163 results about "Oxyhemoglobin saturation" patented technology

The invention discloses an emotional pressure relieving and monitoring method combined with a virtual reality technology, and the method comprises the following steps: S1, providing a virtual environment for a user through a virtual reality device, and enabling the user to interact with the environment through wearing a virtual reality head-mounted device and using a controller; s2, collecting physiological data of the user in real time through a biosensor, wherein the physiological data comprises heart rate, brain wave, electrodermal response and oxyhemoglobin saturation; s3, inputting the physiological data in the S2 into a long-short-term memory network model for processing, and predicting emotional changes; s4, adjusting the virtual reality environment in real time to adapt to the current emotional state of the user based on the emotional state analysis and prediction result of the long-short-term memory network model; and S5, repeating the steps S2 to S4 to monitor the emotion of the user. According to the method, solid technical support is provided for emotion pressure management and monitoring based on the virtual reality technology, and a traditional static emotion regulation method can be effectively replaced.

The invention relates to the field of swimming physical training analysis, and particularly discloses a swimming underwater physical training effect analysis system based on training data, which is characterized in that video data, motion data and physiological data of a swimmer are acquired by integrating an underwater camera, an inertial measurement unit, a myoelectricity sensor, a heart rate sensor and a blood oxygen sensor; space-time synchronous analysis of multi-modal data is realized; on the basis of joint angle change consistency and muscle activation synchronism, whether the action of the swimmer is standard or not is judged, AR real-time feedback is conducted, and real-time correction of the swimmer in training is facilitated; the training load of the swimmer is evaluated based on the underwater speed, the stroke, the stroke frequency, the swimming distance and the swimming duration, and overrun early warning is carried out, so that making of a personalized training plan is facilitated, and meanwhile, overtraining is avoided; by monitoring the heart rate, the oxyhemoglobin saturation, the muscle activation duration and the joint activity condition of the swimmer, whether the swimmer has the injury risk or not is judged, early warning is triggered, and the injury occurrence rate is reduced.

The invention provides an electrocardiogram data analysis method, device, medium and equipment based on multi-modal fusion, which are applied to early warning of acute coronary syndrome (ACS). The method comprises the following steps: acquiring time sequence data of electrocardiosignals and ballistocardiogram signals as well as structural data such as heart rate, respiratory rate and oxyhemoglobin saturation by using a portable device, and preprocessing the data; constructing a double-branch global and local interactive feature extraction model, respectively extracting local and global features of the electrocardiosignal and the ballistocardiogram signal, and simultaneously bridging the isomerism of the two signal types; after feature mapping is carried out on the structural data, inputting the structural data and features of the time series data into a feature fusion model; and finally inputting the fused features into a disease early warning model, outputting an ACS risk probability, and comparing the ACS risk probability with a preset threshold value to realize real-time monitoring and early warning. The method is of great significance to prevention of ACS and guarantee of life health of high-risk groups with cardiovascular and cerebrovascular diseases.

The invention provides a fatigue driving monitoring method and system and a storage medium, and the method comprises the steps: obtaining a DMS video stream, carrying out the feature extraction of the DMS video stream, and obtaining a face ROI region; inputting the face ROI region into a regression model to extract skin brightness change characteristics of the driver, and obtaining multiple vital signs of the driver based on the skin brightness change characteristics; the vital signs at least comprise heart rate, respiratory rate, oxyhemoglobin saturation, blood pressure and heart rate variability; the vital signs are judged according to a preset time period and multiple vital sign threshold ranges, and when at least two of the multiple vital signs exceed the corresponding vital sign threshold ranges, it is judged that the driver is in the fatigue driving state. According to the method provided by the invention, multiple vital signs are detected by depending on one independent regression model, and the accuracy and timeliness of fatigue driving detection are improved.

