277 results about "Intensive care" patented technology

The invention discloses an accurate health risk early warning analysis system and method based on multi-modal medical data fusion. The system comprises a multi-source data acquisition module, a preprocessing module, a dynamic fusion module, a risk assessment module, an interpretability module and a dynamic early warning module. According to the method, multi-modal data are collected, feature vectors are generated through preprocessing and cross-modal fusion, a comprehensive health risk index is calculated through a double-flow model (time sequence LSTM + static GNN), abnormal association is analyzed in combination with causal reasoning, a threshold value is dynamically adjusted, grading early warning is triggered, and finally the model is optimized through reinforcement learning. According to the scheme, deep fusion and dynamic evaluation of multi-modal data are achieved, the accuracy, timeliness and interpretability of risk early warning are improved, the method is suitable for scenes such as chronic disease management and intensive care, and powerful support is provided for clinical decision making.

The invention relates to an intensive care cross-institution collaborative data processing method, which comprises the following steps of: defining a hierarchical data model based on the intensive care field, and modeling various types of information including vital signs, clinical diagnosis and laboratory detection results of a patient according to a time sequence; a self-adaptive standardized interface is designed, and data formats from different hospitals or devices are identified and converted; real-time dynamic tags are introduced for patient data through a tagging technology; various health data, including vital signs, medical history and treatment feedback, of a critical patient are converted into a multi-dimensional health track, and sequential analysis is used for conducting continuous modeling on the condition of the patient; a deep learning and reinforcement learning method is combined to establish a disease evolution deduction engine; the disease development is predicted according to historical data, and the influence of different intervention measures on the disease is simulated to intelligently recommend a treatment strategy; and according to the dynamic deduction result, generating a plurality of treatment schemes, and dynamically adjusting the intervention strategy according to the real-time response of the patient.

The invention discloses a pupil image recognition and disease change evaluation system based on image recognition, and relates to the technical field of monitoring analysis, and the system comprises the steps: obtaining the identity information and historical pupil data of a patient, and building a pupil dynamic database corresponding to the patient; alternately irradiating the eyes of the patient, and collecting a dynamic image sequence corresponding to a pupil light reflex area of the patient; performing spatial-temporal characteristic analysis on the dynamic image sequence, establishing a pupil diameter dynamic change curve, and generating a light reflection sensitivity index of the pupil of the patient according to the pupil diameter dynamic change curve; constructing a pupil dynamic evaluation model according to the pupil diameter dynamic change curve and the light reflex sensitivity index of the patient pupil, and outputting a pupil grade evaluation result based on the pupil dynamic evaluation model; comprehensive analysis is conducted on pupil grade evaluation results, analysis results are uploaded to an intensive care central system, and a grading early warning mechanism is triggered. The application has the effect of reducing the occurrence of illness state delay.

The invention relates to the technical field of medical early warning, and discloses a graded early warning system based on multi-parameter vital sign detection. According to the system, real-time physiological parameters such as the heart rate, the blood pressure, the oxyhemoglobin saturation and the body temperature of a patient are collected through vital sign monitoring equipment; and inputting the parameters into a feature extraction network, generating a multi-dimensional physiological feature vector, and constructing a dynamic risk assessment matrix containing physiological state change trends of different time windows according to the multi-dimensional physiological feature vector. Dividing risk grade intervals according to a preset grading early warning threshold value, adjusting the intervals by adopting a self-adaptive weight distribution strategy, and generating a comprehensive risk score; and when the score exceeds the preset early warning trigger line, activating a corresponding early warning response mechanism. The system can realize comprehensive dynamic assessment of the physiological status of the patient, is suitable for emergency treatment, intensive care and chronic disease nursing scenes, and meets the clinical health risk monitoring and early warning requirements.

