1000 results about "Nursing staff" patented technology

The invention discloses a nursing pressure real-time monitoring system and method based on multi-modal data. The system comprises a data acquisition module, an intelligent analysis module, an analysis module and a real-time feedback module. The data acquisition module synchronously acquires physiological data, behavior activity data and environment situation data of nursing personnel and forms a nursing signal; the analysis module receives the nursing signal from the data acquisition module, receives the dynamic situation information from the intelligent analysis module, and generates a pressure state signal containing pressure event evaluation; the real-time feedback module receives the pressure state signal containing the pressure event evaluation from the analysis module, and generates and outputs a real-time feedback signal based on the pressure state signal. According to the nursing pressure real-time monitoring system and method based on the multi-modal data, the problem that traditional wearable equipment only collects physiological behavior data and cannot be associated with specific nursing situations such as drug administration operation and patient first aid can be solved.

The invention discloses a PICC catheter real-time data acquisition-based nursing quality monitoring system, and relates to the technical field of nursing quality monitoring, the system comprises a data acquisition module, a real-time analysis module, a long-term tracking module, a risk dynamic evaluation module, a nursing intervention module and a patient monitoring module, and the modules are in electric signal connection. According to the nursing quality monitoring system based on PICC real-time data collection, by continuously monitoring physiological parameters of a patient and PICC related data, nursing personnel can respond to demand changes of the patient in time, PICC related complications can be effectively recognized and prevented, abnormal conditions can be found in time, intervention measures are taken, and the nursing quality is improved. Therefore, the risk of complications is reduced, the safety of the patient is improved, nursing personnel can make a personalized nursing plan more accurately, the pertinence and effectiveness of nursing are improved, and the treatment effect of the patient is improved.

The invention discloses a medical care data management system based on big data calculation, and relates to the technical field of data management, and the system comprises a data collection module, a data security module, a data storage module, a care quality analysis module, a care aid decision support module and a data visualization module. According to the medical care data management system based on big data calculation, by integrating and analyzing massive medical care data, more scientific and accurate decision support is provided for nursing personnel, multi-dimensional nursing data of a patient is collected and is compared and analyzed with a standardized nursing knowledge base, differences and defects in a nursing plan are quickly identified, and the medical care data management system is suitable for medical care. And the deviation of the nursing plan of the patient is determined through data analysis, and prospective decision-making suggestions are provided for nursing personnel, so that the subjectivity and uncertainty of manual judgment are reduced, and the efficiency and accuracy of nursing decision-making are improved.

The invention provides an intracranial neuron electrical stimulation system for treating epilepsy and other brain diseases involving epileptic seizure, which can immediately apply intracranial neuron electrical stimulation to the interseizure epilepsy activity in a personalized manner after detecting the interseizure epilepsy pattern each time. And the stimulation is activated by intracranial electroencephalogram (EEG) detection. The intracranial stimulation for epileptic activities in the epileptic seizure period continuously acts along with time, the forming process of an epileptic network can be blocked, the neuronal super-synchronization risk is reduced, and therefore the control effect on epileptic seizure is improved. The invention also includes the use of nerve adjustment biomarkers, thereby dynamically optimizing the detectability and providing more accurate overall assessment for the patient's treatment progress. Finally, according to the scheme, by detecting the intracranial EEG mode and the high-risk state mode (such as the epileptic state and the sudden accidental death risk in epilepsy) in the attack period, an instant alarm is given to the patient / nursing personnel, and it is ensured that safe treatment measures are taken for the patient in time.

The invention relates to the technical field of medical care, in particular to a real-time nursing quality monitoring and alarm system which comprises a data acquisition module, a real-time monitoring module, an intelligent analysis module, an alarm generation module, a decision support module and a visualization module. The real-time monitoring module monitors acquired nursing quality data in real time, the intelligent analysis module processes and analyzes the data and identifies potential problems and trends, the alarm generation module generates alarms and reminds nursing staff to take measures in time, and the decision support module provides suggestions and decision support for optimizing the nursing process. And the visual module provides a user interface, so that nursing personnel can check monitoring data, alarm information and decision suggestions conveniently. Through comprehensive data collection and an intelligent analysis and early warning mechanism, the nursing quality monitoring and management level is improved, potential problems are found and processed in time, and the overall level of nursing service and the patient satisfaction degree are improved.

