54 results about "Lowered consciousness" patented technology

The invention relates to the technical field of medical data processing, in particular to a multi-feature recognition based postoperative anesthesia patient state quantitative evaluation method. According to the method, the anesthesia postoperative state is divided into a deep anesthesia stage, a superficial consciousness recovery stage and a cognitive recovery stage based on clinical observation. In the deep anesthesia stage, physiological feature data are collected at high frequency, and a physical sign health index is obtained by calculating the standardized deviation between the physiological feature data and a normal reference value; in the shallow consciousness recovery stage, physiological feature data and unconsciousness behavior data are collected, a weighted model is constructed in combination with the physical sign health index, and an unconsciousness behavior response index is obtained; in the cognitive recovery stage, physiological feature data and subjective feature data are collected, and short-term trend prediction is performed on a cognitive recovery index based on a grey prediction model. Furthermore, multi-source feature data of the three stages are fused to construct a dynamic trajectory prediction model, the postoperative recovery trend and state change of the patient are comprehensively analyzed, and quantitative evaluation of the postoperative delirium risk is achieved.

The invention discloses an anesthesia state evaluation method and device suitable for patients of different ages and a medium, and belongs to the technical field of neural signal analys.The method specifically comprises the steps that electroencephalogram response signals triggered by stimulation input events corresponding to the patients of different ages in different consciousness states are collected; extracting nerve conduction delay time and frequency domain energy characteristics based on the electroencephalogram response signal, and constructing a delay characteristic vector based on the nerve conduction delay time and the electroencephalogram signal frequency domain energy characteristics; inputting the age data and the delay feature vector of each training patient into a preset training model, and generating a state recognition model; the method comprises the following steps: analyzing nerve conduction velocity migration features of patients of different ages under different consciousness states, acquiring the age and delay feature vectors of a current patient, inputting the age and delay feature vectors into a state recognition model, and judging the anesthesia state of the patient. And prediction and accurate evaluation of anesthesia states of patients of different ages are realized.

Disclosed are systems and methods that provide a novel computerized framework for a closed-loop, decision-intelligence (DI)-based computerized framework for automatically and dynamically managing and controlling a medical procedure, inclusive of administered medication and / or anesthesia to a patient and an intraoperative level of consciousness of the patient. The disclosed framework provides an improved electroencephalography (EEG) indices that adapts to specific patient needs, and dynamically adapts to factors of an ongoing procedure to ensure that the proper levels of anesthesia are administered, required and / or maintained. This provides computerized capabilities to maintain safe levels of the patient's consciousness, such that post-operative patient health is preserved and maintained. Thus, the disclosed framework provides an effective anesthesia management framework that can be leveraged to safely manage a patient's health during and after a medical procedure for which anesthesia is used.

The invention discloses a medical comprehensive assessment method for old people and related equipment, and relates to the field of health management, and the method comprises the steps: obtaining the basic information of the to-be-assessed old people; carrying out body function state evaluation on the human body to obtain a body function state evaluation result related to the life self-care ability and the falling risk; performing nutrition state evaluation on the old people based on the nutrition evaluation scale to screen the risk of malnutrition; performing psychological state assessment on the old people to obtain psychological state assessment results including cognitive functions, emotional states and consciousness states; and comprehensively integrating the basic information, the body function state evaluation result, the malnutrition evaluation result and the psychological state evaluation result to form an old people comprehensive evaluation report. The evaluation report can reflect the health risk characteristics of the old people from multiple dimensions, and provides a scientific basis for the formulation of subsequent medical schemes, nursing measures or intervention strategies, thereby facilitating the improvement of the pertinence and effectiveness of the health management of the old people.

