62 results about "Physical examination" patented technology

This invention provides a safety assurance method and system for unmanned aerial vehicles (UAVs) used for medical examinations of high-rise buildings in cities. The method includes: continuously monitoring the flight parameters of the UAV, sampling the flight parameter data at a frequency of ≥100Hz, and performing fusion processing using a Kalman filter algorithm; employing a fault diagnosis algorithm, based on a dual judgment mechanism of threshold and trend analysis, to analyze the collected flight parameter data in real time; comparing power redundancy and attitude stability indicators with preset thresholds to determine the fault level, and performing graded emergency handling according to the fault level, triggering corresponding handling and response strategies for non-catastrophic or catastrophic faults; after the UAV lands, confirming the safety of the landing point through visual SLAM or GPS positioning, and initiating onboard communication to report the status. This invention provides a complete solution from fault prevention to collision buffering through redundant design, graded emergency response, and dual-level protection, maximizing the protection effect and facilitating industrial implementation and verification.

The present application relates to the technical field of radiation protection barrier production, and particularly relates to a vehicle-mounted radiation protection barrier online evaluation method and system for physical examination, which obtains process parameter information of a workpiece to be evaluated, obtains specification parameters of the workpiece to be evaluated based on the process parameter information, constructs a simulated three-dimensional model diagram of the workpiece to be evaluated if the actual radiation attenuation rate value is not greater than the preset radiation attenuation rate threshold, and preforms a crack sample model diagram, obtains a screened three-dimensional model diagram based on the simulated three-dimensional model diagram and the crack sample model diagram, obtains crack characteristic information in the screened three-dimensional model diagram, evaluates the workpiece to be evaluated based on the crack characteristic information, and obtains a first evaluation result or a second evaluation result. The present application can obtain the best repair scheme of unqualified semi-finished lead plates, so as to repair the semi-finished lead plates and reduce the scrap cost.

The present application relates to the technical field of health monitoring, in particular to a health state intelligent monitoring and guiding system for the elderly and rehabilitation persons, comprising: a data acquisition layer, used for acquiring non-contact physical sign data, environmental data, equipment use frequency and measurement data, flexible wearable device data, voice interaction data and individual basic disease and rehabilitation target data through a non-contact physical sign acquisition module, an environmental and equipment data acquisition module and a multi-modal physiological and basic data acquisition module. The non-contact physical sign acquisition module of the data acquisition layer can collect physical sign and behavior data without active operation of the user, the environmental and equipment data acquisition module is used to collect environmental and medical equipment use data, physical examination reports, the multi-modal physiological and basic data acquisition module is used to integrate physiological emotion and basic disease information, and the problem of incomplete data collection caused by the difficulty of the user to cooperate in the existing system is solved.

1. Name of the design product: automobile physical examination equipment. 2. Use of the design product: mainly used for comprehensive detection of automobiles to generate detection reports. 3. Design points of the design product: in shape. 4. Picture or photo best indicating the design points: perspective view.

The application discloses a cervical cancer methylation detection kit and application thereof, the kit takes PAX5 gene, PAX1 gene, MICOS10-NBL1 gene and MICOS10 gene as detection targets; the kit mainly comprises specific primer probe dry powder combination, PCR reaction reagent dry powder, positive control product dry powder, negative control product dry powder and microdroplet generation oil. The sample is detected by bisulfite conversion, and the kit is combined with microdroplet digital PCR detection technology to realize accurate detection of the methylation level of the target gene. The detection verification result shows that the sensitivity of the kit for cervical cancer detection reaches 96.9%, the specificity reaches 95.7%, the kit has the advantages of accurate detection, simple operation and strong stability, can be widely applied to early screening, clinical auxiliary diagnosis and physical examination of healthy people of cervical cancer, and provides reliable technical support for early discovery and early treatment of cervical cancer.

The present application relates to the medical care form technical field, propose a kind of medical care intelligent form generation method and system based on multimodal big model, comprising: collecting the physical examination of clinical business system in medical care patient, diagnosis record, diagnosis voice data and other multimodal data;Again, generate physical change sequence by multimodal big model in combination with physical examination data, construct diagnosis feature vector;Subsequently, the vector is mapped to medical quality index system, to generate visual form framework;Then, extract diagnosis record key elements and fill into framework, update form information in combination with diagnosis voice data;Finally, medical care intelligent form adapted to each system is output by multimodal big model, and is synchronized to medical care work terminal.The present application realizes the effective fusion of multimodal medical data, and the generated form can completely reflect the whole picture of diagnosis and treatment and the dynamic evolution of signs, improve the clinical work efficiency and medical quality.