The invention discloses a caregiver recommendation algorithm according to a matching degree, and relates to the technical field of nursing. The method comprises the following steps of patient information collection: collecting basic information of a patient, obtaining geographical location information of the patient, determining a city and a detailed address of the patient, guiding the patient to describe nursing requirements in detail, and inputting information of a caregiver through a user side information collection module; and the caregiver fills in own professional skill information which covers basic nursing skills, professional nursing specialists and skills in the special nursing field, and uploads related certificate qualification certificates. Through deep analysis and processing of the multi-dimensional demand information of the patient and the comprehensive information of the nursing staff, the intelligent matching model is used to accurately calculate the matching degree, the nursing staff highly meeting the demand of the patient can be screened for the patient, the pertinence and effectiveness of the nursing service are greatly improved, and the problems of poor nursing effect and the like caused by mismatching are avoided.

The invention discloses a severe clinical health care sensing system and method based on virtual reality, and belongs to the field of virtual reality. Injury information of a patient and the influence of a nursing action selected by a corresponding nurse on an injury position are obtained and imported into an action injury position influence analysis strategy for injury position influence analysis; the method comprises the following steps: acquiring physiological information of a corresponding patient to carry out physiological feature influence analysis, acquiring an injury position influence analysis result of a corresponding nursing process and a physiological feature influence analysis result, and carrying out nursing action matching analysis on the injury position influence analysis result and the physiological feature influence analysis result. The risk caused by the nursing action is accurately analyzed according to the vulnerability degree characteristic of the wound; according to the application, the physical abnormality of the patient is considered while the secondary injury of the wound caused by the nursing action is evaluated, and the danger caused by the nursing action is comprehensively judged.

The invention discloses a respiratory training auxiliary device for critical medicine patients, and relates to the technical field of medical assistance, the respiratory training auxiliary device comprises a device shell and a supporting plate, an air pump is fixedly mounted on the upper surface of the device shell, an operation table is fixedly mounted on the inner side surface of the device shell, and an auxiliary mechanism is arranged between the air pump and the operation table; a device shell is fixedly installed on the upper surface of the supporting plate, a groove is formed in the left side of the device shell, a fixing support is fixedly installed on the inner side face of the device shell, and a breathing mechanism is arranged between the device shell and the fixing support. According to the breathing training auxiliary device for the critical medicine patient, oxygen is transmitted into two sets of closed boxes through a connecting pipe, a first spring and a second spring repeatedly press an air bag to do telescopic motion, breathing of the patient is conveniently adjusted, the air bag is limited through a limiting disc, the air bag is prevented from jumping too fast, and the device shell is fixedly supported through a supporting plate; the pulley block pushes the device shell to move, so that the strength of nursing personnel is saved.

The invention provides a question and answer interaction virtual case development method for nurse inquiry training, which comprises an original case history module for constructing a virtual case text development framework based on a functional health form, a nursing inquiry teaching status and clinical nursing evaluation, and establishing an original case history; the initial response text module is used for determining the development sequence and inquiry elements of each unit, and constructing an initial response text with the guidance of cultivating clinical thinking ability, nursing science professional attainment and humanistic attainment; and the final response text module is used for constructing a final response text through the subject term and the subject term combination rule based on the initial response text. According to the method, all units of the virtual case text development framework are covered, and content comprehensiveness is guaranteed; an initial response text system is designed for cultivating clinical thinking ability, nursing science professional accomplishment and humanistic accomplishment, and educational guidance is achieved; on the basis of establishing a subject term library and designing a subject term combination rule, a response text is perfected, so that the response accuracy of the virtual patient is ensured.

The invention relates to an infection risk digital diagnosis and evaluation method integrated in a medical information system, and belongs to the technical field of risk evaluation. The method comprises the following steps: acquiring three-tube risk screening data, and automatically generating a risk score through a medical information system according to the three-tube risk screening data; a three-management early warning threshold value is preset, and the medical information system obtains continuous prediction data through a monitoring early warning model according to the risk score and the three-management early warning threshold value; obtaining patient infection risk digital diagnosis data through a risk prediction model according to the continuous prediction data; and obtaining a personnel optimization scheduling result through a nursing personnel scheduling model according to the patient infection risk digital diagnosis data. The infection risk assessment integrated in the medical information system is realized, the accuracy of infection risk assessment is improved, and the nursing service is improved.

