85results about How to "Personalize" patented technology

The invention discloses a shaping scheme generation method and system based on image recognition, and the method comprises the steps: obtaining a face image of a user, constructing a half-face model, generating a similar face set, recommending the similar face set to the user, generating a full-face comparison image set, screening the full-face comparison image set, and determining a target case. The method comprises the steps of obtaining a user face three-dimensional data model, predicting a reshaped face image, training a conversion model for converting a plane face image into a three-dimensional face model, converting the predicted reshaped face image into a reshaped three-dimensional face model, and generating a reshaping scheme for the user based on the user face three-dimensional data model and a target three-dimensional face model. Objective, personalized and high-precision generation of the plastic scheme is realized, a user can intuitively preview the plastic effect and participate in formulation of the scheme, satisfaction and credibility are improved, plastic doctors can formulate more professional and feasible operation plans based on detailed scheme and data support, operation risks are reduced, and the success rate is improved.

The invention discloses a drug recommendation method and system based on fine-grained relationship enhancement, and belongs to the technical field of artificial intelligence and digital medical treatment. Aiming at how to effectively extract complex relationships among different medical entities in EHR medical data and realize accurate recommendation of drugs, entity information in a medical data set is modeled by using a heterogeneous graph representation learning method so as to deal with low quality and sparsity of the medical data; expression of various symptoms is extracted through a multi-symptom extractor, patient expression is refined into multi-symptom expression, and the relation between the symptoms and the medicine is established to achieve personalized medicine recommendation. The system comprises a computer processor, an EHR historical medical record data set storage unit, a graph data processing unit, a fine-grained relationship enhanced drug recommendation model training unit and a drug recommendation unit, multi-symptom representation of a patient can be better extracted through the system, the relationship between multiple symptoms and drugs is established, and personalized drug recommendation is achieved. And the accuracy and reliability of drug recommendation are improved.

The invention discloses a respiratory disease oxygen precise conveying system based on a sensor, and relates to the technical field of medical equipment, and the system comprises a sensing module which integrates multiple sensors to collect and process airway and physiological data of a patient; the disease matching module identifies disease types through database comparison; the dynamic adaptation module calculates exclusive oxygen concentration based on a multi-mode fusion initial algorithm; the conveying module executes adjustment; the closed-loop feedback module continuously fine-tunes the oxygen concentration through a closed-loop stepped fine-tuning algorithm to form a closed-loop link, so that accurate dynamic control of oxygen delivery is realized; according to the invention, multi-sensor collaborative acquisition and disease precise matching are combined with a dynamic algorithm and closed-loop feedback, so that individuation and dynamic oxygen delivery are realized, the system avoids misjudgment by relying on a standardized database, and the oxygen concentration, flow and pressure are ensured to be adjusted in real time along with physiological indexes of a patient through multi-parameter collaborative adjustment and stepped fine adjustment; the treatment comfort, the effectiveness and the long-term adaptability are improved.

The invention discloses an oxygen concentration monitor and a monitoring method thereof, relates to the technical field of oxygen concentration monitoring, and effectively improves the accuracy and reliability of the monitor through comprehensive performance parameter acquisition, calibration judgment, body mass index analysis, sampling frequency setting, environment evaluation and compensation algorithm selection. According to the method, physical condition evaluation of a monitored patient can be optimized, and more accurate monitoring data can be provided according to environmental conditions, so that clinical requirements are better met, reliable monitoring services are provided, the medical quality is further improved, the calibration precision and efficiency are improved, and the accuracy and reliability of a monitor are ensured; through precise performance adjustment and calibration judgment and personalized monitoring service, the efficiency of the monitor can be improved, and unnecessary maintenance cost and human input are reduced. Therefore, the efficiency and quality of medical services can be improved, and medical resources can be saved at the same time.

The invention relates to the technical field of database construction, in particular to a construction method and system based on an encephalopathy nursing knowledge base. The method comprises the following steps: acquiring multi-source encephalopathy data; performing structured data screening on the multi-source encephalopathy data to generate structured encephalopathy data and unstructured encephalopathy data; performing multi-modal data structured layering on the unstructured encephalopathy data to generate multi-modal structured layered data; performing data preprocessing on the multi-modal structured hierarchical data and the structured encephalopathy data to generate a standard structured encephalopathy data set; performing context analysis on the standard structured encephalopathy data set to generate an encephalopathy information semantic vector set; and performing redundant relation pruning processing on the encephalopathy information semantic vector set to generate spatial semantic optimization data. According to the method, by integrating multi-source data, structured and unstructured information, real-time dynamic mapping nursing requirements and system feedback evaluation, the construction quality and practicability of the encephalopathy nursing knowledge base are improved.