The present invention provides a system for assessing the state of consciousness of injured persons based on facial recognition, which relates to the field of health assessment technology. It includes a facial information extraction module, a facial feature analysis module, a state of consciousness calculation module, an anomaly detection module, and a state of consciousness assessment module. In the present invention, an infrared camera is used to carefully capture the subtle movements of the muscles around the eyes, corners of the mouth, and forehead, thereby improving the accuracy and comprehensiveness of data collection. By evaluating the blinking frequency, displacement of the corners of the mouth, and stretching amplitude of the forehead muscles, the accuracy and dimension of the assessment are improved. By extracting deformation features and calculating the gradient of motion amplitude, combined with time series analysis, the assessment of the state of consciousness becomes more sensitive and accurate, and is able to detect potential changes in consciousness in a timely manner, thereby responding quickly. The density and distribution feature analysis of mutation points provide rich data interpretation for diagnosis and monitoring, so that the state of consciousness of the injured person can be quickly and accurately assessed without contacting the injured person.

The invention discloses a modeling and intervention simulation method and system for children with difficulty in reading and writing Chinese based on a digital twin brain technology. A data acquisition module acquires behavior data and brain imaging data of children with difficulty in reading and writing Chinese and normal contrast children; constructing a Chinese read-write digital twin base model by using a model construction module, and simulating function shunting and consciousness formation dynamics in a brain read-write process; the individualized modeling module adopts a double constraint optimization method to carry out individualized fine tuning on the Chinese read-write digital twinborn base model and establish an individualized digital twinborn model; the intervention simulation module carries out verification and mechanism analysis on the individualized digital twinborn model, simulates different intervention strategies, predicts the improvement effect of the intervention strategies on individual read-write behaviors and brain characterization, and recommends and outputs an individualized intervention scheme; aiming at individual digital twinning modeling with difficulty in reading and writing in Chinese, an exclusive individual digital twinning model is constructed for each tester, and individual heterogeneity with difficulty in reading and writing is analyzed.

This invention discloses a heatstroke prevention and monitoring system based on conscious cognitive behavioral characteristics, belonging to the field of intelligent medical technology. This invention addresses the problems of existing technologies lacking intelligent analysis and exhibiting a certain degree of subjectivity, making it difficult to ensure the effectiveness of heatstroke prevention and monitoring. It analyzes the patient's physiological signals and behavioral data using a linear discriminant analysis model to predict whether the patient has heatstroke. After predicting heatstroke, a weighted average method is used to further calculate the patient's risk index, and different prevention and monitoring strategies are implemented based on the risk index. Based on this, it can effectively identify whether a patient has heatstroke and the risk index, thereby enabling targeted preventative measures to avoid further disease progression. Simultaneously, through intelligent analysis and judgment, it can effectively reduce the incidence of heatstroke, reduce the consumption of medical resources, and lower the socioeconomic burden.

The invention belongs to the technical field of medical instruments, particularly relates to a supporting assembly and a post-anesthesia awakening bed of a medical health big data sharing platform, and solves the problems of single traditional awakening mode, inconvenient monitoring and the like. The awakening bed is provided with the supporting assembly, a bed plate I and a bed plate II are arranged in a bed frame, a driving structure can enable the bed plate II to incline, a bracelet is arranged, and a monitoring structure is arranged on the bracelet; a hollow lead screw penetrates through a bed plate I in a threaded mode, an ejector rod pushes a piston plate to inject air into an annular rubber air bag through a hose, a detection structure is made to be tightly attached to the skin, and the physical condition of a patient is monitored in real time and transmitted to a platform; the knocking structure enables the knocking plate to intermittently knock the arch of the foot of the patient, consciousness recovery of the patient is promoted in multiple modes, real-time monitoring and data uploading are achieved, and doctors can conveniently observe the illness state.

This application provides a method and system for analyzing EEG consciousness monitoring data applied to anesthesia management. The method includes: acquiring EEG signal entropy sequence data of anesthetized subjects; performing dynamic entropy change analysis on the EEG signal entropy sequence data to obtain the entropy change feature vector of the anesthetized subjects; performing temporal phase coupling modeling on the EEG signal entropy sequence data to obtain the phase synchronization feature matrix of the anesthetized subjects; generating consciousness state fusion features of the anesthetized subjects based on the entropy change feature vector and the phase synchronization feature matrix; predicting the anesthesia state of the anesthetized subjects based on the consciousness state fusion features; and obtaining the EEG signal entropy of the anesthetized subjects at sampling time points in a second time period. This application can accurately predict the EEG signal entropy of anesthetized subjects at sampling time points in a second time period, helping to more accurately monitor the anesthesia state of anesthetized subjects so as to adjust the dosage of anesthetic drugs in a timely manner and ensure the safety and effectiveness of the surgical procedure.

