42 results about "Objective assessment" patented technology

The invention provides an intelligent automobile test case automatic generation and evaluation system, device and product, and relates to the technical field of intelligent automobile test.According to the system, domain knowledge support is provided through a test knowledge base, and a demand understanding module is combined with a fine-tuning large model to deeply analyze demands; function points are extracted, and hidden scenes such as sensor faults and multi-system cooperation are identified; the test case generation module is based on a special prompt template and few-sample learning, a complete case containing elements such as purposes, steps and data is generated by fusing a vehicle model configuration library, and the specialty and the performability are ensured; and the evaluation module realizes objective quality evaluation through multi-dimensional quantitative scoring of demand coverage rate, scene integrity, risk coverage degree, normalization and the like. All the modules cooperate to realize intelligent generation and system evaluation of test cases, and the automation level, coverage range and reliability of intelligent automobile testing are improved.

The invention relates to the technical field of intelligent assessment management, and discloses an assessment method for a virtual maintenance training process, and the method comprises the following steps: collecting real-time operation data in the maintenance training process through a virtual reality device, and the real-time operation data comprises a gesture track, a tool use sequence and an environment interaction log; performing noise filtering and format unification processing on the real-time operation data to generate a standardized operation data stream; key operation nodes in the standardized operation data flow are extracted based on a maintenance knowledge graph, and operation feature vectors are generated; according to the invention, systematic fusion and standardization processing are carried out on multi-source heterogeneous real-time operation data, and an objective evaluation benchmark is constructed based on a maintenance knowledge graph, so that comprehensive quantification and description of an operation process can be realized; the problems that the evaluation dimension is single and the real skill level is difficult to comprehensively reflect due to the dependence on subjective judgment and a single index are solved, and the objectivity and comprehensiveness of assessment are improved.

The device (1) is used to determine insomnia in a patient (8). It has a sensor unit (2) for recording at least one EEG measurement signal of a brain wave of the patient (8) and a control and evaluation unit (3) for evaluating the recorded EEG measurement signal. The control and evaluation unit (3) is configured to carry out an objective assessment routine and in doing so, for the subsequent recording of the EEG measurement signal, to give the patient (8) a stipulation to open his eyes for the duration of an eyes-open period and to close his eyes for the duration of an eyes-closed period, and then to initiate the recording of the EEG measurement signal during at least one eyes-open period and during at least one eyes-closed period. The control and evaluation unit (3) is further configured to perform an evaluation of the EEG measurement signal thus recorded and in doing so to extract from the EEG measurement signal at least one first partial measurement signal from the at least one eyes-open period and at least one second partial measurement signal from the at least one eyes-closed period, and to decide on the presence of insomnia if the at least one second partial measurement signal from the at least one eyes-closed period has a lower proportion of α waves than in a healthy individual.

The present disclosure describes systems and methods for assessing heart and respiratory disorders in a patient using a video analysis tool to analyze video data taken of the patients neck region. The video analysis tool allows for an accurate, objective assessment of the patient. In some aspects of the present disclosure, a clinician may capture video data of the patients neck region and run the video analysis tool. Additionally or alternatively, the system may be implemented remotely whereby the video analysis tool may be executed remotely from the video recording device. The video analysis tool extracts pulsatile signals in the neck region from the video data and determines pulsatile signals of interest for assessing heart and respiratory disorders in the patient. The video analysis tool generates assessment data based on the pulsatile signals of interest.

This invention proposes a method for assessing the resilience of heavy platforms based on the DA-PSR model and complex networks. Taking heavy platforms as the object, an objective resilience assessment system is constructed. An assessment index system with causal relationships is established, and a screening method for the assessment index system based on node betweenness values ​​in complex network theory and the k-means algorithm is proposed. This results in a simplified assessment index system where the remaining node betweenness values ​​account for 52.99% of the total betweenness values ​​and the remaining cluster center values ​​account for 90.55% of the total cluster center values. An index weighting method based on mutual information theory and an index calculation method based on extreme damage quantification are proposed. The PSR framework theory is improved through dimensional analysis, and a resilience DA-PSR assessment model is constructed. Considering the performance requirements driven by tasks, a criterion quantification and dynamic grading method based on task requirements is proposed. The assessment shows that a heavy platform with a resilience assessment value of 0.7373 exhibits different assessment levels of "excellent," "medium," and "poor" under different tasks.

