643 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 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 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 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 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 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 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 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.

The utility model relates to the technical field of urine collection, and discloses a female urine collection device which comprises a collection bag, the top of the collection bag is in threaded connection with a nut, the interior of the nut is in threaded connection with a bag opening mechanism, and the top of the bag opening mechanism is fixedly connected with a sealing mechanism. The bag opening mechanism comprises a urine outlet hard pipe, the urine outlet hard pipe is in threaded connection with the interior of a nut, the top end of the urine outlet hard pipe is fixedly connected with an annular chuck, the top end of the interior of the annular chuck is fixedly connected with a T-shaped supporting cylinder, and the bottom end of the interior of the T-shaped supporting cylinder is fixedly connected with a bottom connecting plate. According to the urine collecting device for women, when a nurse separates and replaces the collecting bag after the collecting bag is full of urine, the leakage phenomenon can be avoided, and in addition, the phenomenon that the sealing effect between the collecting bag and the sealing mechanism is reduced due to the fact that the collecting bag is frequently detached, installed and replaced is avoided; and therefore, the use efficiency of the device can be improved.

The invention provides a pension service supervision method and system based on an image recognition AI model algorithm. The method comprises the following steps: aiming at respiratory arrest, pressure sores and limb stiffness risks in a bedridden old-age care scene, firstly, establishing a physiological abnormality library containing parameters such as a respiratory rate threshold value and a body pressure critical value; a physical sign monitoring device is deployed to collect body pressure hot area distribution data of the bedridden person in real time, breathing interval abnormity, heartbeat attenuation and body pressure exceeding areas are analyzed through an AI model, and a retention risk index is generated. And when the monitoring data exceeds an abnormal library threshold value, triggering multi-modal early warning information, fusing risk area positioning, abnormal duration and temperature gradient change, outputting a multi-modal early warning report combining images and texts, and guiding the nursing personnel to perform targeted intervention. According to the technical scheme provided by the invention, real-time monitoring and multi-mode risk early warning of health hidden dangers in bed are realized, the occurrence rate of complications such as respiratory arrest and pressure sores is reduced, and the precision and response efficiency of nursing for the aged are improved.

The invention relates to the technical field of medical care, in particular to a method for dynamically adjusting the body position of a bedridden patient based on infrared sensing, which comprises the following steps: S1, three-dimensional infrared monitoring: collecting body surface temperature distribution and body contour data of the patient in real time through a plurality of infrared thermal imaging sensors and 3D depth cameras distributed around a sickbed; an eight-channel FLIR A315 thermal imaging sensor (with the precision of + / -0.1 DEG C) and an Intel RealSense depth camera are adopted to construct a three-dimensional monitoring network, sub-millimeter level fusion of a temperature field and body data is realized through non-local mean filtering and an ICP point cloud registration algorithm, the recognition precision of a pressure concentration area is improved to 3 mm < 3 > voxel units and is improved by more than three times compared with a traditional pressure sensing mattress (with the resolution being greater than or equal to 1 cm), and the recognition precision of the pressure concentration area is improved by more than three times compared with that of a traditional pressure sensing mattress (with the resolution being greater than or equal to 1 cm). The temperature gradient monitoring sensitivity reaches 0.1 DEG C / cm, the potential stress injury risk is found 4-6 hours in advance, the risk early warning accuracy rate of data display of a certain hospital in Hainan reaches 92.3%, continuous unattended monitoring is conducted for 24 hours, and the workload of manual temperature measurement of nursing staff is reduced by 80% or above.

The invention discloses a colorectal cancer stoma nursing data processing method and device, and relates to the technical field of nursing data processing, and the method comprises the steps: carrying out the time alignment and abnormality elimination of a stoma part sensor signal, image data and subjective feedback of a patient, and forming initial data; the reading is corrected by using the environmental parameters, cross-source verification is carried out, and calibration verification data is output; then, individual baseline features are constructed, the comprehensive risk amount is calculated, and a self-adaptive threshold evaluation record is generated in combination with a first-order iteration dynamic threshold strategy; and when the risk quantity exceeds a threshold value, an alarm is triggered, and the nurse locally verifies and returns a correction factor, so that the model is gradually adaptive. The method can improve the recognition and response efficiency of acute problems such as skin injury, is more accurate in use in various clinical scenes and patient cases, and remarkably improves the stoma nursing quality.