The application discloses a consciousness disorder patient emotion recognition system based on electroencephalogram microstate analysis, comprising: an electroencephalogram data acquisition module, which is used for presenting emotional stimuli to a consciousness disorder patient according to a preset emotional stimulus paradigm and collecting multi-channel electroencephalogram data; a data preprocessing module, which is used for preprocessing the electroencephalogram data to obtain pure electroencephalogram data; a feature extraction module, which is used for extracting features from the pure electroencephalogram data to obtain microstate features related to positive and negative emotions; a feature fusion module, which is used for fusing the microstate features related to positive and negative emotions to construct a feature representation capable of comprehensively reflecting the emotional state of the patient; and an emotion classification module, which is used for training and classifying the fused features by using a classification model to obtain a patient emotion recognition result. The application realizes objective recognition of the emotions of the consciousness disorder patient, thereby providing an objective neurophysiological index for clinical consciousness judgment and prognosis evaluation.

Disclosed are systems and methods that provide a novel computerized framework for a closed-loop, decision-intelligence (DI)-based computerized framework for automatically and dynamically managing and controlling a medical procedure, inclusive of administered medication and / or anesthesia to a patient and an intraoperative level of consciousness of the patient. The disclosed framework provides an improved electroencephalography (EEG) indices that adapts to specific patient needs, and dynamically adapts to factors of an ongoing procedure to ensure that the proper levels of anesthesia are administered, required and / or maintained. This provides computerized capabilities to maintain safe levels of the patient's consciousness, such that post-operative patient health is preserved and maintained. Thus, the disclosed framework provides an effective anesthesia management framework that can be leveraged to safely manage a patient's health during and after a medical procedure for which anesthesia is used.

The application provides a method, system, device and medium for determining anesthesia consciousness, which comprises: obtaining a target electroencephalogram signal of a target object; determining consciousness state information of the target object based on the target electroencephalogram signal through a consciousness determination model, wherein the consciousness state includes a conscious state, a light anesthesia state and an unconscious state; wherein the consciousness determination model is a machine learning model, and the consciousness determination model is obtained based on training samples, wherein the training samples include sample electroencephalogram signals, and the sample electroencephalogram signals include sample conscious state data, sample light anesthesia state data and sample unconscious state data. Through the trained consciousness determination model, the change in anesthesia depth of the target object during the operation and the smooth transition thereof can be accurately tracked on the basis of accurately determining the unconscious state or the non-unconscious state of the target object, so that the regulation of the amount of anesthetic drugs for the target patient during the operation is more accurate.

The utility model discloses an old-age nursing bed with a protection function, which comprises an old-age nursing bed body, the lower surface of the old-age nursing bed body is fixedly connected with rollers, and the inner surface of the old-age nursing bed body is connected with a sliding rod in a sliding manner. By arranging the motor, the transmission shaft, the first conical teeth, the lead screw and other structures, overall lifting of the sliding rod, the guardrail and the connecting plate can be achieved, so that the old can be effectively prevented from accidentally falling off during sleeping or resting while getting up of the old is not hindered, a physical barrier is provided especially at night or when the old are unconscious, and the safety of the old is improved. By arranging a guide rod, a sliding seat and a table plate, the old can directly use the table plate to have dinner, read, write or use electronic equipment on the bed, so that the convenience of daily activities is improved, and by arranging a rotating shaft, a gear, a limiting assembly and other structures, the table plate can be folded and stored when not used, so that the safety of the old is improved. And the practicability is improved.

