98 results about "Respiratory status" patented technology

The invention relates to the technical field of atomization rate control, in particular to an intelligent atomization compliance monitoring method and system for children. The method comprises the following steps: firstly, acquiring expiration flow velocity, inspiration flow velocity and multi-direction motion acceleration time sequence data of a child in a historical monitoring period, and reflecting breathing and behavior action conditions; dynamically analyzing the numerical characteristics of the expiration flow velocity and the inspiration flow velocity to divide a respiratory cycle, and analyzing the cycle length, the inspiration flow velocity cumulant and the like to construct a respiratory characteristic vector; screening a target monitoring period based on the breathing feature vector and the period number similarity; further analyzing the motion acceleration change and accumulation characteristics in the target monitoring period, and quantifying the behavior compliance expression degree; the behavior compliance expression degree and the breathing feature vector are deeply fused, a'breathing state-behavior cooperation 'joint evaluation model is established, the breathing and behavior states of children are dynamically recognized, the medicine atomization rate is accurately adjusted, and effective deposition of lung medicine is improved.

The invention discloses an intelligent nursing body position adjusting method and system based on respiratory function protection, and relates to the technical field of artificial intelligence and medical nursing. The method comprises the steps that body pressure distribution signals and respiratory thoracic impedance signals of a patient are collected in real time, a physiological data sequence is generated through Kalman filtering and wavelet fusion noise reduction, the physiological data sequence is input into a pre-trained deep learning network, and fusion feature vectors and body position performance indexes are output. And if the body position performance index is not lower than a preset threshold value, inputting the fusion feature vector into a pre-trained classification model, and outputting a classification label of the breathing state. A preset parameter optimization mapping table is inquired according to the classification labels, candidate parameter combinations sorted according to priorities are obtained, the parameter group with the highest priority is selected, a multi-motor cooperation instruction is calculated through a feedback control algorithm, and dynamic regulation and control of the bed surface are achieved. The invention aims to realize respiratory function protection and individualized nursing by sensing the respiratory state in real time, intelligently deciding and adjusting parameters, cooperatively executing control and adopting a safety protection mechanism.

The invention relates to the technical field of general control or regulation systems, in particular to a critical patient respirator parameter adaptive optimization control method, which comprises the following steps of: acquiring and processing physiological signals; constructing a dynamic respiration mechanical model based on a sliding time window recursive recognition algorithm; a man-machine coordination index is calculated, and the desynchrony degree is quantified; generating a ventilation parameter adjustment scheme through the reinforcement learning strategy network; and executing smoothing parameter adjustment, and introducing a safety boundary and a secondary fine adjustment mechanism. The breathing state of the critical patient can be accurately perceived and intelligently regulated and controlled, the ventilation efficiency is guaranteed, meanwhile, the man-machine synchronism and safety are improved, the medical care burden is relieved, and the prognosis of the patient is improved.

The invention discloses an external diaphragm pacemaker regulation and control method and device based on a respiratory radar. The method comprises the following steps: acquiring a chest radar echo signal of a target; analyzing the radar echo signal to obtain a target breathing signal; analyzing the target breathing signal to obtain breathing parameters, and generating a synchronizing signal; the treatment parameters are adjusted by adopting the breathing parameters and the synchronizing signals; the treatment parameters are adopted to output control signals; and regulating and controlling the external diaphragm pacemaker based on the control signal. The breathing state of the target is detected and sensed in real time through the breathing radar, key parameters are extracted, and the opportunity and intensity of electrical stimulation are dynamically adjusted based on the key parameters, so that personalized synchronization with the natural breathing rhythm is realized, and the treatment efficiency and the user comfort are improved.

The invention discloses a breathing equipment data processing method which comprises the following steps: synchronously collecting multichannel physiological signals through a built-in sensor of breathing equipment, carrying out noise processing and data standardization, and segmenting according to a time window to form data fragments; extracting breathing amplitude, frequency and morphological variability features of each data fragment, and combining to generate a multi-dimensional dynamic feature vector sequence; constructing a breathing state modeling system based on a hidden Markov model, training model parameters through a Baum-Welch algorithm, and calculating a prospective risk transition score by using a forward algorithm; and establishing an adaptive threshold strategy based on the risk transition score, carrying out structured labeling on the original respiration data, and generating processing data containing a prospective risk early warning label. Technical support can be provided for intelligent upgrading and personalized treatment of respiratory treatment equipment, and the accuracy, predictability and clinical practicability of respiratory anomaly detection are improved.