The invention relates to an audio processing method and device, electronic equipment, a storage medium and a vehicle, and particularly relates to the technical field of audio processing. The method comprises the following steps: acquiring user voice, and identifying text content corresponding to the user voice; the text content is input into a term conversion model, target audio terms corresponding to the text content and output by the term conversion model are obtained, the term conversion model is obtained through training on the basis of the natural voice text and sample annotation data, and the sample annotation data are audio terms annotated on the basis of the natural voice text; querying a target audio parameter corresponding to the target audio term according to a preset mapping relationship between the audio parameter and the audio term; and processing the original audio according to the target audio parameter. The embodiment of the invention is used for solving the problems that the sound effect adjustment operation is difficult and the mode is fixed.

The invention provides an intelligent clothes nursing machine based on the Internet of Things, and relates to the technical field of intelligent clothes nursing machines, a clothes recognition module is used for recognizing the characteristics of clothes put into the nursing machine and numbering the clothes, and a data acquisition module is used for judging the contact environment data and the wrinkle degree of the clothes; the system calculates a tidiness coefficient and an adhesion coefficient according to the environment data and the wrinkle degree of the clothes, monitors clothes protection data and an equipment state through a clothes protection detection module and sends the data and the state to a control execution module, and calculates the clothes protection cost of each piece of clothes with different clothes protection numbers according to an energy consumption detection module. A user can conveniently select the number of clothes protectors each time according to the clothes protector cost, optimal nursing parameters of the clothes are obtained through the control execution module, and parameters of a nursing strategy are formulated in combination with a neatness coefficient, an adhesion coefficient, clothes characteristics and nursing machine parameters of the clothes.

The invention discloses a dynamic sterilization method based on cough audio detection and analysis, which comprises the following steps: acquiring hospital audio, dividing the hospital audio into audio segments, identifying audio frames containing cough audio, and merging the audio frames containing the cough audio to obtain cough audio segments; overlapping coughs are separated, and samples of all the single-sound coughs are obtained and correspond to the individuals to which the single-sound coughs belong; judging whether the individual coughs accidentally or not on the basis of the quantity and the time interval of the single-sound coughs, and further judging whether a hospital environment sterilization early warning program needs to be started or not; and for each environment index of the hospital, presetting a corresponding disinfection trigger threshold, and if it is judged that the hospital environment disinfection early warning program needs to be started and the hospital environment index reaches the corresponding disinfection trigger threshold, starting a corresponding disinfection program to complete disinfection of the hospital environment. According to the invention, 'on-demand disinfection 'can be realized accurately and dynamically in real time, and interference to normal medical activities is reduced to the greatest extent while the transmission path of aerosol in a hospital is blocked.

This invention relates to an intelligent decision support system for rectal cancer prognosis integrating digital pathological images, belonging to the field of medical image processing technology. The system includes a data acquisition module for collecting multiple sets of sample data; a feature selection module for identifying multiple key medical imaging features of rectal cancer based on the multiple sets of sample data; a model building module for acquiring a pre-trained deep learning model and constructing a rectal cancer prognosis prediction model based on transfer learning, the pre-trained deep learning model, the multiple sets of sample data, and the multiple key medical imaging features of rectal cancer; an image acquisition module for acquiring pre- and post-operative medical images of the rectal cancer patient to be evaluated; and a recurrence prediction module for predicting the recurrence probability of the rectal cancer patient to be evaluated based on the pre- and post-operative medical images of the patient using the rectal cancer prognosis prediction model. This system has the advantage of improving the accuracy of non-invasive prediction of postoperative recurrence of rectal cancer.

The invention provides a pet self-adaptive feeding recommendation method and system based on AI image analysis, and the method comprises the steps: firstly monitoring food images of a feeding disc of feeding equipment at the moment of food discharge stopping and pet feeding leaving, obtaining a food state image set of the feeding disc, carrying out the AI image analysis of the food state image set of the feeding disc, and obtaining a food state image set of the feeding disc; feeding time and food intake information are extracted, a pet food intake data set is formed, the pet food intake data set is input into a pre-trained feeding demand prediction model, and the next hunger time and food intake prediction result of the pet is obtained through fitting analysis. Self-adaptive feeding recommendation information containing recommended feeding time and recommended feeding amount is generated according to the next hunger time and food intake prediction result of the pet, and finally the self-adaptive feeding recommendation information is pushed to an associated mobile terminal for a user to check and decide whether to execute feeding operation or not. Personalized, intelligent and precise management of pet feeding is realized.