The invention discloses an emotion recognition, consciousness evaluation and auxiliary rehabilitation method and device based on closed-loop olfactory stimulation, and a medium, and relates to the technical field of neural function diagnosis and artificial intelligence, and the method comprises the steps: obtaining a first face image sequence of a patient under odor stimulation; inputting the first facial image into a facial action unit intensity estimation model, and obtaining a plurality of facial action unit recognition results output by the model online; determining the facial expression change intensity of the patient based on the recognition results of the plurality of facial action units; and under the condition that the facial expression change is lower than a preset threshold value, adjusting the concentration and the type of the odor stimulation in real time based on a preset concentration gradient, and re-collecting the image for evaluation. Through multiple expression intensity results, the consciousness level of the patient is determined, the olfactory consciousness brain network remaining condition is judged, a rehabilitation training scheme is formulated, and longitudinal tracking is implemented. The emotion and consciousness level of the patient can be accurately evaluated in real time, and the method is applied to olfactory stimulation assisted rehabilitation.

The embodiment of the invention provides an inquiry method and device and a storage medium. The method comprises the steps that a target medical expression corresponding to the chief complaint content of a patient and consciousness state data of the patient are acquired; determining at least one target red flag symptom from a plurality of preset red flag symptoms according to the target medical expression and the consciousness state data; determining a plurality of inquiry targets according to the target medical expression and the obtained target red flag symptom, and determining an inquiry strategy and an inquiry sequence of each inquiry target according to the consciousness state data; performing interrogation on the patient according to the interrogation strategy and the interrogation sequence of each interrogation target; and outputting the inquiry medical history of the patient according to the answers of the patient to the plurality of inquiry targets. According to the embodiment of the invention, patients with unconsciousness can be accurately inquired.

The invention discloses a spinal cord electrical stimulation prognosis prediction system for a patient with disturbance of consciousness based on neurovascular coupling, and belongs to the technical field of brain-computer interfaces. The system synchronously acquires electroencephalogram and cerebral blood flow signals of the patient through electroencephalogram acquisition equipment and transcranial Doppler ultrasound; brain network connections are calculated by using weighted pairwise phase congruency indexes, neurovascular coupling parameters are calculated based on a phase-amplitude coupling method, and finally results are presented through a display module to predict prognosis. The system can solve the problem of clinical lack of prognosis evaluation indexes of SCS treatment consciousness disorder patients, has the advantages of simple acquisition equipment, reusability and the like, and can assist doctors in providing personalized clinical schemes and reducing the treatment cycle; the system relates to a data acquisition, processing and result display module, a key parameter calculation process is clear, and the system is suitable for prognosis evaluation after SCS implantation of a consciousness disorder patient.

This invention discloses an intelligent terminal interactive awakening system and method for patients with impaired consciousness based on Traditional Chinese Medicine (TCM) rules, belonging to the field of intelligent medical technology. The system includes a data acquisition module that acquires multidimensional clinical data of patients with impaired consciousness. Through data cleaning and standardization, an initial patient clinical information matrix is ​​constructed to obtain a structured dataset of impaired consciousness features. An intervention plan generation module generates a preliminary intervention intensity curve based on the structured dataset. For this preliminary intervention intensity curve, boundary condition constraint technology is used to set upper and lower limits for intervention intensity and time. Simultaneously, a smoothness weight allocation method is used to adjust the importance parameters of time points to obtain a smooth intervention execution plan. This intelligent terminal interactive awakening system and method for patients with impaired consciousness based on TCM rules achieves precise and personalized intervention for these patients, improves treatment outcomes, and provides new ideas and methods for clinical practice.

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

The application relates to the technical field of anesthesia post-complication monitoring, in particular to an intelligent early warning system for post-anesthesia complications of surgical patients. The system obtains the intraoperative risk degree according to the size and change of the intraoperative body index data of the patient in each first preset time period, the past medical history score and the allergy history score of the patient, and then judges the intraoperative anesthesia complication patients and the intraoperative normal patients in real time; the postoperative risk degree is obtained according to the size of the postoperative body index data of the intraoperative normal patient in each second preset time period, the consciousness state score, the nervous system score, the wound recovery score and the wakefulness state of the intraoperative normal patient, and the intraoperative risk degree of the intraoperative normal patient, and then the postoperative anesthesia complication patients and the postoperative normal patients are judged in real time. The intraoperative risk degree and the postoperative risk degree are accurately obtained in real time, so that the post-anesthesia complications of the patient can be accurately detected in time, and measures can be taken in time, and the harm of the post-anesthesia complications is effectively reduced.

