13 results about "Assessment scale" patented technology

The invention relates to the field of health data processing, and particularly discloses a virtual reality-driven children tic disorder multi-modal data evaluation and intervention system, which comprises a data acquisition and evaluation module, a data processing module, a data processing module and a data processing module, a professional evaluation scale and an algorithm are adopted to comprehensively evaluate the severity, psychological tolerance and social adaptability of the tourette syndrome of children to obtain an evaluation result; a scene generation and sorting module which is connected with the data acquisition and evaluation module, generates diversified virtual reality scenes according to the evaluation result, carries out the intelligent sorting of the scenes according to a difficulty gradual increase principle, and builds a high-authenticity scene through a high-precision modeling technology; and the interaction control and behavior guide module is used for realizing interaction between the child and the virtual reality scene. By adopting the technical scheme of the invention, personalized evaluation and immersive scene experience can be realized, and intelligent intervention and feedback can be realized.

The invention provides a psychological health state assessment method and system based on AI, and belongs to the technical field of psychological health assessment. The method comprises the steps that S1, historical assessment questionnaires, historical facial expression images and historical emotion text data are acquired; s2, creating a facial expression recognition model and a text sentiment analysis model; s3, the two models are trained; s4, acquiring an actual evaluation questionnaire, an actual facial expression image and actual emotion text data, evaluating the actual evaluation questionnaire through a psychological evaluation scale to obtain a questionnaire evaluation score, and inputting the actual facial expression image into the facial expression recognition model to obtain an expression category. Inputting the actual sentiment text data into a text sentiment analysis model to obtain a sentiment category; and S5, generating a mental health state assessment result based on the questionnaire assessment score, the expression category and the emotion category. The method has the advantages that the efficiency, the specialty, the objectivity and the flexibility of mental health state assessment are greatly improved.

The invention relates to the technical field of education, and discloses a method for multi-dimensional ability assessment and training of teenagers and children, comprising the following steps: S1, data collection and preliminary assessment: collecting basic information of age, gender, past academic records and health conditions of the teenagers and children, and constructing a data file; according to age, a professional evaluation scale and test questions are used to carry out primary evaluation on multi-dimensional ability of cognition, memory, attention, learning difficulty and reading disorder, data are recorded, and standardized cognitive ability test questions are used to inspect cognitive level of children. According to the method and the system for multi-dimensional ability evaluation and training of the teenagers and children, basic information such as ages, genders, previous academic records and health conditions of the teenagers and children is comprehensively collected, professional evaluation scales and standardized cognitive ability test questions are applied, and the abilities such as cognition, memory and attention of the children are primarily evaluated from multiple dimensions.

A method to treat a predetermined subject population diagnosed with Alzheimer's disease (AD), including: selecting subjects diagnosed with early AD or having at least one symptom of early AD, with a goal to improve a score of the subjects in an assessment scale in at least one point, wherein the assessment scale comprises at least one of, an Alzheimer's Disease Assessment Scale– Cognitive Subscale (ADAS-Cog) or variations thereof, and / or a Mini-Mental State Examination (MMSE) scale or variations thereof; delivering auricular VNS treatment to the subjects for a time period of at least one month; identifying an improvement of at least one point in the scale in the subjects following the delivering.

To provide a rehabilitation program for an orthopedic patient in a telemedicine system using a smart device.SOLUTION: To calculate a rehabilitation index for quantitatively evaluating the recovery state of a patient by a numerical scale on the basis of a recovery evaluation score calculated on the basis of a questionnaire using a health-related QOL evaluation scale. A rehabilitation program of a grade suitable for the patient is selected on the basis of the calculated rehabilitation index, exercise biological information of the patient who has executed an exercise program of the rehabilitation program of the selected grade is measured and collected by the wearable sensor device, and it is determined whether the measured and collected data satisfies an exercise target value set in the rehabilitation program of the grade, whereby the grade of the selected rehabilitation program is updated to a program of a grade in which a load more suitable for the patient is applied.SELECTED DRAWING: Figure 1

This invention relates to the field of artificial intelligence visual analysis technology, and discloses an AIQ human-machine collaborative ability analysis system based on dynamic adaptation. The system includes a three-dimensional parameter standardization definition and input module, a five-dimensional AIQ ability model matching and question bank selection module, a dynamic three-dimensional adaptive engine and assessment scale generation module, a multi-modal process data full-link acquisition module, a multi-dimensional data fusion analysis and report generation module, and a system self-iteration and parameter library update module. This invention achieves dynamic adaptive adjustment of the assessment system, featuring input and interaction design with both human-initiated input and machine-initiated capture. It can calibrate the assessment content, task difficulty, and scoring standards in real time according to the cognitive development stage of the test subject, the application scenario of the assessment, and the development level of artificial intelligence technology. This ensures a high degree of fit between the assessment and the test subject's situation, and avoids assessment failure problems caused by the iteration of artificial intelligence technology.

