefore, the algorithm system is suitable for the prediction of each key equipment, and hasthe commonality.

The invention discloses a health evaluation method for eutrophic lakes, which comprises the following steps of: 1, according to the requirements of lake management, starting with an integral river basin, and determining a comprehensive evaluation index system containing the natural attribute for maintaining the life health of the eutrophic lakes and the social attribute of the lakes for satisfying sustainable development demands of human society; 2, establishing an evaluation model including a data entry and processing calculation module, a single factor evaluation calculation module and a comprehensive evaluation calculation module based on the multifactor comprehensive principle and the fuzzy relation synthesis principle according to the comprehensive evaluation index system established in the step 1; and 3, entering basic data to the evaluation model, and performing the health evaluation of the lakes by a calculation result outputted by the evaluation model. By the method, the health condition of the eutrophic lakes can be determined quickly, model software has the advantages of visual result expression, convenience for application and the like, and an effective technical management tool can be provided for the lake management.