The invention relates to the technical field of medical care, and discloses an operating room nursing task automatic scheduling system, which is characterized in that a data acquisition module acquires initial data related to an operating room in real time; the task analysis module is used for receiving the initial data acquired by the data acquisition module and analyzing the nursing task; the task scheduling module is used for automatically distributing the nursing tasks according to a result of the task analysis module, generating a task scheduling scheme and sending the task scheduling scheme to corresponding nursing personnel and related departments; the real-time monitoring module performs data interaction with a mobile terminal carried by a nurse and monitoring equipment in an operating room to monitor the execution condition of a nursing task in real time, and when an abnormal condition occurs in the task execution process, an alarm is given out immediately; the feedback and optimization module evaluates and optimizes the task scheduling scheme and adjusts a task allocation strategy; the overall operation efficiency of the operating room is improved, and the professionality and high efficiency of operation cooperation work are ensured.

The invention discloses an intelligent nursing record generation method and device, and the method comprises the steps: obtaining nursing voice data, and carrying out the noise reduction and sound enhancement processing to obtain a preprocessed voice stream; a speech recognition technology fusing ECAPA-TDNN and an x vector is adopted to recognize medical terminologies, and a text transcription result is generated; recognizing the voice of the target nurse from the preprocessed voice stream and the transcription result in combination with a speaker-independent model and a speaker condition model to obtain a voice transcription text of the voice; performing voice analysis and structured processing on the text by using a multi-modal self-supervised learning model and a hierarchical CNN-BiLSTM framework to obtain a structured text with clinical semantic features; key clinical information is extracted in combination with the medical ontology knowledge base, and a nursing record element set is obtained; and based on the nursing record element set, automatically generating a nursing record meeting the specification. According to the invention, the automatic generation from the nursing voice to the standardized nursing record is realized, and the efficiency and accuracy of the medical nursing record are improved.

The invention relates to the technical field of clinical nursing, in particular to a clinical nursing system for interventional operations, which can accurately identify and predict potential complications by performing deep neural network analysis in combination with preoperative medical history, intraoperative real-time physiological data and operation types. It is ensured that a nursing scheme can be finely adjusted based on individual differences of patients, complex physiological data can be processed through a deep neural network, key physiological data are recognized from the complex physiological data, the scheme is dynamically adjusted in the nursing process through a long-short-term memory network, and the nursing accuracy is improved. The change trend of data in the operation is deeply mined, the fluctuation of physiological indexes is tracked, the abnormity is timely identified, the potential risk is predicted, the nursing decision and the physiological state of the patient can be synchronously updated, the working efficiency of nursing personnel is optimized, and the postoperative recovery effect and comfort of the patient are improved.

The invention provides a big-data-based Alzheimer's disease old-age care platform management method and system, and relates to the technical field of old-age care platform management.The method comprises the steps that patient behavior data information is received, missing data points are deduced according to pre-stored patient behavior file historical behavior pattern data and patient behavior data information, and the missing data points are sent to a server; by evaluating the reliability degree of the event chain and comparing the event chain with a dynamically generated reliability evaluation threshold value, when a comparison result reaches an early warning standard, early warning information with a reliability quantitative index is generated, and the problem that an existing platform is poor in reliability under a non-ideal operation condition is effectively solved. The problems of reliable transmission and accurate interpretation of key information are solved, and early warning failure caused by data deviation or missing is avoided, so that the nursing quality and safety of the Alzheimer's disease patient are remarkably improved, and the optimal time for early intervention and intervention is provided for nursing personnel.

The invention relates to the technical field of nursing monitoring, in particular to a nursing monitoring system for collecting postoperative data of a patient based on myoelectricity sensing. The system comprises a frequency calculation unit, a power quality unit and a monitoring scheme unit. The active degree of the muscle signals around the postoperative wound of the patient is monitored through the broken line and the horizontal reference line in the postoperative wound electromyogram of the patient, when the root mean square point of the corresponding electromyographic signal in the broken line is higher than the horizontal reference line, it is monitored that the active degree of the muscles around the postoperative wound of the patient is increased, and the postoperative wound recovery state of the patient is good; the postoperative wound recovery condition of the patient is monitored in real time through the electromyogram, unnecessary examination and intervention can be reduced, a nurse can accurately judge the muscle activity condition of the patient according to the result of the electromyogram, and pain and burden brought to the patient by excessive examination are avoided. Meanwhile, unnecessary measures can be avoided, the medical cost is reduced, and the nursing efficiency is improved.

