427 results about "Clinical nursing" patented technology

The invention relates to the technical field of medical care, in particular to an intelligent query method for a nursing knowledge base, which comprises the following steps of: performing multi-form standardized processing on a nursing problem input by a user, deeply analyzing a query request by utilizing a semantic understanding model, and obtaining an intelligent query result based on an inference algorithm; the method comprises the following steps: automatically selecting related literatures, clinical data and nursing experience data from a nursing knowledge base, generating a preliminary nursing scheme candidate set in combination with a nursing professional knowledge graph, and performing personalized screening and optimization on the scheme by using an intelligent recommendation model in combination with the current illness state, treatment progress and historical nursing data of a patient; the intelligent recommendation model is self-optimized through user feedback, and the nursing scheme recommendation precision is continuously improved. The nursing knowledge base automatically fuses newest medical research results and clinical nursing practice data. The problems that in the prior art, nursing scheme recommendation accuracy is low, updating is not timely, and the individuation degree is insufficient are effectively solved.

The invention relates to the technical field of medical information processing, in particular to an information sharing method of a pediatric clinical nursing system. And obtaining complete medical record sample data including age, symptom results, treatment cycles and drug doses. Comprehensively analyzing the similarity between the age and the disease result, determining a difference characteristic value, and carrying out initial clustering to form a cluster; disease distribution and influence characteristics are analyzed from disease results in view of differences of disease response and treatment requirements of child patients of different age groups. Selecting a to-be-analyzed disease, determining a prominence index by combining the distribution density and the treatment cycle of the to-be-analyzed disease in the cluster, and reflecting distribution characteristics; meanwhile, the occurrence frequency, the difference characteristic value, the treatment cycle and the medication dosage are analyzed, and the influence degree index is judged. Clinical indexes are determined by combining the influence degree and the outburst index, and individual features of the child patient are accurately represented. Clustering analysis is carried out based on clinical indexes, a more accurate clustering result is obtained, and the information sharing accuracy is improved.

The invention provides a neurology clinical nursing potential safety hazard analysis method and device, and relates to the technical field of neurology clinical nursing, and the method comprises the steps: inputting a risk feature matrix generated based on multi-source heterogeneous nursing data into a rule engine and graph neural network model, and outputting a preliminary screening risk event set; taking the primary screening risk event set and the risk feature matrix as input, and constructing a causal conduction map through a causal discovery algorithm; performing risk conduction quantitative integration on each risk event in the primarily screened risk event set based on a causal conduction map to generate a quantitative risk list; based on the dynamic risk priority number and the conduction path chain, reversely tracing to a root cause node along a directed conduction edge, and generating a targeted intervention strategy packet bound with the root cause node; the targeted intervention strategy package is pushed to the nursing responsible person terminal, the strategy execution effect and the risk evolution data are recorded, and a closed-loop disposal database is generated, so that the dynamics and the effectiveness of potential safety hazard analysis of clinical nursing of the neurology department are improved.

The invention provides a patient pathological data analysis and evaluation method for clinical nursing, and relates to the technical field of nursing informatization. Comprising the steps of collecting biochemical and pathological data of a patient and standardizing units and reference values, analyzing the dynamic trend of detection values and classifying change directions and amplitudes, matching pathological labels and establishing association with nursing items, comparing differences between nursing records and the pathological data and establishing a transverse index relationship, and judging whether the nursing task difference exceeds a threshold value or not and adjusting a nursing path generation scheme. By integrating multi-source pathological data and standardizing units and reference intervals, data consistency and comparability are ensured, the index fluctuation trend is dynamically tracked, the change direction and amplitude are quantitatively analyzed, disease course evolution is accurately captured, direct mapping between pathological categories and nursing items is established, logic binding is clear, intervention precision is improved, and the method is suitable for clinical application. Differences between nursing records and pathological data are transversely compared, nursing dynamic adaptation is optimized, a path scheme is rapidly adjusted through threshold judgment, and the lagging or misjudgment risk is reduced.