The invention relates to the technical field of medical care, in particular to an intensive care data management system based on a block chain, and the system comprises an access behavior analysis module, a data encryption module, a sensitivity monitoring module, a health abnormality monitoring module and a node monitoring module. According to the invention, intensive care data is finely managed by using the block chain technology, the medical process is optimized, the access behavior and response time difference is collected and analyzed, the operation efficiency of medical personnel and medical equipment is effectively monitored, the operation delay and the process bottleneck are identified in real time, the response speed is optimized, and the quality of medical services is improved. Through encryption processing and data classification, the confidentiality of information is guaranteed, the data security is also improved, the data leakage risk is reduced, and due to accurate monitoring and real-time abnormal monitoring of sensitivity, key medical data is particularly protected, and the service quality of patient data management is enhanced.

A medical monitoring system comprises a wearable garment incorporating multiple physiological sensors for real-time patient monitoring. The garment integrates an embedded processing unit that receives sensor data and transmits it wirelessly to a base station or remote server. A multi-modal physiological signal processing unit analyses the data to generate composite physiological indices, including metabolic rate, work of breathing, and fall risk assessments. The garment includes optional monitoring features such as transcutaneous carbon dioxide measurement, electrocardiography, pulse oximetry, blood pressure monitoring, and accelerometer - gyroscope-based motion tracking. The system provides early-warning alerts for clinical deterioration, enabling proactive therapeutic interventions. A wireless communication module ensures real-time data transmission, supporting remote monitoring and integration with hospital networks. The garment's modular design allows for non-invasive physiological assessment while maintaining patient mobility, making it suitable for critical care, ambulatory monitoring, and telemedicine applications.

The invention relates to the technical field of medical informatization, and provides an information digital management system and method based on an intensive care medicine department, and the system comprises a data collection module, a data processing module, and a visualization and alarm module. The data acquisition module obtains a patient monitoring data set, and each patient corresponds to a monitoring data sequence. The data processing module executes the following operations on each patient: determining a target monitoring data sequence and four associated monitoring periods including a first monitoring period, a second monitoring period, a third monitoring period and a fourth monitoring period group, and generating a corresponding monitoring subset; generating an early warning signal through a disease deterioration early warning model; and if the signal is abnormal, analyzing an abnormal reason and an influence range, and generating a structured disease condition comprehensive report. And the visualization and alarm module dynamically displays the state of the patient according to the report, and performs graded alarm on the critical area. The system realizes accurate early warning and monitoring through multi-cycle data fusion analysis and three-dimensional visualization.

The invention belongs to the technical field of early warning systems in Internet platforms, and discloses an Internet of Things-based early warning system and early warning method for an intensive care unit, and the system carries out the abnormal recognition of physiological parameters through a pre-trained early warning model, fuses response task features, medical worker resource states and historical scores based on a response scheduling module, and carries out the early warning of the medical worker. A responder assignment strategy is optimized, and the matching accuracy is improved; furthermore, periodic data acquisition is realized through a response closed-loop recording module, an early warning response responsibility chain containing node and causal link information is constructed, and on the basis, high-risk nodes and bottleneck regions are identified, task allocation weights and path optimization rules are dynamically adjusted, and adaptive updating of scheduling logic is realized; and early warning re-response and rescheduling based on new logic are supported, and a feedback closed loop driven by data is formed, so that the timeliness and accuracy of early warning response are effectively improved, and the risk of intervention failure caused by response lag is reduced.

The invention discloses a critical patient physiological parameter monitoring and intelligent early warning system, which relates to the technical field of intelligent medical treatment, and is provided with a multi-modal data collection module for collecting multi-modal physiological parameter data of a critical patient through a sensor array of flexible electronic skin, and a signal alignment module for aligning the multi-modal physiological parameter data of the critical patient. Aligning signal sequences with different sampling rates in the multi-modal physiological parameter data, setting a physiological theoretical range updating module, constructing a transfer learning model according to historical medical records of a patient, updating a physiological theoretical range of a heart rate variation coefficient in real time, setting a grading early warning module, and triggering a Bayesian network composite event detection model. Generating a graded early warning signal, setting a decision support module, dynamically loading a clinical knowledge graph through a micro-service architecture, and pushing decision support information containing rescue priority labels to a monitoring terminal; and the precision and efficiency of intensive care are obviously improved.