The invention discloses a chronic disease patient nursing management system based on big data, which relates to the technical field of medical nursing and comprises a disease course development analysis unit, a patient health analysis unit, an online diagnosis and treatment unit, a nursing management unit, a nursing recommendation unit and a nursing correction unit. According to the invention, the disease course development model of the chronic disease is constructed according to the disease course development data, the disease development evaluation trend is graded and judged according to the physiological data of the patient, the judgment result is corrected through the online diagnosis and treatment unit, and the matched nursing list is obtained according to the judgment result. The nursing list is sent to a remote medical terminal of a nurse and an intelligent mobile terminal of a family member of the chronic disease patient, physiological data of the patient is obtained after each nursing judgment period is completed, the correction trend of the nursing influence coefficient is judged, and the effect of the nursing scheme is evaluated. The nursing list is timely corrected according to the chronic disease development process of the patient, the disease development condition of the patient is better matched, and chronic disease deterioration is inhibited.

The invention discloses a hospital nursing quality evaluation system based on hospital information terminal data, and relates to the technical field of medical information, and the system comprises a data acquisition module which extracts index data based on a hospital terminal, and the index data comprises patient satisfaction subjective index data, nursing personnel working life data, performance data and adverse event occurrence probability; after preprocessing the data, constructing a data set; and the analysis module performs correlation analysis on the data of the data set based on the Pearson's correlation coefficient, constructs a nursing quality evaluation model through a neural network, and performs training optimization on the quality evaluation model. The comprehensive evaluation level is efficiently and objectively output through the evaluation module, the result is presented through a visual chart, managers can conveniently master the comprehensive evaluation level, hospitals accurately position nursing service short boards according to the evaluation result, targeted optimization is implemented, the nursing system is continuously improved, the requirements of patients are met, and it is ensured that the nursing quality is kept at a high level; and data in a hospital can be fully utilized.

The invention relates to the technical field of data management, in particular to a pressure injury information management system which comprises a patient risk analysis module, a patient screening module, a nursing early warning module, an injury analysis module, an action guidance module and a statistical analysis module. According to the method and the system, the stress injury risk level of each patient is calculated by integrating the medical record data with the lying time, age and basic illness state of the patient, so that the accurate assessment of the risk state of the patient is remarkably improved, the demand of manual intervention is reduced, the information transmission speed is also accelerated, and the risk assessment efficiency is improved. According to the method and the system, nursing personnel can obtain key early warning information in real time, take corresponding prevention measures and collect and identify injury photos to further make injury degree assessment more accurate and timely, provided nursing action guidance is formulated based on actual injury conditions, the nursing working process is optimized, and the overall efficiency and safety of medical services are enhanced.

The invention discloses a hair washing device for a bedridden patient, which comprises a head cover, an elastic sealing sleeve is connected to the mouth of the head cover, the elastic sealing sleeve is formed by connecting a face sealing belt and a neck sealing belt, and a lap joint sticking buckle is arranged on the neck sealing belt; a plurality of grabbing and washing devices are uniformly arranged on the inner side surface of the head cover; each grabbing and washing device comprises two elastic claws which are distributed in a V shape and a micro motor for driving the elastic claws to do opening and closing movement; the hair washing device for the bedridden patient further comprises a power adapter connected with the micro motors. Water spraying openings are evenly distributed in the head cover, a water cavity is formed in the outer side of the head cover, and a water inlet connector and a water outlet connector are connected to the water cavity. The hair washing device for the bedridden patient can help nurses to wash hair of the bedridden patient, and the nursing workload can be relieved.

The invention discloses an intelligent tracking method and system for the rehabilitation state process of an orthopedic patient, and relates to the technical field of medical health. By integrating the wearable device, vital signs, motion states and pressure distribution data of a patient are collected and analyzed in real time, the rehabilitation state of the patient can be accurately monitored, and dynamic progress evaluation is provided; based on a rehabilitation progress evaluation result, the system can automatically generate a personalized rehabilitation exercise scheme, exercise intensity, exercise frequency and a training plan are adjusted according to specific requirements of each patient, and high efficiency and safety of the rehabilitation process are ensured; through analysis of vital sign fluctuation, motion precision and plantar pressure balance, the system can identify potential risk factors in real time and trigger early warning in time to help a patient and nursing personnel thereof to take necessary intervention measures, and smooth proceeding of the rehabilitation process is ensured.