The invention relates to the technical field related to anesthesia nursing data processing, in particular to an anesthesiology department clinical nursing data management method and system, and the method comprises the steps: collecting anesthesiology department clinical nursing data, configuring a first data mapping table and a second data mapping table through static features and dynamic features according to a platform end and an application end, and generating a nursing knowledge graph, adjacent event features are obtained, and multi-scale risk assessment is combined with dynamic threshold reminding. The technical problems that time sequence correlation and cooperative influence of all events in the anesthesia process are not fully considered, risk assessment standards cannot be dynamically adjusted for different anesthesia stages, and risk misjudgment is likely to be caused are solved, and by configuring a first data mapping table and a second data mapping table and combining time entropies and correlation rule support degrees corresponding to time intervals of adjacent events, the risk assessment standard can be dynamically adjusted according to the time entropies and the correlation rule support degrees. Layered management and accurate mapping of static and dynamic characteristics in clinical nursing data of the anesthesiology department are realized, the risk threshold is dynamically adjusted according to time sequence characteristics of different anesthesia stages, and the accuracy and timeliness of risk assessment are remarkably improved.

The invention discloses a postoperative drainage device for clinical nursing and a monitoring system, and belongs to the technical field of biomedical engineering. The problems that an existing device manually monitors drainage liquid data, consequently, the monitoring precision is insufficient, and the complication probability cannot be predicted are solved, drainage liquid and patient vital sign data are collected in real time through the micro spectrograph, the character multi-parameter sensor, the micro pressure sensor and the intelligent bracelet and transmitted to the remote monitoring platform, and the monitoring accuracy is improved. Medical staff can check real-time data of a patient at any time and adjust a treatment scheme in time, so that the nursing efficiency and quality are improved; multi-parameter data such as color, metering and property of drainage liquid and vital sign data are analyzed through a risk prediction model, intervention measures are dynamically adjusted according to different complication types and probabilities in combination with patient condition changes and real-time monitoring data, accurate intervention on the complication is achieved, and the occurrence rate and severity of the complication are reduced.

The invention relates to the technical field of medical treatment, in particular to a multi-parameter collaborative infusion process intelligent monitoring and priority calling method, which comprises the following steps of: acquiring four-dimensional monitoring data through a liquid level pressure sensor array, an infrared dripping speed detection module, a flexible temperature patch and a photoelectric heart rate sensor, and combining an LSTM (Long Short Term Memory) anomaly prediction model, and outputting the pipeline state score, the allergy risk index and the infusion progress prediction value in real time. And generating a real-time risk value through a weight configuration mechanism and stage identification logic, judging a risk level according to a dynamic threshold value, and outputting a corresponding early warning level signal. And the system further maps the early warning level signals into common, emergency and critical call instructions, and distributes the common, emergency and critical call instructions to a multi-channel execution terminal to construct a multi-level linkage response mechanism of closed-loop feedback. According to the invention, the accuracy and response efficiency of infusion risk identification can be significantly improved, and the method is suitable for intelligent reconstruction and automatic early warning response scenes of a clinical nursing information system.

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 discloses an intelligent off-bed monitoring system and method based on polymorphic perception, relates to the technical field of medical monitoring, and breaks through the misjudgment bottleneck of a single sensor by synchronously collecting a body pressure center point coordinate sequence and a breathing waveform amplitude time sequence of a patient and dynamically associating a body movement frequency feature vector with a breathing waveform interruption feature. Real off-bed and on-bed activities are effectively distinguished, and the false alarm rate is effectively reduced; the early warning accuracy is counted in real time, when the false alarm rate exceeds the standard, the mahalanobis distance between a false alarm event and a real off-bed event is calculated to generate a feature offset, a judgment threshold value is dynamically corrected, and the system is adaptive to individual differences of patients; a real-time feedback mechanism improves long-term stability of the system, and sensitivity and reliability are both considered. The system is especially suitable for precise monitoring requirements of high-risk patients, and provides intelligent decision support for clinical nursing.