1. The name of the design product: intelligent self-service physical examination all-in-one machine. 2. The use of the design product: intelligent device for human health detection and data collection. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

This invention proposes a method for optimizing mobile social security services based on a distributed and microservice architecture. Its technological breakthroughs are manifested in three core aspects: Elastic Service Cloud Network: Based on the self-developed PDFC framework, Spring Cloud microservice architecture, and Kubernetes containerization technology, microservices are deployed in a split manner, enabling dynamic scaling of microservice container nodes and second-level fault self-healing. Intelligent Data Hub: A cross-domain data channel is built based on Apache Kafka, collecting social security business data and health record data in real time with millisecond-level transmission efficiency. Intelligent Reporting Engine: An innovative three-dimensional intelligent reporting system is constructed. Pre-event reports are generated by parsing physical examination information; during-event reports are generated through dynamic monitoring of risk warnings; and post-event reports are generated based on actual business processing, achieving an upgrade and transformation of the governance model from "people seeking services" to "services benefiting people."

This invention provides an intelligent method for generating physical examination reports based on LLM and a knowledge base, aiming to better adapt LLM technology to the medical field of physical examinations, which lies between specialist diagnosis and routine health monitoring. The core of this method lies in constructing a hybrid architecture where a knowledge base and LLM work collaboratively to address the ambiguity in interpreting physical examination data caused by its "ambiguous intermediate zone." The specific method includes: identifying all abnormalities based on an indicator range knowledge base; performing precise matching and rule-based reasoning through a clinical physical examination diagnostic knowledge base, generating conclusions for unmatched abnormalities according to three preset rule categories; querying a health advice knowledge base and generating personalized suggestions through LLM; and performing global review and comprehensive verification by LLM to ensure the completeness and consistency of the conclusions. This invention combines a deterministic knowledge base with generative LLM reasoning, significantly improving the accuracy, personalization, and clinical interpretability of interpreting physical examination abnormalities, realizing the intelligent transformation from fragmented physical examination data to actionable health insights.

This invention discloses a dynamic prediction system for long-term adverse cardiovascular event risk after stent implantation, belonging to the field of personal health risk assessment technology. It includes: a cardiovascular assessment module for determining the target cardiovascular adverse event presentation coefficient based on the target patient's first chest pain rating and real-time heart rate after stent implantation; a cardiac function assessment module for determining the emphasis of cardiac function analysis at each stage based on the target patient's physical examination data after stent implantation; a probability determination module for determining the probability of the first adverse event based on the target cardiovascular adverse event presentation coefficient and the emphasis of each cardiac function analysis; and an indicator determination module for comparing the target patient's first adverse event probability with the second adverse event probability of each monitored patient to obtain the target cardiovascular risk warning indicator for the target patient. This invention can improve the accuracy of long-term risk prediction for adverse cardiovascular events.

The application discloses an AI-based health risk assessment and intelligent grading method and system, and relates to the fields of artificial intelligence, health management and big data analysis.The system comprises a data acquisition and preprocessing module, an AI risk assessment model, a personalized suggestion generation module and a user interaction and interface module; the method collects multidimensional data such as physiological indexes, physical examination reports, lifestyles, genetic heredity, medical histories and wearable devices, inputs the data into an AI model after preprocessing, automatically calculates the weights of dynamic indexes and generates a quantitative score, maps the score into a three-level action orientation grade such as a suggestion for medical treatment, regular review and daily attention, outputs personalized guidance, department recommendations and disease early warning in combination with a user portrait, and supports third-party integration and model closed-loop optimization.The application realizes panoramic and accurate insight, dynamic tracking and personalized management of health risks, has high efficiency and can be scaled up, and provides scientific decision-making support for users, medical institutions and insurance companies.

The utility model relates to a kind of multifunctional physical examination apparatus, including Y-shaped sound guide pipe (1), auscultation ear piece (2), chest piece (3), the auscultation ear piece (2) symmetry is set in the two branch ends of Y-shaped sound guide pipe (1), the chest piece (3) is set in the main stem end of Y-shaped sound guide pipe (1), the chest piece (3) back detachably provided with light source (4) and timer (5), the main stem side wall of Y-shaped sound guide pipe (1) is provided with scale mark layer (6) and pupil table (7), the main stem of Y-shaped sound guide pipe (1) still be provided with sensory tester (8), percussion hammer subassembly (9). Compared with prior art, the utility model is simple in structure, convenient to carry and take, and is conducive to improving the work efficiency of medical staff to carry out physical examination.