The invention relates to the technical field of medical instruments, and discloses an intelligent device for monitoring the cardio-pulmonary function of a heart failure patient, the intelligent device comprises a multi-mode sensor module, an AI analysis module, a biological feedback module and a wearable carrier, the multi-mode sensor module is used for collecting heart rate, respiratory rate, oxyhemoglobin saturation and body movement data in real time, and the AI analysis module is used for analyzing the heart rate, the respiratory rate, the oxyhemoglobin saturation and the body movement data; monitoring modes can be dynamically switched in rest, motion and sleep scenes; the AI analysis module is used for detecting abnormity based on real-time data and predicting a heart failure deterioration risk in combination with historical data; and the biological feedback module is used for providing personalized intervention in a vibration or audio mode according to the analysis result. The heart rate, the respiration rate, the blood oxygen saturation and the body movement data are collected at the same time through the multi-mode sensor module, sleep apnea or periodic respiration is recognized in combination with the AI analysis module, the defect of separation of cardiopulmonary function monitoring and sleep mode analysis in the prior art is overcome, and therefore early intervention and treatment adjustment are supported.

The invention relates to the field of anesthetic concentration regulation and control, in particular to a method for analyzing and evaluating the administration concentration of an inhalation type anesthetic. The method comprises the following steps: firstly, according to characteristic data such as basic physiological data, previous anesthesia sensitivity and operation information of a patient, applying a fuzzy matching algorithm to obtain an initial administration concentration; physiological sign data such as blood pressure, heart rate, pulse oxyhemoglobin saturation and end-expiratory carbon dioxide partial pressure of the patient are monitored in real time in the anesthesia process and compared with a normal range, whether the physiological sign data are abnormal or not is judged, and an adjustment scheme of the administration concentration is determined according to the administration concentration-physiological sign correlation model; after the administration concentration is adjusted, the electroencephalogram double-frequency index is monitored to evaluate the anesthesia depth, the anesthesia depth matching degree is analyzed to judge the adjustment effect, and therefore closed-loop control over the anesthetic administration concentration is achieved. According to the method, the administration concentration can be accurately regulated and controlled, the concentration regulation mechanism is optimized, the safety and effectiveness of the anesthesia process are effectively improved, and a reliable guarantee is provided for clinical anesthesia.

The invention relates to the technical field of health management and medical information, and discloses an all-dimensional intelligent cardiopulmonary health management system and method and electronic equipment, and the system comprises a biological sensing module which is used for continuously collecting key physiological indexes of the heart rate, the oxyhemoglobin saturation, the respiratory rate and the motion state of a user; the data processing module is used for storing the collected physiological data and historical exercise records of the user through a central database of a cloud computing platform; the deep learning analysis module is a prediction model built based on a deep learning framework and is used for analyzing the physiological data of the user and generating a personalized exercise plan; the real-time monitoring module is used for detecting the physiological state of the user and automatically adjusting the exercise intensity or type when the physiological state exceeds a preset threshold value. The technical scheme that the multi-mode biosensor is combined with the real-time monitoring module is adopted, and the technical effect of comprehensively monitoring the cardiopulmonary function state of the user in real time is achieved.

The embodiment of the invention provides a control method of an oxygen generation system and an adjustable oxygen generation system, and belongs to the technical field of medical instruments. The control method of the oxygen generation system comprises the steps that 1, the threshold value interval of a pulse rate normal value and the threshold value of an oxyhemoglobin saturation normal value are obtained; 2, receiving a pulse rate monitoring value and a blood oxygen saturation monitoring value of a user of the oxygen generation system; 3, according to the threshold value interval, the threshold value, the received pulse rate monitoring value and the received oxyhemoglobin saturation monitoring value, the oxygen output quantity of the oxygen generation system is controlled, and the oxygen output quantity is the oxygen generation pressure and / or the oxygen output rate. According to the method, the performance parameters of the oxygenerator can be timely and automatically adjusted according to the physiological parameter change of the user of the oxygenerator, so that the requirements of the user at the current moment are met.