The present invention deals with a heat and moisture exchange filter with biocidal activity for medical ventilation equipment that comprises polymeric cellulose fibers impregnated with silver nanoparticles (AgNPs). The heat and moisture exchanger filter can be used in intubated patients under artificial ventilation in anesthesiology and intensive care and allows robust replacement, a fundamental utility for protection against nosocomial cross-contamination infections caused by microorganisms, such as bacteria, fungi, yeasts and viruses.The invention also deals with the method of preparing the heat and moisture exchange filter with biocidal activity and the use of silver nanoparticles.

The utility model provides a severe nursing sputum suction tube, and belongs to the technical field of sputum suction tubes. Comprising a sputum suction tube body, one end of the sputum suction tube body is an insertion end inserted into the respiratory tract of a patient, the other end of the sputum suction tube body is a connecting end connected with a negative pressure generation assembly, the insertion end of the sputum suction tube body is connected with an end head with a smooth surface, and a sputum suction hole is formed in the side wall of the insertion end of the sputum suction tube body. And a connecting head is arranged at the connecting end of the sputum suction tube body. The end head with the smooth surface is arranged at the insertion end of the sputum suction tube body, so that the phenomenon that the end face corner angle of the insertion end of the sputum suction tube body scratches the respiratory tract of a patient when the sputum suction tube body is inserted into the respiratory tract of the patient can be effectively avoided, and the sputum suction tube is safer and more reliable.

The invention provides a multi-agent medical examination recommendation system and method, and relates to the technical field of medical intellectualization. Comprising a medical examination recommendation data set building module used for extracting key medical entities and personal information of patients from electronic medical records of an intensive care medical information database, and generating enhanced patient sequence data by using the key medical entities and a preprocessing mode; the medical knowledge graph building module is used for building a medical knowledge graph according to the disease and the triple generation module based on the large language model; and the medical examination recommendation module is used for processing the enhanced patient sequence data and personal information by utilizing a plurality of intelligent agents and a medical knowledge graph to obtain a target medical examination item. In this way, structured medical examination data can be provided, and the quality of a data set is high; multiple agents are introduced, so that the flexibility and adaptability of the recommended target medical examination items are improved; and the reasonability of the recommendation result is improved by utilizing the established medical knowledge graph.

The present application relates to a kind of respiratory synchronous diaphragm nerve electric stimulator in vitro, belong to medical equipment technical field.The technical scheme of a kind of diaphragm nerve electric stimulation based on real-time breathing signal synchronization trigger is proposed for the problems of high weaning failure rate and quality of life decline caused by VIDD.The technical scheme points include: detecting inspiration negative pressure signal through nasal cavity air pressure sampling tube, control unit dynamically adjusts trigger threshold according to negative pressure signal, when negative pressure is lower than preset value and waveform slope meets the standard, trigger electric stimulation module to output biphasic pulse, pulse parameters include positive and negative alternating waveform, width 0.1ms to 1ms, frequency 10Hz to 50Hz and current intensity 5mA to 30mA, and strictly limit electric stimulation to be only output in inspiration cycle, and expiration cycle is completely blocked stimulation by hardware switch circuit.It is mainly suitable for intensive care and rehabilitation therapy scene, effectively prevent and treat VIDD, improve patient weaning success rate and quality of life.

The invention discloses a respiratory intensive care method and system, and the method comprises the steps: deploying an acoustic sensor on a respirator loop, and synchronously obtaining the ventilation parameters and optional temperature and humidity data of a respirator; preprocessing the acquired multi-modal data, and converting an acoustic signal into a time-frequency spectrogram; the preprocessed data are input into a multi-modal fusion fault recognition model, the model comprises a convolutional neural network branch used for extracting acoustic features and a recurrent neural network branch used for capturing time sequence dynamics, and the probability of a specific fault precursor is output by combining the features of all the branches through a fusion layer; and finally, performing early warning decision according to the probability. The invention also comprises a system for implementing the method. According to the invention, through deep fusion of acoustic, pneumatic and thermodynamic data, accurate prediction of fault precursor is realized, and an earlier time window is provided for clinical intervention, so that the monitoring safety is improved.