The invention relates to a clinical nursing shift change system and method, and relates to the technical field of data processing, and the system comprises a nurse terminal module which is used for inputting shift change information through a standardized template, carrying out the continuous visualization of shift change, and carrying out the butt joint with an electronic medical record system, so as to automatically capture the abnormal and real-time data of a patient; the patient end module is used for generating a two-dimensional code scanning interface for a patient and family members to check nursing propaganda and education, guidance and diagnosis and treatment routes, and feeding back an abnormal state through a voice or graphical interface; the doctor end module is used for synchronously displaying key medical parameters in shift change data, so that a doctor can mark a risk level and trigger a secondary confirmation process; the quality control management end module is used for generating a traceable responsibility definition coefficient; and the data analysis module is used for calculating a shift-change integrity score representing shift-change information integrity and a global shift-change quality index representing shift-change quality in real time. The system can improve the accuracy and efficiency of clinical nursing shift change.

The invention relates to the technical field of blood pressure monitoring, in particular to a patient blood pressure monitoring method and system for clinical nursing. According to the method, the blood pressure controllability is obtained through the distribution fluctuation degree of blood pressure data in a neighborhood range at each moment; the blood pressure confusion degree is obtained according to the distribution conditions of the blood pressure data corresponding to the sampling moments at the same position in different period segments and the blood pressure controllability; the blood pressure disorder degree of each sampling moment is obtained according to the blood pressure disorder degree of the period section where the current moment is located and the blood pressure change condition in the neighborhood range, the neighborhood radius is adjusted based on the distribution of the blood pressure disorder degrees, DBSCAN clustering is conducted on the blood pressure data of the period section at the current moment, a monitoring clustering result is obtained, and blood pressure state monitoring is conducted. According to the method, the neighborhood radius of clustering is adaptively adjusted by combining the blood pressure fluctuation condition and analyzing the abnormality of the blood pressure data in multiple cycles, the sensitivity of clustering to abnormal points is improved, a more accurate clustering result is obtained, and the monitoring result is more reliable.

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 full-scene nursing task dynamic generation method, and relates to the technical field of medical treatment. The method comprises the steps of obtaining medical data of a target user in a preset medical institution; performing event identification according to the medical data of the target user and a trigger condition of at least one preset clinical event associated with each clinical nursing business scene in the plurality of clinical nursing business scenes; if the trigger conditions of the target clinical event associated with the clinical nursing business scene are identified to be matched, loading a target event template corresponding to the target clinical event, and extracting a standardized nursing activity set corresponding to the target clinical event and a nursing task set of each nursing activity under the standardized nursing activity set from the target event template; and instantiating the target clinical event by adopting the target event template according to the medical data of the target user, the standardized nursing activity set and the nursing task set of each nursing activity, and generating a full-cycle nursing task for the target clinical event. Therefore, the efficiency is improved.

The invention relates to a generative AI-based nursing case intelligent teaching question and answer robot and application thereof.A current teaching task is executed through an RAG enhanced retrieval module, question and answer knowledge is retrieved from a nursing knowledge base based on keywords in user question and answer information, and LLM is used for performing enhanced retrieval on the question and answer knowledge; the learning dynamic evaluation module performs learning performance evaluation on answer information in user question and answer information by using LLM, and the workflow management module pushes teaching tasks with corresponding learning strength to the RAG enhanced retrieval module in a matching manner to perform personalized learning path and branch scheduling. Clinical nursing cases can be created based on the generative AI, the nursing key points are answered and answered in a guiding mode, the clinical nursing thinking of students is improved in repeated practice, and the nursing teaching effect is improved. And nursing cases of different specialities are generated according to a rule enhancement formula, so that students are gradually guided to strengthen learning, and the autonomous learning ability and clinical thinking of the students are improved.

According to the clinical nursing patient information monitoring and inputting method and system, the data accuracy, the data inputting efficiency and the privacy protection safety are improved; the method comprises the following steps: firstly, collecting and preprocessing vital sign data of a patient in real time through various physiological sensors; then, acquiring a nursing record image, acquiring nursing record data through an OCR model, acquiring nursing information voice, transwriting the nursing record data and the nursing information voice into nursing information data through a medical scene voice transwriting model, and performing unified standardization processing on the three groups of data to generate patient information data; and finally, when patient information data is input, symmetric encryption is carried out by adopting a national cryptographic SM4 algorithm, encrypted data is obtained, a dynamic encryption key is generated through an ECDH key distribution technology, and the dynamic encryption key can be called to carry out decryption operation after authentication of a dual protection mechanism of Hash value pre-verification and identity authentication is passed.