The application discloses a hearing prosthesis remote system integrating machine adjustment and rehabilitation training, comprising a remote platform, a hearing prosthesis and a wireless device, the remote platform comprising a remote debugging module and a rehabilitation module, a multi-round closed loop iterative training link being formed between the components, in each round of the closed loop iterative training link, the wireless device collects rehabilitation feedback signals formed by a user based on a current rehabilitation training scheme; the remote debugging module receives the signals, generates machine adjustment signals based on the rehabilitation feedback signals and historical machine adjustment feedback results, and sends the machine adjustment signals to the wireless device and the rehabilitation module; the wireless device adjusts the hearing prosthesis based on the machine adjustment signals to obtain machine adjustment feedback results of the user; and the rehabilitation module generates a new rehabilitation training scheme for the next round based on the machine adjustment signals and the rehabilitation feedback signals; the system breaks the technical barrier between machine adjustment and rehabilitation, deeply integrates remote machine adjustment and hearing rehabilitation training, provides complete data support for machine adjustment, and realizes accurate machine adjustment.

The invention discloses a new energy vehicle control method based on face recognition, and relates to the field of vehicle control, an intelligent management center is arranged, related user data information and vehicle data information are obtained, and a face reference picture is stored in the user data information; associating a new energy automobile owner with the new energy automobile, and granting the authority of managing the new energy automobile to the automobile owner; an actual face photo is collected and matched with the reference face photo, and whether the door of the user is opened or not is judged according to a matching result; the intelligent management center sets corresponding operation authorities for users, collects corresponding reference operation gestures and face reference gestures, obtains operation instruction information, matches the operation instruction information, generates corresponding operation instructions according to matching results, and executes corresponding functions according to the corresponding operation instructions. The method has the beneficial effect that a function of individually controlling the new energy automobile is provided for passengers in the back row.

The present application provides a personalized lumbar pillow and its design method, design device and storage medium, by obtaining the lumbar lateral X-ray film and waist three-dimensional body surface information model of the subscriber, and importing the three-dimensional modeling software to draw the original lumbar curvature of the subscriber, and obtaining the original lumbar curvature through measurement; the lumbar curvature of the lumbar pillow of the lumbar pillow is constructed in combination with the waist length and the final lumbar curvature of the subscriber, and the upper end closed curve is formed by extending the spline curve along the direction of the 11-12 thoracic vertebra curvature of the subscriber; the lower end closed curve is formed by extending the spline curve along the rear part of the sacrum of the subscriber; the straight line segment at the bottom of the pillow area is constructed according to the height of the lumbar pillow, and a closed curve is formed, and then the lumbar pillow three-dimensional model is obtained through modeling processing, so as to be printed by 3D using flexible materials. The present application can be personalized according to the lumbar situation of different subscribers, so that it can fully fit the physiological curvature of the subscriber.

The application relates to the technical field of large models, and provides a prompt vector generation method, device, equipment and medium, which extracts and embeds the multi-modal information of a target user, generates a personalized query vector carrying the personalized features of the target user, and fuses relevant information of the personalized query vector and a pre-constructed industry knowledge prompt library to generate a target prompt vector of the target user. The target prompt vector is determined in combination with the personalized features of the target user and global user common features, and the personalized and customized processing of the prompt vector is realized. The application can be applied to a financial scene, and when a downstream task such as insurance recommendation generates a personalized execution result for a user according to the target prompt vector, the personalized features of the target user and the global user common features can be simultaneously referred to, the target user's personalization is considered, and the rules or trends gradually presented in the insurance business scene are not deviated from, so that the execution effect of the downstream task is improved.

The application discloses a kind of customized training plan generation methods for operation and maintenance personnel based on performance prism, which comprises the following steps: collecting multi-source heterogeneous demand data of operation and maintenance personnel on multiple platforms, and combining Carnot model and importance performance analysis model for fusion processing, extracting key technology theme through cluster analysis, drawing core training intention and decomposing into key measurement indicators, collecting employee daily operation and maintenance behavior data and calculating ability membership degree vector, combining post demand information, calculating target ability information to be enhanced, generating training content using intelligent workflow engine according to target ability information and key measurement indicators, generating hybrid training plan combining online and offline according to employee historical schedule, issuing the plan to terminal and setting task reminders, which can ensure that training is executed on time, improve training coverage and completion rate, and realize the intelligentization, customization and high efficiency of operation and maintenance personnel training from demand analysis, capability assessment, content generation to plan execution.