The invention discloses a breathing state detection method and system based on deep learning and a breathing machine, and the method comprises the steps: carrying out the preliminary simple filtering of airflow and air pressure data, and removing the interference of high-frequency noise on subsequent slices; judging a breathing cycle according to the waveform of the breathing data, and slicing the airflow and air pressure data according to the breathing cycle; converting the data from the time domain to the time-frequency domain, and obtaining the time-frequency domain characteristics of the signal; and inputting the obtained signal time-frequency domain characteristics into a neural network algorithm of each subtask, and identifying various states of the current equipment. According to the breathing machine control method, the accuracy of the breathing machine control method and the use experience of a user are improved by combining a multi-state recognition network of convolution, ResNet and Transform, and the robustness is enhanced through multiple recognition and a voting mechanism.

This invention relates to the field of nursing technology for disabled individuals, and particularly to a method and device for identifying the risk of aspiration in disabled individuals. The method includes: establishing a multimodal, non-invasive data acquisition system to simultaneously collect temporal information on laryngeal vibration, respiratory status, and facial movements; preprocessing to extract effective signals; constructing an individual-specific physiological baseline model using historical normal physiological samples and binding it to the individual's identity; segmenting and processing real-time signals to construct a three-dimensional feature collaboration matrix, calculating mutual information entropy, and dynamically iterating the associated baseline; temporally aligning swallowing and respiratory abnormality anchor points, marking key intervals, and screening suspected risk events; and outputting the final aspiration risk identification result after environmental interference filtering, feature weight adaptation, and verification. This invention enables accurate, real-time identification and early warning of aspiration risk without requiring any wearable devices and without affecting the daily care and rest of disabled individuals.

Disclosed is a minimally-invasive sensing device for measuring or estimating respiratory biomarkers. The device contacts a target body fluid detects for at least one target analyte and outputs a signal representative of a concentration of the analyte, from which biomarker information is determined. The present disclosure also relates to methods and systems using measurements or estimations of respiratory biomarkers to assess patient respiratory state, and / or assist in providing respiratory therapy to a patient.

The present application belongs to the technical field of sleep respiratory disease detection, and is a sleep apnea identification method based on a hybrid neural network. The method uses a millimeter wave radar to perceive human sleep in a surrounding bed environment, adopts spatial two-dimensional analysis to locate the chest cavity position, and solves the interference problem in radar sign extraction of different targets at the same distance. Shannon entropy of the respiratory signal is constructed as an iteration index of the whale optimization algorithm, and the minimum index is used to realize iteration optimization of the variational mode extraction parameter, so that different breathing states are matched with different parameters to accurately extract the main frequency narrowband respiratory signal. The respiratory time-frequency energy graph obtained through data processing is used as input, and a CNN network and a bidirectional long short-term memory module are used to jointly construct a feature extraction module, so that the application can identify the frequency change trend over time, capture more comprehensive features, and accurately identify target sleep apnea. In addition, the hybrid network can accurately classify unmanned scenes, apnea, low ventilation and normal breathing.

The utility model discloses an external breathing assembly for controlling inhaled air according to a breathing state. The external breathing assembly comprises a detection control unit and a breathing unit, the detection control unit comprises a breathing sensor, a switching valve and a control module, and the breathing sensor is used for detecting the expiration or inspiration state in the breathing unit; the switching valve is connected with the breathing unit, the switching valve is further provided with an air supply connector used for being externally connected with an air supply unit, and the control module is in communication connection with the breathing sensor and the switching valve and used for controlling the switching valve to act according to the expiration or inspiration state detected by the breathing sensor; by means of the external breathing assembly, the effects of providing gas during inspiration and stopping providing gas during expiration are achieved, various gas inspiration systems can control gas inspiration according to the breathing state, universal applicability is achieved, waste of effective gas is reduced, and the device is particularly suitable for existing atomizers, oxygen inhalation devices and the like.

The invention relates to a multi-dimensional vital sign signal reconstruction method based on multi-antenna WiFi signals. The method comprises the following steps: acquiring x groups of original vital sign CSI signals; de-noising processing is carried out and the signals are decomposed into respiratory signals and heartbeat signals; segmenting into a plurality of motion segment signals; performing mathematical representation on feature data in each motion fragment signal; enhanced signal processing is carried out, and then a feature matrix C corresponding to each motion fragment signal is constructed and formed; differential calculation is carried out, and then a respiration sequence signal and a heartbeat sequence signal are obtained; clustering calculation is carried out, and the motion category corresponding to each motion fragment signal is obtained through reverse deduction based on the clustering index labels. According to the method, weak motion interference can be recognized with high precision, stable and reliable feature support is provided for fine evaluation of the breathing state and recognition of the abnormal state, and therefore the stability of breathing state analysis in different dynamic scenes is further improved.