The invention discloses a method for diagnosing obstructive sleep apnea hypopnea syndrome, and relates to the technical field of medical diagnos.The method comprises the steps that an airflow curve and an oxyhemoglobin saturation curve of a patient during sleep are collected, all respiratory events are traversed and retrieved from the airflow curve, and according to the occurrence time of each respiratory event, all the respiratory events are determined; finding out a corresponding search window from the blood oxygen saturation curve, calculating the area of the search window of each apnea event, accumulating the areas of all closed areas to obtain an area sum, dividing the area sum by the total sleep time to obtain an index value of the sleep apnea specific hypoxia load, and determining the sleep apnea specific hypoxia load based on the index value and an index threshold value. Obtaining the symptom level of apnea of the patient; the method has the advantages of simple and convenient indexes, rapidness and high accuracy, and can be well applied to screening and diagnosis of the obstructive sleep apnea hypopnea syndrome.

The invention discloses an oxyhemoglobin saturation detection method and device, noise reduction equipment, a storage medium and a product, and relates to the technical field of artificial intelligence. The oxyhemoglobin saturation detection method comprises the steps that an initial pulse wave signal collected by photoplethysmography detection equipment is received, and whether a noise signal exists in the initial pulse wave signal or not is judged; if the noise signal exists in the initial pulse wave signal, the initial pulse wave signal is input into a noise reduction model to obtain a target pulse wave signal, and the noise reduction model is obtained through training by taking a historical pulse wave signal as input data and taking the denoised historical pulse wave signal as a label; the target pulse wave signal is sent to the photoplethysmography detection equipment, and the photoplethysmography detection equipment carries out blood oxygen concentration detection based on the target pulse wave signal. The accuracy of blood oxygen saturation detection is improved.

The invention discloses a six-minute walking test system and method, and the system comprises a motion collection device and a mobile device, and the motion collection device is connected with the mobile device through Bluetooth. The motion acquisition equipment comprises an electrocardio recorder, an oxyhemoglobin saturation instrument and a blood pressure instrument, and the electrocardio recorder is integrated with a motion sensor; the mobile equipment comprises a processor and a display screen serving as a display and input device, the display screen comprises a plurality of display areas, and the processor is used for executing the following operations: acquiring test data acquired by the motion acquisition equipment; according to the motion parameters, calculating motion data of the testee participating in the six-minute walking test; the test data and the motion data are displayed in different display areas in the form of charts or data. According to the embodiment of the invention, the motion sensor is integrated in the electrocardiogram recorder, so that the complexity of wearing equipment of the six-minute walking test system is simplified, and a test result can be directly displayed on mobile equipment.

The invention discloses an endoscope image processing method based on oxyhemoglobin saturation and multiple central wavelengths, and relates to the field of medical image processing.The method comprises the steps that a first initial image signal, a second initial image signal, a third initial image signal and a fourth initial image signal are obtained; calculating oxyhemoglobin concentration information of the target part according to the second initial image signal and the third initial image signal; calculating deoxidized hemoglobin concentration information of the target part according to the second initial image signal and the fourth initial image signal; calculating the oxyhemoglobin saturation of the target part according to the oxyhemoglobin concentration information and the deoxidized hemoglobin concentration information; performing brightness enhancement on the second initial image signal based on the oxyhemoglobin saturation to obtain a second enhanced image signal; and generating a target image according to the second enhanced image signal, the first initial image signal and the third initial image signal, wherein the target image is used for identifying the bleeding position of the target part.

The invention relates to an acute myocardial infarction intelligent diagnosis wearable device based on a structural causal model, belongs to the technical field of patient data processing, and solves the problems that patient data cannot be monitored in real time and the monitored data is inaccurate in the prior art. The wearable device for intelligent diagnosis of acute myocardial infarction comprises a blood pressure measuring instrument used for collecting a blood pressure signal of a user in real time; the electrocardio measuring instrument is used for collecting electrocardio signals of a user in real time; the blood oxygen measuring instrument is used for collecting a blood oxygen saturation degree signal of a user in real time; the pulse measuring instrument is used for collecting pulse signals of a user in real time; the signal processing instrument is used for processing the blood pressure signal, the electrocardiosignal, the oxyhemoglobin saturation signal, the pulse signal and manual input data to obtain causal data of acute myocardial infarction and an AMI prediction risk prediction value; and the display processing part is used for manually inputting data, displaying a historical monitoring result, displaying causal data of acute myocardial infarction and displaying an early warning risk prediction value.