The invention relates to a medical clinical nursing aid decision making system and method, and belongs to the technical field of medical clinical nursing information. Comprising a screening module used for obtaining case information, extracting case variable codes of the case information, matching the case variable codes with pre-stored variable codes, and screening out matched pre-stored feature codes; the nursing evaluation decision module is used for calculating the ratio of pre-stored feature codes and judging whether a nursing diagnosis and treatment scheme and path service meet nursing requirements or not; when the requirements are met, characteristic factors of the case information are extracted, and the nursing problem of the patient is obtained; according to the problem, a nursing target and plan are made; the nursing plan execution module is used for assigning nursing personnel according to the nursing target and plan; wherein the nurse updates the nursing problem according to the current nursing state of the patient; and the doctor advice execution module is used for automatically outputting a medicine use prompt according to the inquired medicine information. Balanced distribution of workload and nursing tasks of nursing personnel can be realized.

The invention relates to the technical field of medical care, and particularly discloses a massage device for clinical care. Bionic massage mechanisms are mounted on the outer walls of the two sides of the massage bed, and a stimulation massage mechanism is mounted in the middle of the bottom end of the massage bed; the bionic massage mechanism comprises a multi-degree-of-freedom mechanical arm, a mounting mechanism, a massager, a moving block, a moving screw rod, a fixed frame and a driver, the mounting mechanism is mounted at one end of the multi-degree-of-freedom mechanical arm, and the massager is clamped and mounted at the other end of the mounting mechanism; through cooperative operation of the multi-degree-of-freedom mechanical arm and the driver, complex actions of kneading, pushing and pressing, tapping and the like of a professional rehabilitatrist can be simulated, massage manipulations are greatly enriched, the massage effect is remarkably enhanced, a pressure sensor arranged on the massager can monitor local pressure intensity changes of a massage part in real time, and the massage effect is improved. When the pressure intensity reaches a preset threshold value, the controller can automatically adjust the massage intensity, and it is ensured that the massage process is effective and safe.

The utility model discloses a clinical nursing leg cushioning device, which relates to the technical field of clinical nursing instruments, and comprises a placing base plate, a folding leg cushioning mechanism is arranged above the placing base plate, the folding leg cushioning mechanism comprises a movable arc-shaped plate, the bottom of the movable arc-shaped plate is movably connected with the rearmost side of the top of the placing base plate, and the folding leg cushioning mechanism is arranged above the placing base plate. A telescopic arc-shaped plate is slidably mounted in an inner cavity of the movable arc-shaped plate, the top end of the telescopic arc-shaped plate penetrates through the top of the movable arc-shaped plate and is movably provided with a shank placing plate, and a sponge pad is fixedly mounted at the top of the shank placing plate. Through mutual cooperation of the placement base plate, the movable arc-shaped plate, the telescopic arc-shaped plate and the shank placement plate, the legs of a patient can be rapidly and stably supported, meanwhile, through cooperation with the telescopic arc-shaped plate in the movable arc-shaped plate, the thighs of the patient can be supported, and after the shanks of the patient are supported, the patient feels more comfortable after being placed for a long time.

The invention discloses a neurology department clinical nursing potential safety hazard analysis method and device, and relates to the technical field of clinical nursing potential safety hazard analys.The method comprises the steps that physiological data and behavior data of a patient are collected, and multi-source data are preprocessed through weighted Kalman filtering; performing multi-dimensional fusion on the processed data, calculating a comprehensive health score by adopting a weighted average method, and evaluating the potential safety hazard of the patient in combination with a convolutional neural network; and based on the comprehensive health score, generating a personalized nursing scheme, and providing nursing decision support for medical staff. According to the clinical nursing potential safety hazard analysis method for the neurology department, the physiological data and the behavior data are combined, multi-dimensional data fusion is carried out through weighted Kalman filtering and the convolutional neural network, the accuracy of patient health assessment is improved, noise and errors are reduced, and the consistency and reliability of the data are ensured.