The invention discloses a data asset compliance evaluation method, equipment and a medium, and relates to the technical field of data asset compliance evaluation. The method comprises the following steps: acquiring enterprise data assets, and evaluating the enterprise data assets based on a preset evaluation rule to obtain an evaluation index; based on the evaluation index, determining an influence factor corresponding to the evaluation index, and allocating a weight coefficient for the influence factor; weighted summation is carried out on the influence factors and the weight coefficients corresponding to the influence factors, and evaluation index scores are calculated; and generating compliance risk assessment results and repair suggestions of the enterprise data assets based on the assessment index scores. According to the method, the same measurement standard is established for the enterprise data assets through the unified evaluation rule and influence factor, and the evaluation index score is calculated through weighted summation, so that objective evaluation of the compliance of the data assets is realized.

The embodiment of the invention discloses an insomnia treatment effect assessment method and related equipment. The evaluation method comprises the following steps: acquiring a first fNIRS signal and a second fNIRS signal, and preprocessing the first fNIRS signal to obtain a first effective feature value set; preprocessing the second fNIRS signal to obtain a second effective feature value set; and respectively inputting the first effective feature value set and the second effective feature value set into the target model to respectively obtain a first classification label corresponding to the first effective feature value set and a second classification label corresponding to the second effective feature value set. And obtaining an insomnia treatment effect result of the insomnia patient based on the first classification label and the second classification label. Wherein the classification label is used for indicating the insomnia degree. The evaluation method is used for objectively evaluating the insomnia degree of the insomnia patient, the evaluation result is accurate, the insomnia treatment effect can be effectively evaluated, and decision making can be guided.

Disclosed are methods for assessing severity, determining future risk, matching with a drug treatment, and measuring response to treatment, for memory dysfunction, Alzheimer's disease, and cognitive decline. Also disclosed are new methods of use for drugs and natural compounds repurposed for use in improving memory, as well as for preventing and treating memory disorders, Alzheimer's disease and cognitive decline. All the above-mentioned methods are computer assisted methods analyzing the expression of panels of genes, clinical measures, and drug databases. A universal approach in everybody, as well as a personalized approaches by gender, and by diagnosis, are disclosed.

The invention discloses a multi-source data fusion hospitalized patient psychological state intelligent monitoring system, which relates to the technical field of health monitoring and comprises a data acquisition module, a multi-source data fusion module, an environment correction module, a psychological state evaluation module and a predictive analysis module. According to the method, multi-source data of electrocardiogram, electroencephalogram, facial expression recognition and speech emotion analysis are integrated, so that comprehensive and objective assessment of the psychological state of the patient is realized, and the accuracy and reliability of psychological state recognition are remarkably improved; according to the method, environmental parameters of noise and illumination are collected in real time, the comprehensive feature vector is dynamically corrected in combination with a treatment program feature value, interference of the special environment of a hospital on a monitoring result is greatly reduced, in addition, a psychological state reference model based on a convolutional neural network and an LSTM deep learning prediction algorithm are adopted, and the monitoring accuracy is improved. Not only can the current psychological state be accurately identified, but also psychological crisis can be early warned by analyzing the historical data trend.

This invention relates to the field of hydropower technology, specifically to a multi-dimensional assessment system and method for regional pumped storage development capacity based on data feature modeling and Beta distribution. The assessment method involves constructing a multi-layered Beta distribution model, introducing AHP scores, FCE scores, and TOPSIS scores as raw data, and optimizing them to obtain a more objective assessment report. Applying this assessment system to the aforementioned method, through a data-driven approach combined with reasonable statistical calibration, enhances the objectivity, dynamism, and accuracy of the assessment method, ensuring more scientific and rational support in complex decision-making.