The utility model relates to a monitoring head frame convenient to wear on the head, which comprises a head band, an electroencephalogram electrode, a brain oxygen probe, a TCD support and a fixing band, the head band can adjust the annular shape matched with the head, the electroencephalogram electrode is embedded on the head band and captures the electrical activity of the brain, the brain oxygen probe is arranged on the wearing inner side of the head band and measures the oxyhemoglobin saturation in the brain tissue, and the TCD support is used for supporting the brain. The TCD supports are arranged on the head band and located on the two sides of the head, TCD probes are arranged on the TCD supports and used for monitoring changes of cerebral blood flow, fixing holes are formed in the plate faces of the mounting supports, the fixing holes and the first adjusting holes are arranged up and down, the fixing holes are located above the first adjusting holes, and the two ends of the fixing band penetrate through the fixing holes in the two corresponding mounting supports to be fixed. Velcro tapes are arranged at the two ends of the fixing end, so that the brain oxygen probe, the electroencephalogram electrode and the TCD probe can be tightly attached to the head position, the accuracy of the monitoring result is improved, the fixing belt is fixed through the Velcro tapes, and the monitoring head frame can be adjusted according to different head shapes of different users.

The invention discloses an emergency nursing system capable of dynamically adjusting priority, which belongs to the technical field of emergency nursing and comprises the following steps: acquiring heart rate detection data, blood pressure detection data and oxyhemoglobin saturation detection data of a patient at preset time intervals, and filtering; setting a sliding time window, and respectively calculating a heart rate change rate, a blood pressure change rate and an oxyhemoglobin saturation change rate for the filtered heart rate detection data, the filtered blood pressure detection data and the filtered oxyhemoglobin saturation detection data in the sliding time window; correlation analysis is conducted on the heart rate change rate, the blood pressure change rate and the blood oxygen saturation degree change rate, parameter correlation characteristics are obtained, and a comprehensive parameter deterioration index is calculated; the comprehensive parameter deterioration index is compared with a preset threshold value, and whether a priority improvement mechanism is triggered or not is judged; and executing the priority lifting mechanism. By establishing a dynamic monitoring mechanism based on the change rate of the physiological parameters, real-time capture and quantitative analysis of the change trend of the illness state of the patient are realized.

The invention discloses an intelligent stretcher system and a data processing method. The intelligent stretcher system comprises a stretcher control module, a vital sign monitoring module, a stretcher state monitoring module, a wireless data module, a data processing module and a power module. The stretcher control module is used for regulating the posture of the stretcher; the vital sign monitoring module is used for monitoring heart rate, blood pressure, oxyhemoglobin saturation and body temperature data of a patient on the stretcher; the stretcher state monitoring module comprises an attitude sensor mounted on the stretcher and a plurality of pressure sensors for detecting the pressure of each position on the stretcher, and the attitude sensor is used for monitoring attitude data of the stretcher; the wireless data module comprises a multi-channel wireless data transmission module, and monitored vital sign data of a patient is transmitted to a remote monitoring center through a plurality of wireless data transmission channels; the power module is used for supplying power to the whole intelligent stretcher system. The data processing method comprises steps S1 to S8. According to the invention, real-time monitoring and far-end sharing of the vital sign data of the patient on the stretcher are realized.

The invention discloses a method for detecting heart rate, respiration and oxyhemoglobin saturation based on micro-vibration images, and belongs to the technical field of physiological detection and image processing. A camera collects facial micro-vibration videos of a testee in real time, uses an ROI algorithm to lock a facial key area, extracts RGB micro-vibration change signals to replace red light and near-red light signals, and determines whether the micro-vibration videos are abnormal or not; performing wavelet transform five-layer decomposition, three rounds of peak valley screening and abnormal value elimination on the RGB microvibration time sequence signal, performing fine tuning training by using a yov11 model, and calculating to obtain heart rate, respiration and blood oxygen physiological indexes. According to the invention, non-contact detection is realized through video acquisition and signal processing of micro-vibration of a face area, and the comfort level and the use convenience of a testee are improved; interference caused by motion artifacts, baseline drift and expression changes is eliminated through multi-scale wavelet denoising; the three-wheel peak-valley screening algorithm deeply excavates the features of the face micro-vibration signals, and the recognition accuracy of the signal peak-valley pairs is improved; and an abnormity elimination and self-feedback parameter adjustment mechanism improves the calculation precision.