The application provides a new energy mine truck thrust rod fatigue life prediction method, belonging to the field of federated learning and application technology. First, a multi-mine area multi-source fatigue feature dataset is constructed. Then, a double-layer neural network structure based on Bayesian modeling is designed, including a sparse prior generation module, a thrust rod time series feature encoding module and a thrust rod residual life Bayesian prediction module, to realize model parameter sparsification, time series feature expression and uncertainty quantification. Further, a graph structure based federated training and information aggregation mechanism is adopted, combined with global aggregation and local graph modeling strategy, to realize knowledge sharing and personalized adaptation between different mine areas. Finally, an online fine-tuning mechanism based on uncertainty driving is proposed, realizing rapid adaptive optimization of the global model in the new mine area environment through Bayesian inference. The method can significantly improve the accuracy, robustness and cross-domain generalization ability of thrust rod life prediction while ensuring data privacy.

The invention relates to the technical field of Internet of Vehicles, and discloses a resource allocation method, a resource request method and a storage medium, and the resource allocation method comprises the steps: obtaining a target instance type requested by a target vehicle-mounted terminal; selecting a basic resource instance matched with the target instance type from the resource pool as a target resource instance, and allocating the target resource instance to the target vehicle-mounted terminal, so that the target vehicle-mounted terminal applies the target resource instance; the resource pool comprises basic resource instances of at least two instance types. According to the application, the basic resource instance of the corresponding type matched according to the request of the target vehicle-mounted terminal can be allocated to the target vehicle-mounted terminal, so that allocation according to needs is realized, and the overall utilization rate of resources is improved.

The application discloses a kind of automated filling and checking method, system, product and medium of insurance information, and it is related to artificial intelligence field.The method comprises the following steps: in response to batch insurance instruction, the insured identity information is received and managed, and the independent data object is constructed to form the insured information set;Age is calculated by traversing the set and analyzing birth date;Age is used as a matching factor, matched with an insurance product rule base, to determine the applicable product plan range and premium calculation factor;Generate and bind a differentiated rule set for each data object;Based on context and differentiated rule set, generate an aggregated interactive interface;Receive input information in the exclusive problem area, and check according to the differentiated rule set;All input information that passes the check is summarized to generate an aggregated insurance order.Implementation of the technical solution provided in the application improves the efficiency of automated processing in the batch insurance scenario.

The invention discloses a control method and device of transcranial electrical stimulation equipment, electronic equipment and a storage medium, the control method of the transcranial electrical stimulation equipment can be applied to the technical field of brain-computer interfaces, the transcranial electrical stimulation equipment comprises a plurality of electrodes, and each electrode is used for being in contact with a target stimulation object. Carrying out transcranial electrical stimulation and electroencephalogram signal acquisition on the target stimulation object; the method comprises the following steps: in a transcranial electrical stimulation process, acquiring electroencephalogram signals acquired by a plurality of electrodes; based on the electroencephalogram signals collected by the multiple electrodes, the contribution degree of each electrode to transcranial electrical stimulation is adjusted; for each electrode, updating a target electrical stimulation parameter corresponding to the electrode based on the initial electrical stimulation parameter corresponding to the electrode and the adjusted contribution degree corresponding to the electrode; and controlling the electrode to perform transcranial electrical stimulation based on the updated target electrical stimulation parameter corresponding to the electrode. According to the transcranial electrical stimulation system and method, individuation and accurate control of each electrode are achieved, and the effect and safety of transcranial electrical stimulation are improved.

The present application relates to the field of intelligent medical auxiliary decision-making technology, and discloses a ladder treatment scheme recommendation method based on asthma control level and drug response phenotype. The present application aims to solve the problem that the existing scheme cannot identify the deep reason of uncontrolled condition, leading to blind step-up treatment. The present application excludes non-compliance interference by checking the drug execution rate, and improves the authenticity of condition assessment. The present application uses environmental exposure characteristics to adaptively correct the exhaled nitric oxide determination threshold, and eliminates the deviation of smoking on inflammation recognition. The present application combines the logic tree voting of multi-dimensional biological indicators to lock the drug response phenotype. Finally, based on the double index of condition state and phenotype, the present application locates the upgrade or transformation treatment path and generates a recommended scheme. The present application realizes the precise typing and differentiated drug administration of asthma treatment, effectively reduces the drug exposure risk of hormone-insensitive patients while ensuring the clinical efficacy.