The invention discloses an intelligent pilot post competency monitoring device and method. The device comprises a monitoring cloud platform display unit, a display unit, a control unit, a data collecting and processing unit and a post competency system. The pilot post competency assessment method effectively solves the technical problems of discontinuous monitoring, non-objective assessment and non-intercommunication of data in the existing pilot post competency assessment method. According to the method, the strong relevance between training investment and efficient improvement of safety performance is improved, low-cost and efficient pilot post competency evaluation is realized, the method adapts to variable requirements of future flight scenes, and a scientific, accurate and flexible selection and evaluation solution is provided.

The invention relates to a vehicle function safety risk assessment method and device, equipment, a medium and a vehicle. The method comprises the steps that environment parameters corresponding to a vehicle function operation scene are determined; determining driving behavior parameters according to the road test natural driving data corresponding to the hazard event; and according to the environmental parameters, the driving behavior parameters and the duration time of the hazard event, determining the vehicle function safety risk level. By parameterizing the driving behavior information of the driver and the vehicle function operation event, the vehicle function safety is objectively evaluated, the situation that function safety evaluation mainly based on manual subjective analysis is conducted depending on teams executing rating work and expert knowledge and experience is avoided, and the reliability of vehicle function safety risk evaluation can be improved.

This invention discloses a dynamic and collaborative prognostic assessment method for aneurysmal subarachnoid hemorrhage, comprising the following steps: training five sets of machine learning models based on common assessment features in the training set using a 10-fold cross-validation method to obtain five common prediction models for aneurysmal subarachnoid hemorrhage (FO); training five sets of machine learning models based on personalized assessment features in the training set using a 10-fold cross-validation method to obtain five individual prediction models for FO; dynamically combining the optimal FO common prediction model and the optimal FO individual prediction model using dynamic weights to obtain the optimal FO prediction model; and deploying a prediction tool based on the optimal FO prediction model in a web portal. This invention ensures a synergistic match between the model's generalization and accuracy, establishing a network-based prediction tool to provide clinicians with more convenient and objective assessment and to offer individualized prognostic functional status predictions for each patient.

In an example embodiment, a system, a method, and an apparatus are provided that include an application, configured for: creating a subjective, objective, assessment, and plan (SOAP) report, the creation includes: using a voice-to-text converter to turn a free-form verbal conversation with a patient into a text stream, the text stream is enhanced with metadata from a database to create an enhanced text stream that forms a basis for the SOAP report. Other examples can provide that the metadata includes data from a previous SOAP report, and data associated with a prevision visit of the patient. Still other scenarios can provide that the enhanced text stream is sent to a large language model (LLM) to automatically create a practitioner-specific SOAP report. The SOAP report is structured according to a practitioner's specific requirements, and the SOAP report is automatically entered into a patient database for subsequent access.

Disclosed are methods for assessing severity, determining future risk, matching with a drug treatment, and measuring response to treatment, for stress disorders. Also disclosed are new methods for use for drugs and natural compounds repurposed for use in reducing stress severity, as well as for preventing and treating stress disorders. All the above mentioned methods are computer assisted methods analyzing the expression of panels of genes, clinical measures, and drug databases. A universal approach in everybody, as well as a personalized approaches by gender, and by diagnosis, are disclosed.