The utility model discloses an assessment ruler for postoperative active pain, which relates to the technical field of pain assessment tools, and comprises an assessment ruler main body, one side of the assessment ruler main body is provided with an NRS pain score indication line, the surface of the NRS pain score indication line is provided with a plurality of first lamp bodies, and the first lamp bodies are provided with second lamp bodies. A plurality of first control buttons matched with the first lamp bodies are arranged above the NRS pain score indication line. According to the utility model, the positions of the first indicator and the second indicator are moved, so that the first control button and the second control button which correspond to each other are pressed, the first lamp body and the second lamp body which correspond to each other are lightened, and the voice output device synchronously broadcasts the contents of the NRS pain level and the FAS pain level which reach the positions; according to the design, the postoperative active pain assessment process of the patient can be quicker and more efficient, the patient can express own pain feeling more accurately, and assessment errors caused by unsmooth communication or understanding deviation are reduced.

We provide rehabilitation programs for orthopedic patients through a remote medical consultation system using smart devices. [Solution] A rehabilitation index is calculated that quantitatively evaluates the patient's recovery state on a numerical scale based on a recovery evaluation score calculated from a questionnaire using a health-related QOL assessment scale. A rehabilitation program of a grade appropriate for the patient is selected based on the calculated rehabilitation index. Then, the patient's exercise bio-information is measured and collected using a wearable sensor device as they perform the exercise program of the selected rehabilitation program. The grade of the selected rehabilitation program is updated to a program of a grade that imposes a load more appropriate for the patient by determining whether the measured and collected data meets the exercise target values ​​set for the rehabilitation program of that grade.

The invention relates to an identification method and identification equipment for a medical scale, and aims at reducing the manual analysis step of a doctor, improving the data processing speed and efficiency and enhancing the protection for the privacy of a patient through character scanning identification and automatic processing evaluation of the scale. The check code verification is carried out on the evaluation scale, so that the recognition capability of the check code used for recognizing the validity of the evaluation scale on the evaluation scale is improved, the accuracy of character scanning and the validity of the evaluation scale are ensured, and particularly, the accuracy is enhanced when handwritten contents of a doctor are processed. The comprehensive evaluation tool based on the deep learning model can quickly integrate evaluation scale scores, clinical symptoms and other related indexes in real time, more comprehensive diagnosis support is provided, and the influence of human errors and subjective factors is reduced. The workload of hospitals in the aspects of data management and analysis is reduced through the automatic and electronic process, and hospital resources can be more effectively distributed to other important tasks.

The application relates to the technical field of comprehensive evaluation of geriatrics, and discloses a scale missing item processing method and system for comprehensive evaluation of the elderly, which comprises the following steps: acquiring multi-source evaluation related data, aligning the multi-source evaluation related data to preset items of a comprehensive evaluation scale for the elderly, identifying missing items in the scale, dividing the missing items into multiple types, performing hierarchical completion according to the divided types, constructing a confidence level calculation model, and generating a confidence level of an evaluation conclusion; based on a preset key item set and an expansion condition, performing adaptive evaluation scheduling, preferentially completing key item evaluation, and only when the expansion condition is met, triggering non-key item evaluation or reevaluation suggestion; through the above method, automatic identification, hierarchical completion, confidence level labeling and adaptive scheduling of missing items in the comprehensive evaluation scale for the elderly are realized, the number of triggering times of unnecessary evaluation items is reduced, and the traceability of the missing processing result is improved.

This application relates to a method and apparatus for generating an assessment scale. The method includes: acquiring a behavioral question database, category classification rules, and question ratio rules; segmenting the behavioral question database according to the category classification rules to obtain at least one segmented behavioral question database; acquiring user data; filtering from the segmented behavioral question database to obtain a corresponding target segmented behavioral question database based on the user data; randomly selecting questions from the target segmented behavioral question database according to the question ratio rules to generate initial behavioral questions; and generating an initial assessment scale based on the initial behavioral questions. This method can solve the problems of inflexibility and lack of customization in assessment scales generated by traditional methods.

This invention belongs to the field of rehabilitation medicine technology, specifically disclosing an intelligent triage assessment system and method for F-S-D symptom clusters in breast cancer chemotherapy patients. The system includes: a multi-dimensional data acquisition module configured to acquire real-time sensory intensity data of the patient for three dimensions: fatigue, sleep disturbance, and depression, and map them into standardized symptom intensity vectors; a dynamic threshold determination module configured to determine whether to enable a fixed threshold or a dynamic threshold, and calculate a personalized dynamic threshold when enabling a dynamic threshold; a core symptom determination module configured to determine the patient's current core symptoms using a recursive decision tree; and a specialized assessment scale loading module configured to retrieve specialized assessment scales for core symptoms from the cloud for the patient to complete, and generate a structured report with severity gradients based on the completion results. This invention eliminates the need for full-scale quantitative assessment, making the testing process more targeted and reducing the workload of the assessment.

The invention provides a KAN network-based autism assessment scale numerical regression method, which realizes high-precision prediction of autism patient scale scores by collecting multichannel electroencephalogram (EEG) data, combining with behavior scale scores and utilizing feature extraction and modeling capabilities of a KAN network, improves the interpretability of a model, and improves the prediction accuracy of the autism assessment scale numerical regression. And the influence of each feature on scale scoring can be visually displayed. According to the method, the accuracy and consistency of scale scoring are effectively improved, dependence on manual evaluation of experts is reduced, and the method has wide clinical application potential and can be used for early screening, diagnosis support and personalized intervention analysis of autism.