This invention discloses a risk prediction device and storage medium for metabolic-associated fatty liver disease in children or adolescents. The two-stage cascaded screening strategy and model of this invention provide a highly accurate, accessible, and scalable solution for the early identification of metabolic-associated fatty liver disease in children or adolescents. This invention utilizes different anthropometric data to identify high-risk groups in routine school physical examinations, followed by further screening using a comprehensive serological index at community health centers, thereby achieving accurate diagnosis of metabolic-associated fatty liver disease and providing clinicians with a non-invasive auxiliary diagnostic tool that combines high precision, high accuracy, and broad accessibility.

The application discloses a physical examination table full quantity intelligent auditing method based on natural language processing, and particularly relates to the technical field of natural language processing. First, the heterogeneous data of a physical examination table of a subject is acquired, and preprocessing is performed to obtain a standardized heterogeneous data set. A first structured fact list is generated based on the first data source after standardization, and a second structured fact list is obtained by reconstruction based on the second data source after standardization. Then, the first structured fact list and the second structured fact list are associated based on the unique identification of the physical examination table of the subject, and multi-dimensional logical consistency comparison is performed. An intelligent auditing result is obtained according to the comparison result. Finally, an intelligent auditing report is generated based on the intelligent auditing result, and human-computer interaction is performed. With the powerful computing power of the AI model, the application realizes full quantity automatic auditing of the physical examination table, does not need manual sampling, improves the auditing efficiency, reduces the misjudgment rate, and is suitable for the auditing scene of large-scale physical examination data.

The present application relates to the technical field of children's health assessment, in particular to a children's body fat rate adaptive prediction method and system based on trajectory feature cooperation, comprising the following steps: obtaining children's physical examination data set, analyzing height and weight change to calculate difference ratio to screen samples, extracting waist circumference change slope to evaluate stability to screen samples, calculating body sign proportion difference to adjust training weight, identifying age stage residual difference gap to adjust model parameters, combining body fat trend and body weight trend direction to adjust prediction slope to generate results. In the present application, samples are screened through height and weight trajectory, combined with the fluctuation continuity of waist circumference change slope to eliminate abnormal data, the feature weighting coefficient is set according to the proportion deviation of height and weight and muscle mass, the response coefficient is adjusted according to the distance relationship of the grouping mean and the central interval of the age stage residual, the change path is judged by the consistency of the body fat and body weight prediction trend, the non-trend prediction deviation is avoided, and the stability and sample adaptability of the model are improved.

This invention discloses a highly sensitive method for detecting troponin I. This method utilizes the reusable nature of a biosensor to perform multiple fluorescence signal reads. Based on these multiple reads, it selects the most accurate concentration range for determining concentrations in the low-to-medium concentration range, achieving higher resolution detection results in both low and medium concentration areas. Furthermore, it incorporates chemiluminescence detection, employing higher-resolution chemiluminescence to determine the final concentration in the high-concentration region. Ultimately, this method achieves better resolution detection results across high, medium, and low concentration regions, enabling accurate identification of sample concentrations across all concentration ranges. It boasts a sensitivity of 0.824 ng / L and a detection range of 0.824 ng / L–100,000 ng / L. The method significantly reduces sample volume, requiring only 20 μL for accurate detection, thus reducing blood volume and improving blood collection efficiency in physical examinations.

This invention provides an intelligent processing method and system for public health physical examination follow-up family signature data based on multi-device acquisition. The method includes: collecting raw data streams from multiple vendors' devices via an edge gateway; unifying fields, types, and units through protocol parsing, regular expression and syntax analysis; and promoting automatic semantic alignment of cross-device fields through a dynamic semantic benchmark template. This method employs a lightweight encoder-decoder and contrastive learning mechanism to construct a shared embedding space, achieving device-level semantic matching. It integrates contextual consistency verification and incremental knowledge distillation to support continuous model optimization with new devices and clinical feedback. This invention effectively solves the problem of inconsistent structure and semantics in multi-source medical data, improves the standardization and label consistency capabilities of health data, and promotes the automated application of intelligent risk assessment and follow-up management.