The invention relates to the technical field of respiratory lung sound recognition, in particular to a respiratory lung sound auxiliary recognition method and system for clinical nursing. The invention provides a respiratory lung sound auxiliary identification method and system for clinical nursing, solves the technical problems of data scarcity, complex noise interference and insufficient cross-device generalization ability in lung sound signals through generative data enhancement and cross-modal migration, and combines self-supervised comparative learning and causal feature discovery to identify the respiratory lung sound. Multi-source signal feature fusion and noise robustness improvement are realized, a real-time noise environment is dynamically adapted, the limitation that a traditional method depends on annotation data and feature extraction is easily influenced by hybrid noise is broken through, a full-link closed-loop system from synthetic data generation, cross-modal alignment to causal-driven decision is constructed, and multi-source signal feature fusion and noise robustness improvement are realized. And the accuracy and clinical applicability of clinical lung sound analysis are effectively improved.

The utility model relates to the technical field of compression hemostasis devices, in particular to a compression hemostasis device for clinical nursing, which comprises a fixing plate and a compression hemostasis rubber head, the fixing plate is semicircular, the inner wall of the bottom of the fixing plate is fixedly connected with a fixing block, and the outer wall of the top end of the fixing block is fixedly connected with an arc-shaped plate. A sponge pad is bonded to the inner wall of the arc-shaped plate, a second clinical nursing compression belt is fixedly connected to the outer wall of one side of one side of the top end of the fixing plate, and a first clinical nursing compression belt is fixedly connected to the outer wall of the other side of the other side of the top end of the fixing plate. The top compression hemostasis rubber head can slide on the compression belt and can be conveniently and accurately adjusted to a bleeding position, the limb bottom supporting structure can be bent and folded, so that the side face of the limb is attached and limited, the compression stability is further improved, and hemostasis failure caused by limb sliding is prevented; and the use efficiency of the compression hemostasis device for clinical nursing is 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 relates to the technical field of clinical nursing management, and discloses an intelligent nursing system and method based on clinical big data, and the system comprises a clinical nursing node supervision module, a clinical nursing personnel allocation module, and a clinical nursing execution module. According to current nursing time point information, in combination with an intelligent search algorithm and target patient clinical nursing plan information, patient clinical nursing project information is accurately extracted, clinical nursing projects are efficiently customized and supervised for patients at different clinical nursing time nodes, and the service quality and efficiency of clinical nursing are improved; the optimal clinical nursing personnel is accurately and scientifically screened based on the clinical nursing project information of the target patient, the working state of the clinical nursing personnel and the spatial distance information between the clinical nursing personnel and the patient, intelligent allocation of the clinical nursing personnel is achieved, and the response speed and scientificity of clinical nursing are improved.

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 discloses an intelligent analysis and early warning system for potential safety hazards of clinical nursing, and relates to the technical field of intelligent nursing monitoring. Physiological data of a patient is collected in real time and preprocessed, a physiological data set S is constructed and summarized and calculated, characteristic indexes are obtained, and a microcirculation disturbance index Wxh is calculated according to the characteristic indexes; the method comprises the following steps: evaluating the current body state of a patient, constructing a time sequence analysis model, predicting a microcirculation disturbance index Wxh of the patient in a future period of time, evaluating the health state of the patient in the future period of time, carrying out risk early warning, carrying out nursing strategy grading, and carrying out nursing intervention on the patient. The physiological data of the patient in the clinical nursing process are monitored in real time, the clinical nursing effect is optimized, and the nursing efficiency and the nursing safety are improved.

The invention relates to the technical field of medical care, in particular to a clinical care information recording method and equipment of an intelligent medical system and a medium. The method comprises the following steps: acquiring a patient category of a current patient, taking other patients in the patient category as target patients, and acquiring a nursing effectiveness degree according to a target achievement condition and a physical sign stability condition of the target patients; screening low-score patients through nursing plan satisfaction scoring, obtaining contrast patients of the low-score patients, and obtaining reference weights of the low-score patients according to differences between the low-score patients and the contrast patients; and presetting reference weights of other target patients except the low-score patient, obtaining a nursing evaluation degree according to the reference weights, the nursing effectiveness degree and nursing plan satisfaction scoring, and judging whether the nursing plan of the current patient is reasonable or not. By acquiring the nursing assessment degree, whether the nursing plan of the current patient is reasonable or not is accurately judged, and the nursing plan of the current patient is adjusted in time, so that the current patient is effectively treated.