The invention relates to a multi-modal data driven caregiver training method and device, equipment and a medium, and the method comprises the steps: eliminating the clock deviation of multi-source equipment through the synchronous processing of joint movement, a voice instruction and hand pressure data, and generating a time alignment data set; fusing the nursing action dynamic features and the pressure gradient features by using a time sequence neural network, and constructing a space-time fusion sequence; the joint angle change rate and the pressure parameter are decoded based on a probability model, and an operation continuity index is quantified in combination with time window integration; and finally, identifying weak links of skills according to the mechanical parameter sequence, and matching a clinical standard course library to generate a personalized training instruction. According to the method, the problems of action-instruction collaborative distortion, one-sided single-mode evaluation and feedback disjunction caused by multi-source data time delay are solved, real-time accurate evaluation and immersive adaptive training of nursing operation biomechanical parameters are realized, and the venipuncture stability and the pressure sore prevention force control capability are remarkably improved.

The invention relates to a stress injury assessment opportunity prediction method based on a Braden scoring system and an RNN model. The method comprises the following steps: collecting a Braden index and other related data of a patient; preprocessing the data; performing feature extraction on the collected data, and constructing a feature vector; an RNN model is trained through the feature vectors, and a stress damage risk prediction model is formed; inputting the real-time data of the patient into the trained stress injury risk prediction model, predicting the risk probability of the patient, and automatically determining the optimal time of the next evaluation according to a preset threshold value; and result output and feedback: feeding back the prediction result and the suggested evaluation opportunity to nursing personnel, and providing personalized nursing suggestions. According to the method, the risk change of the pressure injury of the patient can be automatically judged, the optimal evaluation and intervention opportunity is determined, the nursing quality is improved, and the occurrence rate of the pressure injury is reduced.

The invention discloses an intelligent mattress for monitoring the bedridden state and vital signs of a patient, and belongs to the technical field of nursing mattresses. The longitudinal sliding rails and the transverse sliding rails are additionally arranged at the bottoms of the module adjusting plates, the angle dynamic adjusting function of the module mattress in the vertical direction is achieved, the mattress can adjust the local height of a bed body in time according to pressure gravity center shifting or posture sudden change, the risk that a patient slides down or shifts is prevented, and the patient lying state analysis module is combined, so that the patient lying state is analyzed. According to the posture and gravity center judgment result of a patient, automatic adjustment can be achieved, when the patient gets close to the bedside or has the falling risk, the guardrail can be automatically lifted, an effective physical barrier is formed, image information and pressure data are fused, the posture state of the patient is comprehensively recognized, protective response is automatically made, and linkage is achieved through an external terminal. Nursing personnel and family members can be informed in time when a patient is in a high-risk state, the response speed and the processing efficiency are greatly improved, and a data-identification-control-feedback full-process closed-loop management mechanism is achieved.

The invention relates to the technical field of nursing personnel distribution, in particular to a wireless call-for-help communication system for a smart ward. When a help calling signal is received, the system obtains all related data information including nursing experience, position information and the like of a nurse. Calculating a first matching factor (based on nursing experience) for each nurse and each patient by analyzing historical nursing data; meanwhile, a second matching factor (based on the position relation) is calculated according to the movement track of the nurse; the system also evaluates the accumulated workload and the future predicted workload of the nurse to reflect the busy degree and the fatigue degree of the nurse. In the help calling matching module, the nursing experience, the position relation, the workload and the task of the day of the nurse are comprehensively considered, and the target nurse most matched with the patient to be rescued is screened. According to the method, multiple factors are combined, more flexible and more accurate screening is achieved, it is ensured that the selected nurse can reach the position of the patient as soon as possible, the problem is effectively solved, and the efficiency and quality of medical care are improved.

The invention provides a hospital common department infection source real-time monitoring method and system, and belongs to the technical field of intelligent medical health management. The method comprises the following steps: counting at least one use index value of at least one disinfection appliance of each common department; when at least one use index value does not accord with a preset standard value, determining that the common department is a target monitoring department; randomly sampling regional bacteria monitoring is carried out on nursing personnel from the target monitoring department; and determining whether the target monitoring department has an infection source exposure risk or not based on a result of regional bacteria monitoring. The system comprises a statistical unit, a target monitoring department determination unit, a sampling monitoring unit and an infection source risk determination unit, and is used for realizing the method. According to the technical scheme, in the daily diagnosis and treatment process, the department area with the infection source exposure risk can be recognized in time based on the actual clinical data, and the whole process can be automatically executed based on the preset management strategy capable of being dynamically configured.