This invention discloses a multi-mode queue collaborative processing method based on reinforcement learning, comprising: S1, collecting multi-source heterogeneous data from a physical examination center; S2, performing spatiotemporal alignment and feature extraction on the data to construct a high-dimensional state feature vector; S3, constructing a high-fidelity digital twin simulation environment, initializing an agent based on an improved H-PPO algorithm, and defining a heterogeneous topology; S4, constructing a multi-objective weighted fusion reward function and introducing a cross-modal action consistency constraint factor to guide the agent in optimization; S5, outputting parameterized mixed actions through an Actor network and performing legality verification; S6, implementing differentiated collaborative scheduling strategies for different queue modes; and S7, updating network parameters and completing deployment through an online fine-tuning mechanism. This invention achieves dynamic resource allocation and closed-loop process optimization in the complex environment of a physical examination center, effectively shortening waiting time and improving equipment utilization.

The invention relates to an intelligent self-service physical examination system based on the Internet of Things technology, which comprises a control center, an unmanned department, guide bracelets, registration equipment and hospital leaving equipment, and is characterized in that the registration equipment registers identity information of a physical examinee, distributes the guide bracelets corresponding to the identity information to the physical examinee, and transmits the identity information to the control center at the same time; a physical examination person wears a guiding bracelet and sequentially reaches each unmanned department according to the guidance of the guiding bracelet, self-service physical examination equipment of different items is arranged in different unmanned departments, the self-service physical examination equipment verifies the identity through the guiding bracelet, then the physical examination person completes the physical examination items in a self-service mode and transmits the physical examination data to the control center, and after all the physical examination items are completed, the control center sends the physical examination data to the control center. And after the physical examination report is completed, the control center sends the physical examination report to the mobile phone program of the physical examinee. By adopting the scheme, the invention provides the intelligent self-service physical examination system based on the Internet of Things technology, which solves the privacy problem and the doctor resource shortage problem.

This invention discloses an intelligent obesity assessment and personalized weight loss management system that integrates multimodal data, belonging to the field of intelligent health management technology. It includes: a hierarchical data acquisition module configured to collect general public data and specialized medical data hierarchically through wearable device interfaces, manual input interfaces, and third-party data access interfaces. The general data includes height, weight, dietary records, and exercise records, while the specialized medical data includes complication diagnosis results, physical examination report data, and clinical treatment records. A dual-model data analysis module is also included, incorporating a clinical in-depth analysis model and a public health model. This invention solves the problems of existing systems having limited adaptability to specific scenarios, poor data integration compatibility, and insufficient security and compliance. It not only meets the general weight loss needs of the general public but also provides clinically adapted diagnostic and treatment support for specialists, achieving precise and compliant management of obesity across all scenarios.

The utility model discloses a kind of article temporary placing box for outpatient physical examination, including frame, placing plate and support rod, the four corners of the frame bottom are all fixedly connected with universal wheel, the rear side of the frame inside is fixedly connected with several quantities of support rod.The utility model is through the cooperation of frame, placing plate, support rod, universal wheel, containing groove, carousel, guide slot, moving frame, sliding block, fixed plate, moving block, through slot, gear, rack, screw rod, positioning hole, positioning rod, sliding slot, isolation plate, fixed hole, placing groove, spring, fixed rod and rotating block, solve the cleaning and disinfection when the existing equipment is carried out, due to internal baffle fixedly not detachable, leading to cleaning not completely, there is dead angle, bacteria is easy to breed, influence health safety, cannot effectively reach the high standard cleaning requirement required by medical environment, increase the risk of cross infection, the problem of potential threat to user health.

1. The name of the design product: micro physical examination graphic user interface of electronic device. 2. The use of the design product: interface for watch device. 3. The design points of the design product: in the graphic user interface. 4. The picture or photo that best shows the design points: front view. 5. The use of the graphic user interface: for displaying multiple health indicators of human body. 6. The human-computer interaction mode of the graphic user interface: the front view is the "micro physical examination" starting interface, after clicking the "start" button, the "micro physical examination" is started, after more than 30 seconds of detection time, the front view changes to interface change state figure 1, interface change state figure 1 slides down to change to interface change state figure 2, interface change state figure 2 slides down to change to interface change state figure 3, interface change state figure 3 slides down to change to interface change state figure 4, and interface change state figure 4 slides down to change to interface change state figure 5.