The invention discloses a heat preservation auxiliary fixing device for an anesthesia awake patient and an implementation method of the heat preservation auxiliary fixing device. A mattress is arranged at the upper end of a bed board in the device; an operation screen and a push handle are arranged at the rear end of the bed plate through a mounting plate; a body fixing mechanism is arranged on the mattress, two arm fixing mechanisms are installed on the two side faces of the mattress, a quilt curling mechanism is installed at the tail end of the mattress, and a heat preservation quilt is installed in the quilt curling mechanism. A warm air spraying mechanism is arranged at the upper end of the arm fixing mechanism, the warm air spraying mechanism is movably connected with the arm fixing mechanism, the warm air spraying mechanism is electrically connected with a warm air box, and the warm air box is fixed to the lower end of the bed board; supporting legs are installed at four corners of the bed board. The technical effects are achieved as follows: a patient is fixed through the body fixing mechanism and the arm fixing mechanism, the patient is prevented from consciously conscious and consciously consciously consciously and consciously consciously moving to interfere with a detection line in the anesthesia awakening period, and the warm air spraying mechanism is matched with the heat preservation quilt to realize heat preservation of the patient and avoid the shivering phenomenon of the patient.

The invention provides an electroencephalogram coding method and system for communication of patients with disturbance of consciousness, and relates to the technical field of electroencephalogram coding. The method comprises the following steps: constructing a codebook of multi-dimensional stimulation and response dimensions, mapping information units into code words, and setting separability and length constraints; a frame structure comprising a synchronization preamble, a code element area, a verification and error correction area and a confirmation and retransmission area is adopted for transmission; collecting and weighting multi-channel electroencephalogram signals under time sequence constraints, and decoding and outputting confidence coefficients based on observation signals; when the confidence coefficient is lower than a threshold value, adaptive retransmission and redundancy lifting are executed; evaluating a load index in real time, dynamically adjusting frame and strategy parameters, and switching a sensory mode; and a result is output and feedback is combined to complete closed-loop transmission, so that high-precision, stable and tolerable alternating current is realized.

The vomit collector comprises a vomit bag and a measuring container matched with the vomit bag, scale marks are arranged on the measuring container, a strip-shaped air bag is arranged along an opening of the vomit bag, and an air pressure adjusting opening is formed in the air bag in a matched mode. Two ear hanging belts are arranged on the air bag, and each ear hanging belt is connected with a tightening belt through an annular belt; a bag body of the vomit bag is provided with a cannula opening, and a valve and a sealing plug are arranged in the cannula opening. On the basis of preventing vomitus from polluting the surrounding environment and increasing the occupational exposure risk of medical staff, the vomitus metering device gives consideration to sealing performance and comfort, can be used in cooperation with a stomach tube at the same time, and can accurately meter the vomitus.

The invention belongs to the related technical field of pediatric respiratory nursing, and particularly relates to a pediatric respiratory nursing rehabilitation training auxiliary blowing and sucking device which comprises a base, a fixing frame is fixedly connected to the upper end of the base, a cylinder is fixedly connected to the upper end of the fixing frame, and an air bag body is arranged at the left end in the cylinder. In the respiratory rehabilitation training process of a pediatric patient, the circular plate and the push plate are pushed to move by expanding the air bag, the displacement distance is clearly indicated on the graduated scale plate through the indicating arrow linked with the circular plate and the push plate, and for the child patient, dull training is difficult to insist; by means of the method, abstract breathing force can be converted into specific and visible scores, namely the arrow moving distance, training interests and competition consciousness of child patients can be greatly stimulated, passivity is changed into active, and compliance is improved.