The invention relates to the technical field of rehabilitation assessment, in particular to a cerebral apoplexy rehabilitation assessment method and system based on voice multi-task learning, and the method comprises the following steps: carrying out the psychological emotion recognition of assessment voice data, and obtaining a cerebral apoplexy rehabilitation subjective assessment task used for perceiving the subjective rehabilitation feeling of an assessment object; performing physiological function recognition on the evaluation voice data to obtain a cerebral apoplexy rehabilitation objective evaluation task for perceiving the objective rehabilitation state of the evaluation object; and performing weight adaptive combination on the stroke rehabilitation subjective evaluation task and the stroke rehabilitation objective evaluation task by using a multi-task learning mechanism to obtain a stroke rehabilitation evaluation model. According to the method, objective function states and subjective emotional feelings fed back from the voices of the patient can be taken into consideration during rehabilitation evaluation, pain and discomfort of the stroke patient can be perceived during functional evaluation, the individual accuracy of stroke rehabilitation evaluation is improved, and the user experience is enhanced.

This utility model discloses a precise testing device for the compressive strength of packaging boxes, relating to the field of testing technology. The device includes a testing base plate, a support frame fixedly connected to the top of the base plate, a pressure sensor mounted on the top of the base plate, and a testing limiting structure located on the base plate. The limiting structure includes a mounting frame, a lifting plate, a drive motor, and a threaded rod. The mounting frame is fixedly connected to one side of the base plate, and a sliding groove is formed on the side of the mounting frame closest to the base plate. The drive motor is fixedly mounted on the top of the mounting frame. Through the cooperation of the mounting frame, the lifting plate, and the limiting plate, the consistency of the compression height can be ensured. Regardless of the height of the packaging box being tested, it can be conducted under the same testing conditions. This provides good lateral comparability for multiple sets of test data, enabling a more scientific and objective assessment of the packaging box quality.

This invention discloses a method for quantitatively assessing the severity of dark circles under the eyes, belonging to the field of objective evaluation technology in cosmetic dermatology. The method divides the eye into the upper and lower eyelids, each assigned a 50% weight. Each area is scored in three dimensions: area (A), color (D), and structure (S). A weighted total score for each eye and a combined total score for both eyes are calculated. Based on the total score, the severity is classified as mild, moderate, severe, and extremely severe. Furthermore, the percentage of each indicator is used to classify the condition as pigmentary, structural, and mixed types. This invention provides an objective, standardized, and repeatable assessment. The combination of multi-dimensional indicators improves the accuracy of the classification. It can be used for preoperative diagnosis and postoperative efficacy comparison, and is compatible with automated assessment in medical aesthetic systems, solving the technical problem of the lack of unified standards in traditional subjective assessments.

This invention discloses an AI-based data management and analysis platform for TCM standardized residency training, belonging to the field of TCM standardized residency training data management technology. It addresses the problem of ineffective processing and analysis of acquired TCM standardized residency training data. This invention utilizes an AI comparison algorithm to perform curve data overlap comparison. This method can intuitively demonstrate the similarities and differences in key features between the standard residency training model data and the residency training model data. Machine learning algorithms are used to model the overlap comparison results, obtaining AI comparison model data for the residency training model data. This transforms the comparison results into a quantifiable model, facilitating objective evaluation of the residency training effect. Different quality ranges correspond to different learning plans, enabling targeted guidance based on the trainees' actual situations. Different learning paths are recommended based on the trainees' attribute tags, further meeting their personalized needs.

The invention discloses a children infantile autism rehabilitation training strategy generation method and system, and relates to the technical field of intelligent rehabilitation. The three core defects of high data subjectivity, strategy templating and adjustment lagging in traditional rehabilitation training are overcome. The key points of the technical scheme are as follows: a time sequence convolutional network and a gating cross-modal attention mechanism are fused to realize accurate association of symptom inducements; performing multi-step reasoning based on the dynamic knowledge graph, and identifying hidden risks; neural development logic sorting and dynamic feasibility verification are realized through a multi-level fusion algorithm; and driving continuous optimization of the knowledge graph by using the feedback data. The full-process intelligent effect from objective evaluation and precise intervention to continuous optimization is achieved, high-accuracy, high-perspectiveness, scientific and effective rehabilitation training support is provided for the autistic children, and the pertinence, predictability and long-term effectiveness of rehabilitation training are remarkably improved.