The present invention relates to the technical field of aerosol drug delivery, and discloses a cavity aerosol drug delivery device for elderly care, comprising a main body, a detachable aerosol canister disposed inside the main body, a spray valve for inhaling drugs from the aerosol canister disposed on the upper side of the main body, a main cover fixedly disposed on the left side of the spray valve, and a fixed cover fixedly mounted on the left side of the main cover. The cavity aerosol drug delivery device for elderly care, by respectively placing two support parts against the upper and lower gums of the patient's mouth, and using a support rod to drive the support parts to move relative to each other, can achieve the purpose of opening the elderly patient's mouth, which is beneficial for nursing staff to administer drug treatment to the elderly patient, solves the problem that the elderly patient's mouth is difficult to open on its own, resulting in low drug delivery efficiency, further improves the treatment effect on the elderly patient, and is beneficial for the elderly patient to recover as soon as possible.

The utility model relates to a rolling type urination delivery mattress which comprises a bed body and a delivery mattress arranged on the bed body, and further comprises driving frame sets arranged on the two sides of the bed body. The driving roller is arranged on one of the driving frame groups; according to the rolling type urine delivery mattress, the driving frame sets are arranged on the two sides of the bed body, the driving frame sets are used for connecting the driving roller and the driven roller, and meanwhile the two ends of the delivery mattress are wound on the driving roller and the driven roller respectively. When the puerperal mattress is replaced, the puerperal mattress can be automatically wound on the driving roller only by operating the driving frame set to rotate the driving roller, and meanwhile, the driven roller can synchronously release the same amount of puerperal mattress. By means of the design, the patient is effectively prevented from being repeatedly moved when the puerperal mattress is replaced, interference to the patient is greatly reduced, multiple nurses do not need to be matched with one another, and the efficiency and convenience of nursing work are remarkably improved.

The invention provides an intensive care nursing feeding device, and relates to the technical field of medical instruments, the intensive care nursing feeding device comprises a base, a lifting part movably arranged on the top of the base, a storage part arranged on the top of the base, and a flow control part arranged on one side of the lifting part and connected with the storage part; the lifting part is movably connected with the flow control part through an angle adjusting part, and a conveying pipeline used for conveying food is arranged on one side of the flow control part; the flow control part is used for accurately controlling the food flow; through the arrangement of the flow control component and the pressurizing component, the feeding speed and the food flow are accurately controlled, complications are reduced, and the comfort level of a patient is improved; through the arrangement of the lifting part, the angle adjusting part and the rotating table, a patient can be fed at any angle, the workload of nursing personnel can be relieved, and the nursing personnel can efficiently conduct feeding work.

The invention relates to a clinical symptom nursing strategy intelligent recommendation system and method based on artificial intelligence, and the method combines historical clinical symptoms and nursing big data to construct a corresponding nursing strategy intelligent recommendation model, thereby enabling the nursing strategy intelligent recommendation model to recognize the feature relationship between different symptom features and corresponding nursing strategies. And enabling the model to recognize the symptom characteristics of a clinical patient and intelligently recommend a corresponding nursing strategy. The system can also combine model output and nurse feedback, fuse and recommend a clinical symptom nursing strategy most related to patient symptoms, so that nurses can make preliminary assessment and deal with the appearing symptoms to confirm nursing problems, sort critical and urgent conditions, develop nursing measures, highlight nursing key points and improve the nursing efficiency. And potential complications can be prevented or treated in time. In clinical nursing work, clinical nurses can be effectively guided to perform judgment thinking and carry out predictive nursing, so that the nursing work is homogenized, and the nursing quality and safety are improved.

The invention discloses an anesthesia reviving room risk assessment system for postoperative nausea and vomiting prediction, relates to the technical field of postoperative nausea and vomiting prediction, and aims to perform multi-modal fusion on clinical features of a patient and brain function signals to realize basic probability calculation of postoperative nausea and vomiting risks, and introduce real-time dynamic physiological parameters as regulatory factors to realize postoperative nausea and vomiting risk prediction. And performing adaptive adjustment on the basic prediction result to generate a comprehensive risk probability value. The system can collect and process data in real time after a patient enters an anesthesia reviving room, and dynamic and personalized risk assessment is achieved. Compared with a traditional scoring method which only depends on static clinical features, the method has the advantages that tiny fluctuation of the postoperative physiological state of the patient can be captured, prediction precision and timeliness can be improved, clear decision support can be provided for nursing staff, and therefore preventive intervention measures are optimized, and the occurrence rate of complications is reduced.