The invention discloses a brain monitoring method and system for a patient with disturbance of consciousness, and belongs to the technical field of medical monitoring. A brain monitoring system for a patient with disturbance of consciousness comprises a patient brain monitoring module and a patient demand recognition module. By continuously acquiring the electroencephalogram activity signals and combining with the effective connection analysis algorithm, the brain monitoring information flow graph of the patient with the disturbance of consciousness can be constructed, signal transmission and causal intensity between different brain function areas can be accurately reflected, the brain activity of the patient with the disturbance of consciousness can be monitored in real time, and accurate evaluation of the brain state of the patient is ensured; by combining the electroencephalogram activity signal and the body movement monitoring signal, the physiological state of the patient can be comprehensively analyzed, the body movement data of the patient during unconscious activity is captured, and the monitoring comprehensiveness and accuracy are further improved.

The invention discloses an ecological healing model system and method based on natural connection and consciousness expansion. The ecological healing model system comprises an evaluation module, a natural activity module, a technical intervention module and a data analysis module. The influence of multi-sensory stimulation in the natural environment on the neural mechanism of the teenagers and family members of the teenagers is systematically discussed for the first time, the brain-computer interface technology and the psychological evaluation tool are combined, the internal relation between natural healing and consciousness expansion is revealed from the two aspects of neurophysiology and psychology, and the limitation of traditional psychological treatment is broken through. Through case research and multi-channel psychological evaluation verification, 12 weeks of intervention shows that the natural connection degree of participants is remarkably improved, the psychological pressure is remarkably reduced, and the psychological toughness is remarkably enhanced, which shows that the model has a remarkable effect on promoting the psychological health of teenagers.

The invention relates to the technical field of consciousness state monitoring, in particular to a consciousness state real-time monitoring system and method based on multi-modal physiological signal fusion, and the system comprises a server side and a medical care side; the server comprises a physiological index data acquisition module used for acquiring current physiological index data of a target patient, and a feature extraction module used for performing feature recognition extraction on the acquired current physiological index data to form corresponding feature data; the consciousness state recognition module is used for taking the extracted feature data as input data, inputting the input data into a pre-trained consciousness state classification model, and outputting consciousness state type data corresponding to the target patient; and the feedback module is used for feeding back the consciousness state type data corresponding to the target patient to the medical care terminal of the medical care personnel.

The utility model discloses a urine bag special for a patient with disturbance of consciousness. The urine bag comprises a bag body, a butt joint mechanism, a non-return mechanism, a sensor and a beeper. The bag body is provided with a drainage opening matched with urine to flow in, and the butt joint mechanism is arranged on the outer surface of the bag body, communicated with the drainage opening and used for fixing the bag body to a patient; the non-return mechanism is arranged between the bag body and the butt-joint mechanism, so that urine flows into the bag body from the butt-joint mechanism and is prevented from flowing back into the butt-joint mechanism from the bag body; the sensor is arranged at the bottom of the bag body and electrically connected with the pager, and the sensor can detect urine in the bag body to start the pager. Compared with the prior art, the special urine bag for the patient with the disturbance of consciousness not only can prevent urine from flowing back and overflowing, but also can remind medical staff to replace the bag body in time, so that the comfort level of the patient lying in bed is greatly improved.

The electric displacement robot with the liftable and telescopic seat plate is suitable for various bed heights and use scenes, the three-degree-of-freedom lifting mechanism can achieve large-range adjustment of the seat plate in the horizontal direction and the height direction, the robot can be flexibly in butt joint with sickbeds, wheelchairs and pedestal pans of different heights, adaptability is improved, and the robot is suitable for being used in various bed heights and use scenes. Posture adjustment and repeated operation in the patient shifting process are reduced; the structure supports the patient to autonomously adjust the position of the seat plate through a simple control interface (such as a button, a remote controller or a voice instruction), is particularly suitable for the old or the postoperative rehabilitation person with sober consciousness but limited action, relieves the nursing burden, and improves the independence and dignity of the patient; the seat plate is provided with a defecation hole structure, so that the seat plate can be directly butted with a pedestal pan, and the patient can conveniently defecate. Meanwhile, nursing personnel can conveniently clean the buttocks on the premise that the patient does not need to be greatly moved, and the nursing efficiency and comfort are improved.