The invention belongs to the field of artificial intelligence and contact type measurement, and discloses a blood oxygen saturation degree measuring method based on a smart phone camera. The method comprises the following steps: acquiring fingertip video data by using a smart phone under the condition of no external equipment, extracting a pulse photoplethysmography (PPG) signal from the fingertip video data, and constructing a multi-dimensional feature set through feature extraction and calculation; furthermore, the invention provides a two-channel deep learning model fusing a convolutional neural network and a long-short term memory network, the multi-dimensional feature set and the preprocessed PPG signal are processed in parallel, the advantages of the two networks in the aspects of feature extraction and time sequence modeling are fully exerted, and the accuracy of feature extraction and time sequence modeling is improved. And the sufficiency of the extracted features and the generalization ability of the model are ensured, so that the accurate estimation of the oxyhemoglobin saturation is realized. The research provides a feasible scheme for health self-examination in a family environment.

The invention discloses a chest image diagnosis method and system based on multi-modal sign collection, and relates to the technical field of medical image.The method comprises the steps that a chest image of a patient is obtained, electrocardiosignals and blood oxygen saturation data are synchronously collected, and an associated radiology report is obtained; the image lesion features and the frequency domain rhythm template are combined for processing, motion artifacts are eliminated through a frequency domain decoupling equation, and refined image features are output; inputting the refined image features and the text pathological semantic features into a bidirectional attention mechanism to generate fusion features, and splicing the oxyhemoglobin saturation data and the text pathological semantic features into a sign-text vector; and inputting the fusion feature and the sign-text joint vector into a multi-task loss function, and outputting a structured diagnosis report. According to the method, accurate elimination of motion artifacts is achieved through a frequency domain decoupling equation, and coupling calculation is conducted on an electrocardio rhythm template and image lesion features in a frequency domain space.

The invention discloses a method and device for determining SAS patients based on PPG signals, and relates to the technical field of biomedicine. The method comprises the following steps: acquiring a target continuous PPG signal and oxyhemoglobin saturation data of a patient within a set duration; determining a trough position of the target continuous PPG signal based on a window sliding minimum detection method, and cutting the target continuous PPG signal into at least two single PPG signals; determining at least one risk duration corresponding to the patient and a blood oxygen change amplitude corresponding to each risk duration from set durations according to the blood oxygen saturation data; performing multi-peak fitting processing on each single PPG signal by adopting a Gaussian function to obtain a Gaussian wave mean value variation amplitude corresponding to each risk duration; and determining an SAS result of the patient according to the blood oxygen change amplitude and the Gaussian wave mean value change amplitude corresponding to each risk duration and a judgment standard. According to the method, the Gaussian wave mean value is used for replacing the heart rate, interference of high-frequency signals can be effectively ignored, and the SAS detection result is more reliable.

The invention relates to a method for monitoring cerebral apoplexy, a device for monitoring cerebral apoplexy and a storage medium, and the method comprises the steps: collecting physiological parameters such as electroencephalogram (EEG), oxyhemoglobin saturation (SpO2), electrocardiogram (ECG) and blood pressure through wearable equipment or a family health monitoring system, and carrying out data preprocessing, feature extraction and anomaly detection; the EEG signals are processed by utilizing frequency domain characteristics and short-time energy analysis, and the cerebral apoplexy risk is identified by adopting a support vector machine (SVM) classification model. The system can analyze and detect abnormal conditions in real time, and sends out early warning information through a mobile phone App, a short message or a telephone to remind a user to see a doctor in time. The system comprises wearable equipment, a family health system, a hospital platform and a mobile health application, and is suitable for personal health monitoring and centralized monitoring of medical institutions. The real-time performance and accuracy of cerebral apoplexy monitoring are remarkably improved, the user experience is enhanced, the medical response speed is increased, and the method has wide application prospects and practical value.