The invention belongs to the technical field of medical apparatus and instrument control, particularly relates to an atomization control system for respiratory nursing, and aims to solve the problems of low medicine deposition efficiency, serious waste and incapability of precise medicine administration caused by the lack of the capability of sensing and responding to the real-time respiratory state of a patient in a traditional atomization device. The system comprises a breathing state real-time monitoring module, an aerosol generation and regulation module, an intelligent control center, a man-machine interaction interface and a cloud data collaboration platform. Breathing parameters are collected through a high-sensitivity sensor, the particle size and the output opportunity of fog drops are dynamically adjusted in combination with a dual-mode ultrasonic atomization technology, and accurate inspiration phase dosing is achieved; a self-adaptive learning engine is arranged in the intelligent control center, the breathing cycle can be predicted, atomization can be started in advance, and the response speed is increased; local closed-loop control and remote personalized management are supported, and the medicine utilization rate and treatment compliance are remarkably improved.

This invention discloses an AI-assisted diagnostic system for CT rib fractures based on image recognition, belonging to the field of smart healthcare technology. It includes recognizing the patient's contour using thermal imaging data, constructing a respiratory model to analyze respiratory status, and automatically triggering CT image acquisition of the ribs at the optimal inhalation moment. Subsequently, artifact detection is performed; if qualified, the system is handed over to AI for intelligent fracture diagnosis, achieving a fully automated process from image acquisition to diagnosis. This invention uses non-contact thermal imaging to monitor respiration and body movement, constructing a respiratory model that integrates chest contour and airflow temperature changes, accurately identifying the optimal inhalation moment to trigger CT acquisition, reducing motion artifacts at the source and improving image quality. The system is highly robust, automatically determining the optimal acquisition time even under conditions of clothing or weak breathing, reducing reliance on patient cooperation, and is particularly suitable for rib fracture patients, improving examination success rate and efficiency.

According to the atomization device for the breathing machine, by introducing the structural design that a driving controller, a pressure sensor, a two-way connecting pipe, a three-way connecting pipe and an atomization cup work cooperatively, on-demand atomization control based on the breathing state of a patient is achieved; the core problems of medicine waste, environmental pollution, poor use experience and the like existing in a traditional continuous atomization mode are effectively solved. According to the invention, invalid aerosol generated in a non-inspiration period in a traditional'continuous atomization 'mode is avoided, and especially for high-value drugs (such as biological agents and inhalable antibiotics), the actual inhalation dose proportion can be obviously improved, the single treatment cost is reduced, and the treatment economy and the curative effect reliability are improved.

The application discloses a mesh nebulizer. The nebulization control method of the mesh nebulizer comprises the following steps: acquiring breathing data of a user; determining a breathing state of the user and an end time point of exhalation of each breathing cycle based on the breathing data; the breathing state comprises stable breathing and abnormal breathing; and controlling a running state of a nebulization sheet based on the breathing state and the end time point of exhalation. According to the breathing state of the user and the end time point of exhalation, the running state of the nebulization sheet is accurately controlled, so that the drug utilization rate is improved, and intelligent and personalized nebulization treatment is realized.

The invention discloses a non-contact breathing state monitoring method based on a millimeter wave radar, and belongs to the technical field of non-contact human body vital sign monitoring. The method comprises the steps that radar echo signals of a human body target are collected through a millimeter wave radar, a phase sequence is obtained through frequency mixing, filtering and phase demodulation, and breathing signals are extracted through phase unwrapping and displacement conversion; fourier transform is carried out on the respiratory signals, and the respiratory frequency and amplitude are calculated; a plurality of slope extraction algorithms are adopted, derivation is conducted on the respiration signals in the inspiration and expiration stages, and the respiration slope is obtained; and finally, integrating the respiratory rate, the amplitude and the slope, setting a threshold value and a scoring system, and quickly and accurately evaluating the respiratory distress degree. The method does not need to contact a human body, can penetrate through clothes, is suitable for various scenes such as clinical monitoring and emergency triage, and has the advantages of being easy and convenient to operate, high in real-time performance and high in reliability.