The invention relates to the technical field of medical information systems, in particular to an artificial intelligence-based psychosomatic medical system, which comprises a network layer; a data acquisition module; the data processing module is connected with the data acquisition module and is used for processing the collected data; the intelligent analysis module is connected with the data processing module and used for analyzing the processed data; according to the system architecture design of the invention, the characteristics of psychosomatic medicine are fully considered, and all the modules are in close cooperation to form a complete diagnosis and treatment closed loop. From data acquisition, intelligent analysis and application output, each link reflects the thought of syndrome differentiation and treatment in psychosomatic medicine. Particularly, in the intelligent analysis module, psychosomatic medical knowledge is innovatively combined with a modern machine learning algorithm, a unique knowledge graph is constructed, psychosomatic medical diagnosis and modern medical standards can be considered at the same time, and a more comprehensive and accurate diagnosis result can be given.

The invention discloses an intelligent terminal and system for evaluating the consciousness state of an unconscious patient based on neurology department monitoring, and belongs to the technical field of medical treatment. According to the method, feature sampling is carried out on the collected neurology department monitoring real-time data of the coma patient, the preset evaluation index of the patient is obtained and analyzed, the key consciousness state risk evaluation parameter is marked as the patient consciousness state basic score of the current monitoring period, and the comprehensive evaluation result of the consciousness state of the coma patient is obtained. An evaluation model is constructed by combining monitoring data collection with key feature extraction, a convolutional neural network of a multi-feature extraction layer and a recurrent neural network of time sequence learning, weights are dynamically corrected by combining individual factors, intelligence and individuation of consciousness state evaluation are achieved, feature vectors of four types of indexes are optimized through the multi-feature extraction layer, and the evaluation accuracy of the consciousness state evaluation is improved. Dynamic correction is carried out by combining the age of the patient, the cause of coma and the monitoring period, so that the evaluation result can reflect the overall consciousness state and highlight the key risk point of the individual.

The application provides a kind of multi-modal interaction data processing method and system of children's picture book reading, it is related to data processing technical field, the method includes: to multi-modal original interaction data set is processed in parallel, extracts and outputs visual semantic feature, interactive speech semantic feature and interactive behavior semantic feature;In visual semantic feature and interactive speech semantic feature, dynamically determine at least three key semantic anchor points, i.e., visual key semantic anchor point corresponds to the core role space coordinate of current picture book page and key text area center point, interactive speech key semantic anchor point corresponds to the core emotion frame timestamp in speech spectrum and question word position;Based on the key semantic anchor point, construct dynamic semantic geometric relationship graph in cross-modal joint feature space.The application can realize the accurate adaptive fusion of cross-modal feature, effectively improve the accuracy of children's picture book reading interaction data processing and the adaptability of interactive response.

The invention relates to the technical field of filter elements, in particular to a mining filter element protective cover integrated with an NFC chip and a using method thereof.The mining filter element protective cover comprises a mask body and a filter element, and the filter element comprises a filter material layer and a supporting frame arranged on the periphery of the filter material layer; an electronic identification chip is arranged in a non-core filtering area on the edge of the filter material layer, and a microporous breathable film for packaging the electronic identification chip is arranged on the surface of the side, attached to the mouth and the nose, of the filter material layer; a visual identification code associated with the information of the electronic identification chip is arranged on the surface of the microporous breathable film; the visual identification code and the electronic identification chip jointly form a unique identity label of the filter element; through double identification of the electronic identification chip and the visual identification code, the anti-counterfeiting property and the tamper-proof property of the identity of the filter element are improved; the air permeability and filtering performance of the filter element are not influenced after the chip is integrated; by binding the filter element with the identity of the miner, individualized and traceable analysis of dust exposure data is realized, and real and continuous data is provided for occupational health management of the miner.

The application discloses a kind of personalized intelligent recipe recommendation system based on user health information, comprising: user information management module, for obtaining and managing the health information of user;Energy calculation module, for calculating ideal body weight, body type classification, basal energy requirement, blood sugar adjusted energy requirement and meal nutrient target according to user information;Food database, for storing the nutrient composition and type attribute of food;Recipe generation module, for selecting food combination from food database according to meal type and nutrient target, and generating personalized recipe using multi-nutrient synergistic optimization intelligent algorithm.The present application is based on the principle of nutrition, on the basis of personalized health management, increase the precise energy calculation function based on ideal body weight and body type classification, realize precision and individualization in energy calculation, nutrient optimization, food selection and other multiple links.