The invention relates to the technical field of vehicles, in particular to a vehicle oxygen supply method and device, computer equipment and a storage medium. According to the altitude and the oxyhemoglobin saturation, an oxygen demand index is determined, and the oxygen demand index is in positive correlation with the altitude and is in negative correlation with the oxyhemoglobin saturation; a target oxygen supply mode is determined from candidate oxygen supply modes according to the oxygen demand index, the numerical value of oxygen supply parameters is determined according to the oxygen demand index, and the candidate oxygen supply modes comprise at least two of seat headrest diffusion oxygen supply, air conditioner air outlet oxygen supply and nasal catheter oxygen supply. By adopting the method, the problem of single oxygen supply mode in the prior art can be improved.

The invention relates to the technical field of intelligent medical treatment, and discloses a neonatal wearable physical sign monitoring device which comprises a plurality of collection points used for collecting neonatal physical sign signals, and the collection points comprise PPG sensor units which are arranged at different key positions of neonatal socks and have independent monitoring functions; the PPG sensor unit transmits collected photoelectric pulse signals to the processor module for processing, the processor module carries out fusion calculation on the signals of all collection points, and the final output of the oxyhemoglobin saturation and the heart rate of the newborn is obtained by integrating the data of all the collection points; the technical problems that an existing monitoring device for monitoring newborn physiological data is poor in wearing stability and poor in monitoring result accuracy are solved.

The invention relates to a multi-sensor fused vital sign and motion posture monitoring system and method. The system comprises a photoelectric volume pulse wave acquisition module, an electrocardio acquisition module, an inertia measurement module, a synchronization module, an artifact suppression module, a contact state recognition module, a data quality evaluation module, a vital sign extraction module and an anomaly detection module. Synchronously acquiring a photoelectric volume pulse wave signal, an electrocardiosignal and motion information; suppressing motion artifacts in the photoplethysmography signal and / or the electrocardiosignal based on the motion information; identifying the contact state and generating a data quality indicator related to the measurement reliability in combination with the de-artifact physiological signal; when the data quality meets a preset condition, heart rate, oxyhemoglobin saturation and / or breathing information are extracted, and vital sign parameters are formed; and carrying out conjoint analysis on the artifact-removed physiological signal and the motion information, and marking heart rate rhythm abnormity and / or posture abnormity. According to the invention, the reliability and availability of vital sign monitoring can be improved.

The invention discloses an inpatient alarm bracelet system and method based on multi-parameter vital sign monitoring, and relates to the technical field of inpatient alarm bracelets. Matching corresponding vital sign parameter initial weights from a preset disease-parameter sensitivity mapping library, wherein the vital sign parameters comprise heart rate, respiratory rate, oxyhemoglobin saturation, body temperature and heart rate variability; the method comprises the following steps: establishing an individualized physiological fluctuation baseline model based on vital sign data collected at the initial stage of wearing in combination with a resting state time period identified by an acceleration sensor, and generating a dynamic reference interval; collecting photoelectric volume pulse waves, electrocardiosignals, body temperature and acceleration data, judging whether motion artifacts exist or not by analyzing the spectrum correlation between physiological signals and motion signals, and generating a signal quality mark; and calling the initial weight and the dynamic reference interval under the condition that the signal quality mark indicates that the data is valid.

The invention discloses a physiologically-driven standardized intelligent simulation patient system, which comprises an adult simulation patient, a computer, a computer, a computer, a computer, a computer, a computer, a computer and a computer, wherein the adult simulation patient is made of a simulation man-made high polymer material, is environment-friendly and pollution-free, has obvious anatomical marks, touches two nipples, ribs, sternum and xiphoid processes, is flexible in joints, and realizes various operation body positions; wherein the physiological data comprises the heart rate, the blood pressure and the respiratory rate, the data is combined with a built-in physiological model to simulate the physiological state of a patient in real time, a monitor is simulated, real-time physiological data monitoring and feedback are provided, and the vital signs, the heart rate, the blood pressure and the oxyhemoglobin saturation of the simulated patient are displayed; the system has strong physiologically-driven standardized intelligent comprehensive simulation patient, can perform situational teaching according to a real clinical environment, effectively assesses the clinical thinking and personal operation skills of students, can greatly improve the team cooperation spirit of the students, and simulates the real physiological response and clinical scene.