The utility model discloses a clinical nursing leg supporting device which comprises an installation frame, a fixing column is arranged on the upper portion of the installation frame and fixedly connected with the installation frame, a telescopic column is arranged in the fixing column and connected with the fixing column in a telescopic mode, and the telescopic column is connected with the installation frame in a telescopic mode. A supporting rod is arranged on the side face of the telescopic column and is in threaded connection with the telescopic column, an adjusting block is arranged on the surface of the supporting rod, and a lifting rope is arranged on the lower portion of the adjusting block. During use, the mounting frame is clamped at the edge of the bed frame, and the top plate is in contact with the bed frame by rotating the adjusting rod, so that the mounting frame and the bed frame are fixed, the height between the telescopic column and the fixed column is adjusted, the supporting rod is adjusted to a proper height, the position of the adjusting block is moved, and the hanging plate corresponds to the legs of a patient; the leg supporting device is simple in structure, convenient and fast to operate, small in size, convenient to move and suitable for different occasions.

The invention relates to the technical field of lung sound signal analysis, in particular to a respiratory lung sound auxiliary identification method and system for clinical nursing. The method comprises the following steps: firstly, acquiring a segmented lung sound signal, a segmented signal component and a segmented respiration signal of each day; further obtaining an initial qualified component according to the correlation characteristics of each segmented signal component and the segmented breathing signal corresponding to the time sequence in combination with the fluctuation rule characteristics of the segmented signal components; further, according to fluctuation difference characteristics of each qualified signal component segment and a time sequence corresponding segment lung sound signal, combining a lung sound law coefficient to obtain a noise influence coefficient of each qualified signal component segment, and screening out a low-noise time period; further obtaining the credibility of each initial qualified component in the current day according to the distribution similar characteristics of low-noise time periods in the initial qualified components of the current day and all historical days in combination with the similar characteristics of noise influence coefficients; and finally, screening based on the credibility to obtain the optimal signal component of the current day.

The utility model belongs to the technical field of turning-over devices, and provides an auxiliary turning-over device for clinical nursing, which comprises a mounting mechanism comprising a sickbed, and two sides of the sickbed are oppositely provided with two clamping grooves; and the turnover mechanism comprises a plurality of supporting grooves fixedly installed on one sides of the multiple clamping grooves correspondingly, the interiors of the multiple supporting grooves are slidably connected with lifting frames correspondingly, driving assemblies are fixedly installed at the upper ends of the lifting frames, and the driving assemblies comprise a plurality of L-shaped supports fixedly installed at the upper ends of the multiple lifting frames correspondingly. By arranging the driving assembly, a patient can be turned over easily, the working intensity of medical staff can be reduced, nursing staff can nurse the patient conveniently, bedsores and amyotrophy of the patient are avoided, and meanwhile clinical medical staff can turn over the patient conveniently for comprehensive examination.

The utility model relates to the technical field of clinical nursing, and discloses a bedridden patient vomit measuring cup which comprises a measuring cup body, scale marks are arranged on one side of the measuring cup body, an L-shaped clamping piece is fixedly connected to the side, away from the scale marks, of the measuring cup body, and a cup cover is connected to one side of a cup opening of the measuring cup body. One side of the cup cover is connected with a rotating assembly, the other side of the rotating assembly is connected with the metering cup body, the side, away from the rotating assembly, of the metering cup body is connected with a clamping assembly, the other side of the clamping assembly is connected with the cup cover, and the outer wall of the metering cup body is fixedly connected with two symmetrically-arranged cup handles. According to the vomiting measuring cup for the bedridden patient, the measuring cup is clamped beside a sickbed used by the patient through the L-shaped clamping plate, when the patient feels vomiting, the patient can vomit into the measuring device only by slightly leaning to one side or deviating the head, the vomiting amount of the patient can be observed in time through the scale marks on the measuring device, and medical staff can conveniently record the illness state of the patient.