The invention discloses a four-dimensional evaluation method for an intelligent algorithm flood forecasting result, and aims to overcome the technical defects that an existing flood forecasting algorithm evaluation system is single in dimension, lacks space-time universality consideration and does not give consideration to flood type adaptability and decision reliability. According to the method, a four-dimensional comprehensive evaluation system covering space-time expansibility, performance indexes, flood type adaptability, interpretability and uncertainty quantification is constructed. According to the method, each dimension index is mapped to a 0-10 quantized interval through a standardized normalization method, comprehensive and objective evaluation of the intelligent algorithm is realized in combination with a weighted comprehensive evaluation model, and the problems of algorithm selection blindness, limited application scene, high decision risk and the like are solved. Experimental verification shows that the method can effectively identify technical advantages and disadvantages of different algorithms, provides a scientific basis for model selection, optimization and engineering application of a flood forecasting algorithm, and is especially suitable for algorithm evaluation in a multi-scale and multi-type flood scene.

The invention relates to an assessment device and an assessment model for objective assessment of pain. The assessment device comprises a processor, and the processor comprises a frequency domain transformation module, a frequency band separation module, a first assessment sub-module and a second assessment sub-module. The frequency domain transformation module generates a time-frequency characteristic matrix; the frequency band separation module divides the time-frequency characteristic matrix into five frequency bands related to pain perception in a frequency domain; a first evaluation sub-module extracts end time step features and an adjacent matrix from the time frequency feature matrix; generating a first feature vector representing a global association pattern between electrodes for acquiring EEG signals based on the end time step feature and the adjacency matrix; the second evaluation sub-module generates a second feature vector comprising the local space-time dynamic feature of the EEG signal; splicing the first feature vector and the second feature vector to form a fused feature vector; and calculating category probability distribution of the fusion feature vector and carrying out normalization processing to generate a pain objective quantitative index corresponding to the EEG signal.

The application provides a depression tendency identification method based on biomarkers and artificial intelligence, utilizes LC-MS technology to quantitatively detect multi-dimensional biomarkers in samples, combines with mental health assessment scale scores, generates continuous scores and state labels reflecting individual depression tendency degrees through a plurality of machine learning model modeling, provides data support for objective evaluation and intervention strategy making of mental health states, and provides an objective and efficient quantitative identification method in preliminary screening of depression tendency, and can assist clinical workers in screening, risk stratification or intervention scheme reference.

This application relates to the field of physiological signal detection and health monitoring technology, and provides a wearable device and method for microcirculation status assessment and multi-physiological parameter monitoring. The wearable device includes: a signal acquisition unit, a feature extraction unit, and a status assessment unit. The signal acquisition unit is used to acquire at least one physiological signal characterizing the hemodynamic characteristics and related microcirculatory physiological processes within peripheral blood vessels. The feature extraction unit is used to obtain feature parameters based on the physiological signals. The status assessment unit is used to analyze and calculate based on the feature parameters using a machine learning model and / or a physiological mechanism model to obtain a status assessment result characterizing the peripheral vascular microcirculation status. This application transforms the palpation assessment process, which relies on human experience, into an engineered, parameterized, and objective assessment process, reducing reliance on human experience and improving the objectivity, consistency, accuracy, and repeatability of the assessment results.

The invention relates to a medical simulation teaching technology, in particular to a uterus and mouth examination simulation teaching system, which is characterized in that an entity part comprises a maternal model and an interactive cervix uteri simulation assembly; the data processing part comprises an intelligent control module, a teaching evaluation module and an intelligent feedback module; the visualization part comprises an AR visualization feedback module, a radial pressure sensor, an axial pressure sensor and a displacement sensor of the cervix uteri simulation assembly, and is used for synchronously collecting palpation stress and uterine mouth opening change and storing the palpation stress and the uterine mouth opening change in a warehouse; the teaching evaluation module automatically scores based on standard data, an AR terminal overlaps and displays a pressure threshold ring, a track guide line and judgment prompt, evaluation feedback and intelligent guidance to generate error correction key points, and reproducible training, objective assessment and closed-loop improvement are achieved.