The embodiment of the invention provides a vehicle control method, a vehicle and a computer readable storage medium, and the method comprises the steps: obtaining state perception data of the vehicle, the state perception data comprising physiological signal data and operation behavior data of a vital sign object in the vehicle; performing feature extraction on the state sensing data to obtain multi-modal feature data; state identification is carried out based on the multi-mode characteristic data, a state prediction result is obtained, the state prediction result is used for determining an auxiliary control mode corresponding to the vehicle, and the auxiliary control mode is used for adjusting driving auxiliary function parameters and cabin environment response of the vehicle; and controlling the vehicle by using the state prediction result. According to the invention, the technical problems of single monitoring means, insufficient sensing accuracy and delayed safety response in the prior art are solved.

This disclosure provides a function processing method, apparatus, device, storage medium, and program product, relating to the field of computer technology. The method includes: in response to a trigger operation, acquiring the current time; determining a target trigger function to be executed based on the current time, wherein the target trigger function is one or more trigger functions associated with the current time; and executing the target trigger function. This method allows users to command a terminal to execute time-configured trigger functions through simple trigger operations, greatly simplifying the operation process. This method can also flexibly respond to diverse function execution needs; different times can be associated with different trigger functions, allowing the same trigger operation to achieve different functions at different times, realizing personalized and time-sharing function execution, and improving user convenience and satisfaction with function execution.

The invention discloses a closed-loop binaural vagus nerve stimulation system integration and a closed-loop binaural vagus nerve stimulation method for neural rehabilitation. The system integration comprises a host, a binaural stimulation module, a rehabilitation training execution module and a myoelectricity acquisition module. The rehabilitation training execution module integrates a myoelectricity synchronous hemiplegic upper limb rehabilitation system (including a visual assistance and mirror image training subsystem), a dysphagia synchronous training system and a breathing pairing synchronous training awakening system. When the system works, a corresponding mode is started according to an evaluation result of a patient to guide the patient to execute a target training action through a healthy-side target muscle group; a myoelectricity acquisition module synchronously acquires a myoelectricity signal generated by the action; the host processes the signals, generates or adjusts electrical stimulation parameters of the vagus nerves of the two ears in real time according to the signals, and applies electrical stimulation in a target time window of action execution, thereby forming closed-loop nerve regulation and control with healthy-side myoelectricity as real-time feedback. According to the invention, accurate and personalized synchronization of multi-mode rehabilitation training and central nervous regulation and control is realized.

The invention relates to the technical field of retail inspection, and particularly discloses a retail store inspection method and system based on a configurable questionnaire, and the method comprises the steps: collecting the multi-dimensional state data of a target store in real time, and enabling the multi-dimensional state data to comprise static attribute data, dynamic business data flow and environment context data; performing standardization processing on the multi-dimensional state data to generate a target store state vector; based on a pre-trained optimal strategy curved surface model, the target store state vector is mapped to an inspection strategy vector space, a recommended inspection strategy vector is obtained through calculation, and the optimal strategy curved surface model represents a nonlinear mapping relation between the store state vector space and the inspection strategy vector space; according to the recommended inspection strategy vector, dynamically assembling and generating an inspection questionnaire from the modular questionnaire component library, and generating a corresponding inspection task execution scheme; and dynamic strategy optimization based on state perception for retail store inspection is realized.

The utility model discloses a pelvic floor muscle exercising device for stress urinary incontinence, relates to the technical field of exercising equipment, and solves the problems that some existing pelvic floor muscle exercising auxiliary instruments in the market are limited in function, so that a user often needs to purchase various instruments, the cost is high, the occupied space is large, and the exercising complexity is increased. A pelvic floor muscle exercising device for stress urinary incontinence comprises a fixed seat; the fixing base is of a rectangular plate structure. A supporting rod is fixedly arranged at the top of the rear side of the fixed seat; the supporting rod is of a cylindrical structure. The two sides of the supporting rod are each fixedly provided with a set of fixing plates of a T-plate structure. Two second sliding rods of L-shaped rod structures are arranged in the circular through groove in the front side of the fixing plate in a sliding mode. Connecting plates of arc-shaped plate structures are fixedly arranged at the inner side ends of the two second sliding rods. The sitting posture exercise mode and the standing posture exercise mode are integrated, a user does not need to purchase instruments with different functions, and cost and space are greatly saved.