The present application relates to the technical field of clinical nursing, in particular to a clinical nursing system for interventional surgery, in the present application, through the combination of preoperative medical history, intraoperative real-time physiological data and operation type, depth neural network analysis can accurately identify and predict potential complications, and the nursing plan can be adjusted according to the individual differences of patients, the nursing plan can be adjusted according to the individual differences of patients, the depth neural network can process complex physiological data and identify key physiological data, the long short-term memory network can dynamically adjust the scheme in the nursing process, the change trend of intraoperative data is deeply mined, the physiological index fluctuation is tracked, the abnormality is identified in time and the potential risk is predicted, the nursing decision can be updated synchronously with the physiological state of the patient, the working efficiency of the nursing staff is optimized, and the postoperative recovery effect and comfort of the patient are improved.

The utility model relates to the technical field of medical nursing, and discloses an anti-extubation limb fixing pad for ICU (intensive care unit) nursing, which comprises a pad strip, a tension sensor is arranged on one side of the pad strip, and a box body is arranged at the top of the tension sensor; velcro b is sewn on one side of the top of the filler strip, and Velcro a is sewn on one side of the bottom of the filler strip. And key rings are fixedly mounted on two sides of the tension sensor. Through the arrangement of the tension sensor, the key chain and the alarm, when a patient applies force to pull the filler strip, the tension detected by the tension sensor is larger than a set threshold value, the patient is judged to be abnormal, the processor gives an instruction, the alarm gives out an alarm sound, and nursing personnel are reminded to go to check the abnormal condition in time. The device can be provided for patients to call nurses, and is suitable for patients who cannot speak.

The invention relates to the technical field of nursing manpower allocation, and discloses a man-hour analysis and post evaluation-based nursing manpower allocation system, which comprises a data acquisition module, a data analysis module and an allocation model module, and is characterized in that the data acquisition module, the data analysis module and the allocation model module can determine a development environment and a technical framework through Python; establishing a basic module; the data acquisition module is mainly used for collecting patient data, nursing personnel data and hospital data. According to the nursing manpower allocation system based on man-hour analysis and post evaluation, by scientifically and reasonably allocating nursing manpower resources and optimizing man-hour arrangement, the workload of nursing personnel can be effectively reduced, and the working efficiency is improved; a hospital can utilize existing human resources to the maximum extent on the premise of ensuring the medical service quality, resource waste is reduced, and the overall operation efficiency is improved; and meanwhile, the optimal configuration scheme is beneficial to reducing the occupational tireness rate and loss rate of nursing personnel.

The invention relates to the technical field of intelligent medical care, and discloses a drainage port nursing recommendation method and system for a patient with bile leakage. The system comprises a data acquisition module used for acquiring bile drainage data and state data of skin around a drainage port in real time; the cloud decision module is internally provided with a nursing scheme recommendation model associated with a bile leakage nursing knowledge graph, and is used for carrying out fusion analysis on the multi-modal data and generating a personalized nursing plan; the local execution terminal is used for receiving and displaying the nursing plan and guiding nursing personnel to execute and record actual nursing operation data; and the closed-loop feedback module is used for returning the actual execution data and the post-nursing state data so as to optimize the nursing scheme recommendation model and the bile leakage nursing knowledge graph. The technical problems that in traditional nursing, evaluation is subjective, decision-making depends on experience, execution is not standard, and knowledge is difficult to accumulate are solved, and standardization, individuation and continuous self-optimization of bile leakage drainage opening nursing are achieved.

The invention discloses a Doppler ultrasonic diagnosis system for dysphagia detection, and belongs to the technical field of Doppler ultrasonic diagnosis. The method comprises the following steps: respectively measuring the geniolingual muscle movement, swallowing time, tongue movement and the distance between the tongue bone and the thyroid cartilage of a stroke patient in a B-type ultrasonic mode and an M-type ultrasonic mode, recording test data after multiple swallowing tests, calculating to obtain an average value of the geniolingual muscle movement, the swallowing time, the tongue movement and the distance between the tongue bone and the thyroid cartilage, and calculating the average value of the geniolingual muscle movement, the swallowing time, the tongue movement and the distance between the tongue bone and the thyroid cartilage. Then the measurement results of the swallowing time and the distance between the tongue bone and the thyroid cartilage are used as evaluation and diagnosis bases for diagnosis, so that objective and accurate diagnosis bases are provided for the treatment and rehabilitation process of the swallowing dysfunction of a stroke patient, and nursing personnel can evaluate and diagnose the swallowing dysfunction after the stroke by using a simple B-ultrasonic instrument at the bedside; and the diagnosis accuracy of medical personnel is improved.