The invention relates to the technical field of monitoring restraint, and particularly discloses an intensive care restraint device and a using method thereof.The intensive care restraint device comprises an abdomen restraint strap, the abdomen restraint strap surrounds the waist of a patient for binding, the abdomen restraint strap is sleeved with a binding strap, and the two sides of the binding strap are connected with connecting straps through adjusting buckles; shoulder restraint straps are arranged outside the binding strap in a crossed manner; the device further comprises a pressure sensor, the pressure sensor monitors the extrusion pressure change in real time and is used for judging the dysphoria degree of the patient, the pressure sensor is arranged at the intersection of the shoulder restraint strap to monitor the extrusion pressure change when the patient struggles in real time, and a motor in the control assembly is combined to drive a screw transmission mechanism to drive the patient to move. When the patient moves restlessly, the restraint strap is automatically tightened to prevent struggling off or accidental extubation; after the patient is calm, the patient is gradually relaxed and constrained, complications such as blood circulation disorder and pressure sores caused by long-term excessive constraint are effectively avoided, and medical safety and patient comfort are both considered.

The invention discloses a multi-modal data-based auxiliary decision-making system suitable for a perioperative period and an intensive care period, which can provide multi-dimensional reference contents such as real-time monitoring, attribution analysis and decision-making recommendation of physiological parameters for a user, can provide auxiliary information for decision making of medical personnel, and can improve decision-making efficiency. Meanwhile, the system greatly reduces the requirements for medical knowledge and personal professional literacy of medical personnel, not only reduces the requirements for personnel ability, but also weakens the dependence on human experience, and can realize dynamic adjustment of physiological parameter calibration data, so that compared with the traditional technology, the use reliability is improved; therefore, the method is very suitable for large-scale application and popularization.

The invention relates to the technical field of medical data mining, and particularly discloses an elderly sepsis index model, a prediction model construction method and a prediction system.The method comprises the steps that a development queue data set and an independent verification queue data set of elderly sepsis patients at the age larger than or equal to 60 years old are determined according to an intensive care database; performing sepsis death and prognosis importance sorting on candidate inflammation-immune composite indexes of the development queue data set according to a total correlation feature selection algorithm; superposing and combining preset basic indexes, each index in the importance inflammation marker indexes and a preset importance scoring standard; comparing the scoring results of the multiple groups of joint optimization index models, and evaluating the scoring results; and determining the joint optimization index model with the optimal evaluation result as the senile sepsis index model. According to the construction method of the senile sepsis index model provided by the invention, the index model suitable for senile sepsis can be obtained based on the existing index database.

The utility model relates to the technical field of medical instruments, and discloses a respiratory training device for intensive care, which comprises a main plate, a fitting plate is clamped at the bottom of the main plate, a collecting pipe for storage is clamped at the top of the main plate, and a circulating pipe for butt joint is clamped at the top of the collecting pipe. An auxiliary piece used for sliding is clamped in the runner pipe, a sleeving ring used for preventing leakage is clamped on one side of the runner pipe, and a flexible rubber hose used for conveying is arranged on one side of the sleeving ring. Through cooperative arrangement of a main plate, an attaching plate and a collecting pipe, internal components can be better disassembled and adjusted when the device is used, a patient can conduct cleaning and disinfection treatment in time, it is avoided that saliva doped in gas emits peculiar smells in the device, the service life of the device is shortened, and up-down irregular movement of an internal ball is prevented; the accuracy in the detection process is improved, and the requirements of the public market are met.

The invention discloses a PatchTST model-based respiratory signal restoration method, which comprises the following steps of: S1, reading low-resolution sensor input data and high-resolution respiratory physiological waveform target data, and carrying out data cleaning, formatting and time alignment to form a unified data set; and S2, dividing the aligned time sequence data into window samples with fixed lengths, dividing a training set and a verification set, carrying out standardization processing on the data, and then constructing a PyTorch data loader. According to the method, the adaptation problem of the low-resolution input data and the high-resolution target waveform can be effectively solved, the target data quality can be further optimized, the breathing physiological state of a patient can be reflected more truly, and reliable data support is provided for clinical intensive care and respiratory disease diagnosis.