This invention relates to the field of report optimization technology, and in particular to a method for prioritizing medical examination report conclusions based on user medical history. The method includes: collecting multi-source data; preprocessing the multi-source data to obtain a structured multi-source dataset; based on the structured multi-source dataset, mining the correlation between health data and diseases through association analysis, constructing a health trend prediction model using a deep Q-network, and obtaining multi-dimensional diagnostic analysis results; combining the multi-dimensional diagnostic analysis results with a priority calculation formula to determine the priority of diagnostic conclusions; calculating a comprehensive risk score through data fusion scoring, classifying risk levels according to the comprehensive risk score, and matching corresponding phased intervention strategies; inputting the multi-dimensional diagnostic analysis results, intervention strategy execution feedback data, and user health preferences into a comprehensive diagnostic decision model, and combining the diagnostic conclusion priorities to obtain differentiated health association strategies. This solution accurately identifies disease severity through dynamic priority adjustment.

The application provides an engineering machinery health evaluation method and system, and belongs to the field of engineering machinery intelligent operation and maintenance, comprising: acquiring multi-source data of engineering machinery equipment; defining corresponding ontology and relationship of the multi-source data and writing into a knowledge graph to obtain a structured knowledge network; calling the structured knowledge network for query, obtaining a rule reasoning result based on a device component causal chain and a preset rule; vectorizing device state data, retrieving a most similar historical device case through a vector index engine to obtain a vector recommendation item; weighting and fusing the rule reasoning result and the vector recommendation item, giving each check weight and execution priority to obtain a personalized check item list; constructing a task tree according to the personalized check item list to obtain a physical examination report of the engineering machinery equipment. The application realizes personalized physical examination of "vehicle-specific inspection", obtains a practical structured report, and meets operation and maintenance decision requirements.

Disclosed is an ultrasonic diagnostic apparatus including a probe configured to transmit an ultrasonic signal to an object and receive information about an echo signal reflected from the object, and a main body including a display, an input interface configured to receive user input, and a processor configured to obtain physical examination data about a sacrum skin lesion of the object from the input interface, obtain an ultrasonic image of the object based on the information about the echo signal obtained from the probe, detect a variation related to a sacral dimple on the ultrasonic image, classify the variation as any one of a normal variation and a pathological finding, and control the display to display information about the pathological finding on the ultrasonic image based on the variation being classified as the pathological finding.

We provide a five-senses telemedicine system that utilizes sensory data to support smooth medical treatment. [Solution] The patient-side device 1 acquires visual, auditory, tactile, olfactory, and gustatory data, as well as vital signs. This data is integrated by the server 2 or the data processing unit 17 of the patient-side device 1 to generate differential diagnosis candidates. After automatically performing non-invasive physical examinations and tests, it supports automatic booking of medical appointments. The physician-side device 3 reproduces this sensory data and transmits movements and sensations bidirectionally. The physician operates the patient-side device in real time, utilizing the five-sensory data to perform physical examinations and tests such as palpation and joint range of motion assessment, thereby supporting diagnosis. H.265 / UDP is used for communication, supporting both low-speed and high-speed lines, ensuring stable operation even in sparsely populated areas.

This application discloses a method, apparatus, and system for intelligently calculating insurance customer medical examination exemption limits. The method includes: receiving an underwriting decision request; constructing a hybrid feature vector based on customer identification, integrating statistical features and actuarial rule features; selecting a target model from a pre-trained risk prediction model library according to product type, and inputting the vector to obtain a customer risk probability value; responding to the risk probability value, calculating and outputting a personalized optimal medical examination exemption limit through an optimization model aimed at maximizing the company's long-term expected profit. This application, through the dual-engine linkage of data-driven risk prediction and profit model-driven decision optimization, achieves automated information processing from accurate individualized risk assessment to automated optimal business decision-making, significantly improving work efficiency.

This invention discloses an embodied intelligent physical examination palpation result judgment algorithm, belonging to the field of medical robot technology. This invention is applied to an embodied intelligent agent comprising a tactile sensor array, a force sensor, and an end effector. The algorithm includes: acquiring the initial scanning path of the palpation area; controlling the end effector to perform initial screening palpation at each palpation point along the initial scanning path. The advantages are: this invention achieves intelligent palpation through a multi-layered design, including online estimation of tissue impedance and adaptive adjustment of palpation application parameters; autonomous encrypted rescanning of suspicious areas to accurately confirm abnormal boundaries; assignment of confidence labels based on the change in confidence before and after rescanning; and inputting structured palpation data into a medical large language model to generate a formatted report. This results in improved palpation accuracy, reduced the risk of missed or misdiagnosed diagnoses, and reduced the paperwork burden on doctors.