The inventors discovered that three-dimensional posture and time series motion data are capable of providing robust, accurate and objective assessments of patient musculoskeletal health. Through the coupling of novel kinematic modeling and dimensionality reduction techniques, the invention is able to utilize posture and motion trajectory data in order to identify various neuromuscular and musculoskeletal conditions previously indistinguishable through the use of conventional clinical assessments. Further, by leveraging recent advancements in motion capture technologies, the invention provides approaches and systems adapted for remote implementation, allowing for quantitative and objective assessments to be collected over time and at reduced cost. Methods of generating a biomechanical assessment for a patient are provided.

This application relates to the field of equipment health monitoring technology, and provides a method and system for assessing the health status of rotating equipment. The method includes: acquiring a historical dataset of the rotating equipment, wherein the historical dataset consists of historical data subsets corresponding to multiple feature parameters; traversing the historical data subsets using a sliding window method and calculating the statistical dispersion index of the data values ​​within the sliding window; selecting the sliding window with the optimal statistical dispersion index and determining the set of data values ​​within this sliding window as the benchmark dataset; and determining the health score of the rotating equipment through weighted fusion calculation based on the real-time acquired feature parameter data values, the data values ​​in the benchmark dataset, and the weights of each feature parameter. This solution achieves a comprehensive and objective assessment of the health status of rotating equipment, reducing reliance on human experience.

This invention relates to the field of children's motor development and intelligent assessment teaching. The system and method of this invention acquire key joint coordinates from children's movement videos using label-free motion capture and human posture estimation algorithms; normalize, encode, and calculate joint angles in the three-dimensional coordinate data to form standardized input data; automatically extract temporal features of the movements using a CNN deep learning model, and classify the overall and local movement sequences using a multi-task learning method; output the specific stage of the child's motor development continuum, achieving a scientific and objective assessment of motor development. The technical solution of this invention preserves the natural expression of the movements, achieving simultaneous classification and recognition of the overall motor development level and local sequences. It can not only determine whether a child's movements meet the standards but also accurately locate their stage position in the motor development continuum. Through this developmental assessment, it provides more scientific and personalized support for physical education and health monitoring.

This invention relates to the field of aircraft propulsion system technology, and discloses a comprehensive evaluation and decision-making method for multiple engine concept design schemes. By introducing game theory concepts, it achieves deep coupling of subjective and objective weights, and combines the maximum entropy criterion and deviation penalty factor to seek the optimal compromise between expert experience judgment and the inherent laws of data, thereby obtaining the optimal combination of weights. Based on this, a quantifiable comprehensive evaluation index is constructed to achieve a comprehensive and objective assessment and ranking of engine concept design schemes. Simultaneously, the Euclidean distance considering the standard deviation of technical indicators is introduced into the ranking of alternative schemes, enhancing the discriminative power and robustness of the evaluation results, effectively solving the problem of the difficulty in comprehensively balancing multiple technical indicators such as performance, structure, and cost. This invention can identify and screen the most promising innovative schemes, providing decision support for subsequent component design, thereby improving the overall engine performance and reasonably controlling R&D costs.

Techniques are disclosed for automatically generating Subjective, Objective, Assessment and Plan (SOAP) notes. In some implementations, a text transcript that is derived from an audio recording of an interaction between a first entity and a second entity is accessed. A first machine-learning model prompt can used to generate a labeled transcript that includes the text transcript labeled with label types corresponding to the first and second entities. A plurality of second machine-learning model prompts can be used to generate a set of note sections based on the labeled transcript. Each note section of the set of note sections corresponds to a section of a SOAP note that corresponds to the text transcript, and the SOAP note can be generated by combining note sections of the set of note sections. The SOAP note in a database that is associated with at least one of the first entity and the second entity.