The utility model relates to the technical field of medical protection instruments, in particular to an adjustable anti-falling guardrail for a sickbed, which comprises a sickbed main body, bed edges on the front side and the rear side of the sickbed main body are respectively and fixedly provided with a support cross frame, and the tops of the two groups of support cross frames are respectively provided with an adjustable fence mechanism. The child patient can be protected and prevented from falling from the two sides of the sickbed, operation is convenient, meanwhile, the height of the protective net can be adjusted according to the height of a child, the child patient is more humanized, the child patient is effectively prevented from falling from the sickbed, safety is high, and other accidents are avoided.

The invention discloses an intensive care state real-time prediction method and system based on mask dynamic composition. The method directly faces the challenge that clinical time sequence data is extremely sparse, and a monitoring missing mode is creatively converted into valuable prediction features. A monitoring mode dynamic relation graph is constructed to encode the clinical cooperative monitoring intensity between the indexes; comprehensively modeling time sequence dependence in combination with a time sequence attention mechanism and multi-level local feature extraction; and finally, through adaptive multi-channel fusion, accurate and end-to-end prediction of the future multi-index clinical trajectory of the patient is realized. Compared with a traditional filling or special architecture method, the method has the advantages that knowledge hidden in clinical monitoring behaviors can be more effectively mined, more excellent prediction performance can be achieved on an intensive care state data set with extremely sparse data, and a new technical path is provided for development of an intelligent clinical early warning system.

The invention relates to the technical field of extubation action recognition and early warning systems, and discloses a patient unplanned extubation action recognition and early warning system based on wrist strap equipment, the system comprises the wrist strap equipment worn on the wrist of a patient, and the equipment is internally provided with an action sensor, a processor and a communication module. The action sensor is used for detecting hand actions of a patient, the processor analyzes data of the sensor to recognize non-planned extubation actions, and once potential extubation actions are recognized, the system immediately gives out early warning to medical staff in a sound-light alarm and wireless communication mode. The method has the advantages of high recognition accuracy, real-time early warning, protection of patient privacy, reduction of burden of medical staff, improvement of medical safety and the like, is suitable for various patients in hospitals, particularly patients in intensive care units, is beneficial to reduction of the incidence rate of non-planned tube drawing events, reduction of adverse nursing events, reduction of harm to the patients, and is beneficial to popularization and application. The nursing quality is improved and the satisfaction degree is improved.

The utility model discloses an electrocardiograph monitor for intensive care, and mainly relates to intensive care. Comprising a movable base, a monitor body is installed on the upper surface of the movable base, a wiring port is formed in one side of the monitor body, an adjusting structure is arranged at the position, corresponding to the wiring port, of one side of the monitor body, the adjusting structure comprises a fixing frame, and the fixing frame is fixedly connected with the monitor body; the inner wall of the fixing frame is rotatably connected with a two-way screw rod, the arc surface of the two-way screw rod is in threaded connection with two clamping plates, the two clamping plates are slidably connected with the inner wall of the fixing frame, and the side, away from the monitor body, of the fixing frame is fixedly connected with a supporting plate. The beneficial effects of the utility model lie in that the clamping plate is used to limit the connecting line at the wiring port position, the situations of loose wiring and poor contact are avoided, and the storage rod is used to wind the connecting line with redundant length, thereby facilitating the management and distinguishing of a user.

1. Name of the product in this design: Intensive Care Unit. 2. Purpose of this design: To provide a place for animals to receive medical treatment and rehabilitation. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The utility model belongs to the technical field of medical first-aid equipment, and discloses a full-automatic breathing balloon pressing device which comprises a breathing balloon body and a support, the breathing balloon body comprises a balloon, one end of the balloon is connected with a connecting pipe communicated with an inner cavity of the balloon, and the inner wall of the connecting pipe is connected with a pressure sensor and a flow meter respectively. According to the scheme, manual operation is replaced with the automatic pressing structure, and the problems that a traditional breathing balloon is unstable in pressing frequency, uneven in force, fatigue and the like are solved; a pressure sensor and a flow meter are combined to realize real-time monitoring and intelligent regulation and control, so that the ventilation pressure and the tidal volume are effectively controlled, and the safety is improved; the adjustable fixing assembly adapts to various balloon sizes, and stable pressing is ensured; the common and advanced modes adapt to different treatment requirements and are widely applied to pre-hospital first aid and intensive care, and the respiratory support efficiency and reliability are remarkably improved.