The invention provides a medicine content detection method combining a respiration simulation device and HPLC (High Performance Liquid Chromatography), which relates to the technical field of medicine detection and comprises the following steps: establishing a mathematical expression of a target medicine net peak area and a target medicine concentration under each respiration parameter combination and a mapping relation between the respiration parameter combination and a target medicine reference peak area; therefore, the target drug net peak area of the to-be-detected gas is determined, a plurality of similar breathing parameter combinations similar to the breathing state under the current breathing parameter combination are screened out, and the accurate value of the target drug concentration of the to-be-detected gas is determined by combining the corresponding confidence coefficient, so that the accuracy of the detection result is ensured, and the detection efficiency is improved. A mathematical expression for solving the target drug concentration under the current breathing parameter combination is established without multiple calibration tests, so that the workload is greatly reduced, and the drug concentration detection efficiency is improved.

The invention relates to the technical field of medical instruments, and provides a ventilation mask capable of switching high-flow oxygen supply in order to solve the problems that an existing ventilation mask is difficult to flexibly switch oxygen therapy modes according to the actual breathing state of a patient, and basic oxygen therapy and high-flow oxygen supply requirements cannot be met at the same time, the ventilation mask capable of switching high-flow oxygen supply comprises a mask body, and a sliding groove is formed in the front side of the mask body; a supporting platform is arranged on the inner side, and a supporting frame is arranged above the supporting platform; the gas injection mechanism is arranged on the supporting platform, one side of the gas injection mechanism is connected with a switching valve, and the gas injection mechanism is used for switching high-flow oxygen supply modes; and the nose switching mechanism is clamped on the support frame, is connected with the gas injection mechanism and is used for synchronously switching a high-flow oxygen supply mode with the gas injection mechanism. The breathing state of a patient can be monitored in real time, convenient switching between a low-flow oxygen supply mode and a high-flow oxygen supply mode can be rapidly achieved according to the breathing state of the patient, the oxygen therapy mask is suitable for the disease requirement of the patient from mild hypoxia to severe hypoxia, and the oxygen therapy requirements of different stages can be met without replacing the mask.

The utility model discloses an isolated respirator mask capable of monitoring the breathing of firemen, a monitoring assembly comprises an exhalation pressure monitoring device, a breathing frequency monitoring device and an exhalation temperature and humidity monitoring device, so that the monitoring assembly can monitor the exhalation airflow pressure, breathing frequency and exhalation airflow temperature and humidity of the firemen in the respirator mask respectively, thereby more comprehensively obtaining the breathing state of the firemen in the respirator mask, improving the monitoring reliability, and through the corresponding control of the air supply state of the respirator mask by the air supply adjusting assembly, ensuring that the firemen can breathe comfortably in the respirator mask, so as to improve the safety.

A dry powder inhalation system includes a breath detection device, a drug delivery device, and a computing device. The breath detection device is configured to monitor the breathing state of an animal and transmit the signals of the breathing state. The drug delivery device is configured to deliver the dry powder orally or nasally to the lungs of the animal. The computing device is configured to receive the signals of the breathing state, evaluate a stress state of the animal, predict a breathing cycle of the animal, and control the drug delivery device to release the dry powder during a non-stressed inhalation period for the animal to inhale the dry powder autonomously. A dry powder administration method is also disclosed.

The invention provides a wireless respiration monitoring system and method for clinical treatment, and relates to the technical field of respiration test medical treatment, and the method comprises the following steps: collecting respiratory muscle function physiological parameters of a clinical patient; establishing a mathematical evaluation model and a large sample healthy population database, and mapping and outputting a recovery evaluation initial value of the respiratory muscle function; interference item parameters of a clinical patient are collected, and an evaluation correction coefficient is obtained; and adjusting a recovery evaluation initial value of the respiratory muscle function output by the mathematical evaluation model to generate a recovery evaluation correction value. The breathing state quality of the patient after the clinical treatment stage can be predicted in advance through the mathematical evaluation model. In addition, through the collected interference item parameters, the initial value of the recovery evaluation can be calibrated, so that the finally output correction value of the recovery evaluation can more accurately predict the breathing state quality of the patient after the clinical treatment stage. And the accuracy is higher.

The invention relates to the technical field of atomizer regulation and control, in particular to a laryngeal medicine atomizer and an intelligent flow rate regulation and control system thereof. The system is used for determining a basic breathing state of a patient according to historical treatment information of the patient, and determining an initial atomization flow rate based on the basic breathing state; collecting real-time monitoring data, and determining an initial state normal degree index and a throat real-time stress degree index according to the real-time monitoring data; the initial atomization flow velocity is corrected according to the initial state normal degree index and the throat real-time stress degree index, and the corrected atomization flow velocity is obtained; and a control instruction is determined based on the corrected atomization flow speed, so that the atomizer outputs atomized medicine based on the control instruction. According to the invention, the accuracy of atomization flow rate control can be improved.