The embodiment of the invention discloses a vehicle cabin oxygen supply control method and device, a vehicle and a storage medium, and the method comprises the steps: collecting image data of passengers in a vehicle cabin and pressure data of seats, and determining the types of the passengers based on the image data and the pressure data; based on the passenger type, the passenger blood oxygen saturation degree, the vehicle altitude and the cabin oxygen concentration, whether oxygen needs to be supplied to a vehicle cabin or not is judged; when the judgment result is that oxygen needs to be supplied to the vehicle cabin, determining the total oxygen demand based on the basic oxygen demand of each passenger category and the number of passengers; and oxygen is supplied to the vehicle cabin based on the total oxygen demand, so that the oxyhemoglobin saturation of the passenger is maintained in a blood oxygen reference range, and the oxygen concentration of the cabin is stabilized in an oxygen concentration standard range. According to the embodiment of the invention, the flexibility of a trigger mechanism and the oxygen supply accuracy during oxygen supply can be improved.

The invention relates to the technical field of risk scoring tools, in particular to a non-invasive simple risk scoring tool for traumatic hemorrhagic shock for wearable equipment. The method has the advantages that a non-invasive simple risk scoring tool for traumatic hemorrhagic shock is combined with clinical practice, economic benefits and time benefits are comprehensively considered, five vital sign indexes including systolic pressure, diastolic pressure, heart rate, respiratory rate and oxyhemoglobin saturation are used as the basis, a multi-factor Logistic regression method is used for constructing the risk scoring tool, and the risk scoring tool is used for evaluating the risk of traumatic hemorrhagic shock. The evaluation process does not need to depend on laboratory detection or highly specialized operators, and the first-aid personnel can master the use method in a short time and quickly complete evaluation. Due to the light design and the low operation threshold of the tool, the tool can be effectively applied in a non-professional scene, meanwhile, extra wounds to the wounded are reduced, the operation complexity is greatly reduced, and the risk scoring tool is more suitable for pre-hospital first aid and rapid deployment and application requirements in special scenes.

The invention belongs to the technical field of detection and early warning, and discloses an embedded pressure sore detection and early warning system and an automatic preventive measure starting device thereof, which improve the accuracy and sensitivity of monitoring, comprehensively monitor local pressure, oxyhemoglobin saturation and blood flow changes through the combination of a pressure sensor and an optical sensor, and improve the accuracy and sensitivity of monitoring. And pressure sore early warning failure caused by single parameter detection is avoided. Automatic intervention measures are achieved, prevention functions such as turning over and massaging are dynamically started through system design, nursing pressure is relieved, and the prevention effect is improved. And an embedded early warning system is designed, so that the device is suitable for mattresses, wheelchair cushions and other scenes, and the experience of patients is improved. The system integrates a pressure sensor and an optical sensor, and combines three models of PTIM, OSFM and MRAM to realize comprehensive analysis of multi-dimensional parameters of pressure, blood oxygen and blood flow, so that the sensitivity and accuracy of pressure sore risk prediction are greatly improved.

The invention discloses a plateau oxygen supply controller and method based on an event-triggered learning mechanism, and belongs to the technical field of plateau oxygen supply. The plateau oxygen supply controller comprises a blood oxygen saturation acquisition module and an event-triggered learning controller module of oxygen supply concentration; an oxyhemoglobin saturation SpO2 sequence is obtained through an oxyhemoglobin saturation acquisition module, and an arterial blood oxygen partial pressure PaO2 sequence is obtained through calculation according to an oxygen separation curve equation; the oxygen supply concentration percentage FiO2 is obtained; and the learning controller module is triggered by the event of the oxygen supply concentration to optimize the oxygen supply concentration percentage FiO2 through the minimum quadratic performance index. According to the plateau oxygen supply controller and method based on the event-triggered learning mechanism, the oxygen supply controller is designed for the resource-limited plateau hypoxia exercise process, so that the oxyhemoglobin saturation is effectively adjusted, and strong adverse reactions occurring in the hypoxia exercise process are relieved.