1.The name of the design product: treatment hospital transfer respirator. 2.The use of the design product: a medical device for intensive care and patient transfer in professional medical institutions. 3.The design points of the design product: the combination of shape, pattern and color. 4.The picture or photo that best shows the design points: perspective view. 5.The design claimed contains color.

The utility model relates to the technical field of neurology intensive care, in particular to an infusion device for neurology intensive care, which comprises a cushion, an adjusting device and a backrest, the cushion is provided with armrests on two sides, symmetrical connecting plates are arranged at two ends of the rear side wall of the cushion, a rotating rod is arranged between the two connecting plates, and the rotating rod is connected with the adjusting device. Wherein a first motor is arranged on the outer side wall of one connecting plate, a supporting plate is arranged on one side wall of the cushion, a fixing rod is arranged on the upper side wall of the supporting plate, the adjusting device comprises an adjusting box, a sliding rod, a sliding block and a second motor, a groove is formed in the adjusting box, an opening is formed in the front end of the groove, and the sliding rod is arranged in the groove. The sliding block is attached to the inner side wall of the groove and is in sliding connection with the inner side wall of the groove, a connecting rod is arranged at the front end of the sliding block, the connecting rod penetrates through the opening and is in sliding connection with the opening, and a hook is arranged at the lower end of the connecting rod, so that the infusion requirements of different patients are met, and the comfort degree is further improved.

The present invention comprises: a head unit which generates stimuli by means of power supplied from a main body unit, so as to deliver the stimuli to a user's skin; and an intensive care unit which is provided on the head unit so that when the head unit is pressed against the user's skin, the intensive care unit pinches an area of the user's skin to protrude outward and intensively applies stimuli to the protruding skin.

The embodiment of the invention provides an intensive care data acquisition method and system, which can solve the problems of alarm fatigue, low equipment management efficiency and data islanding existing in an ICU environment for a long time. The method comprises the following steps: receiving a Bluetooth broadcast data packet reported by a plurality of Bluetooth gateways deployed in an ICU ward, wherein the Bluetooth broadcast data packet comprises Bluetooth Beacon signals periodically broadcasted by bed unit Bluetooth tags configured by a plurality of sickbed units and low-power-consumption Bluetooth broadcast signals from a plurality of Bluetooth converters; performing position estimation on each Bluetooth converter based on the Bluetooth broadcast data packet, so as to automatically bind the medical equipment and the bed units according to the spatial position relationship between the Bluetooth converters and each bed unit; and when the equipment monitoring data from the Bluetooth converter is received, associating the equipment monitoring data with the patient information of the corresponding bed unit, and generating a structured monitoring data record with the unique identification of the bed unit, the patient identification and the medical equipment identification.

The utility model discloses a clinical fixing device for medical intensive care medicine, which comprises an arm fixing shell, the arm fixing shell adopts a square fixing tube shell structure and a hollow structure at the middle end, the upper surface of the arm fixing shell is provided with a curved concave surface, and the curved concave surface at the upper end of the arm fixing shell is provided with small ventilation holes. A circular hole is formed in the inner side surface of the lower end of the arm fixing shell, a convex circular shaft is clamped to the circular hole, a C-shaped mounting seat is fixedly connected to the lower surface of the convex circular shaft, a threaded hole is formed in the inner side surface of the lower end of the C-shaped mounting seat, and a threaded jackscrew is connected to the inner side surface of the threaded hole of the C-shaped mounting seat through threads; the arm fixing shell structure is adopted, the hollow structure is adopted, air holes are formed in the surface of the arm fixing shell structure, the arm is breathable after being fixed, the comfort degree is improved, the side face silica gel belt is used for clamping and fixing the arm, fixing is convenient, the bottom of the arm fixing shell is fixed to a table top through the rotatable C-shaped installation base, the angle can be adjusted, and installation is convenient and flexible.