The invention discloses an adjustable breathing exercise device for breathing training, and relates to the field of medical equipment, the adjustable breathing exercise device comprises a hollow base and a connecting air pipe communicated with the base through a pipeline, an evaluation mechanism for evaluating the breathing state of a patient in real time is installed on the upper side of the base through a connecting piece, and the evaluation mechanism comprises a transparent pipe, a connecting pipe and a connecting rod, visual scale marks are axially arranged on the side wall of the transparent tube, and a plurality of air holes are formed in the circumference of the upper side of the transparent tube at equal intervals; through multi-dimensional innovation of a magnetic circuit structure, intelligent control and health protection, the intelligent breathing training device which is comprehensive in function, accurate in control and high in sanitation and safety is designed, and the remarkable beneficial effects of the intelligent breathing training device are reflected in the following four aspects: in the aspect of a training mode, through the electromagnetic coupling design of the first magnetic ring and the second magnetic ring, the training mode is optimized; and in combination with a built-in power supply module and a wireless transmission module, free electronic switching between an expiration training mode and an inspiration training mode is realized.

An ARI Smart Respiratory Inhaler (herein referred to as a "Smart Inhaler") with an integrated mist canister is disclosed. The smart inhaler is an Internet of Things (IoT) inhaler that delivers a medicament and measures pulmonary conditions, including partial pressure; nitric oxide; oxygen; a peak flow rate; and the forced expiration amount. The data is collected and transmitted to mobile applications and web portals, which allow patients and healthcare providers to track and view respiratory system status in real time. Other aspects include software and cloud networks with algorithms that can predict any trends or problems and alert stakeholders before they are likely to appear. The intelligent inhaler also utilizes a block chain technology to enable stakeholders to know treatment and health status in real time. The aim of the invention is to help a patient maintain its medication regimen and to rapidly provide the respiratory system status of the patient to a healthcare worker.

The utility model relates to respirator technical field, and disclose a kind of respirator comprehensive detector, including organism, the outer wall of organism is provided with upper end mounting rack, when using in daily life, different masks can be worn on simulation outlet seat, and then hydraulic rod can be started to stretch and contract, so that installation base plate can drive bellows to deform in the process of lifting, to simulate the breathing state of lung, and when installation base plate is lifted, material discharge vertical rod will be guided, and when installation base plate is displaced to bottom end, material discharge vertical rod will be thickened, at this time, the hole of installation base plate will be exposed, facilitate the installation base plate and the dust particle in bellows can be discharged, while bellows is displaced, it will be periodically rubbed by the arc rubber block on side plate, finally, through vibration, the dust particle in bellows can be better discharged, ensure the accuracy when simulating.

The invention relates to an atomization control method, device and system, atomization equipment and a storage medium. The method comprises the following steps: acquiring a first monitoring signal and a second monitoring signal of a breathing machine, and controlling an atomizer to start atomization under the condition that a breathing state is determined to be an inspiration state according to at least one of the first monitoring signal and the second monitoring signal; and controlling the atomizer to stop atomizing under the condition that the breathing state is determined to be an expiration state according to the running parameters of the breathing machine in the first monitoring signal and any one of the second monitoring signals, or under the condition that the breathing state is determined to be an abnormal state according to the alarm signal of the breathing machine in the first monitoring signal. Therefore, atomization is started only in the inspiration stage, atomization is stopped in the expiration stage and in the abnormal state, medicine waste is remarkably reduced, the effective utilization degree and the corresponding curative effect of medicine are greatly improved, and medical cost and environmental pollution are reduced.

The present application relates to the technical field of respiratory health monitoring, and discloses a remote respiratory health monitoring and management system and method. The method comprises collecting original respiratory data sets containing time sequence and frequency domain features through a multi-modal sensor, dividing respiratory cycle segments and extracting key waveform marker points through dynamic segmentation processing, constructing a respiratory state transition network to form a dynamic topology structure. A respiratory environment coupling matrix is generated in combination with environmental parameters, abnormal respiratory segments disturbed are screened, an analysis model is trained to output a deviation score, multi-level early warning is triggered, and a report containing a backtracking path is generated. Through cross-device verification and matching of user activity log timestamps, data is integrated to construct a respiratory behavior correlation graph, the model determination threshold is updated based on the graph, and the monitoring closed loop feedback is completed. The method realizes accurate monitoring and dynamic management of respiratory health, and provides a complete solution for remote respiratory health control.

The invention relates to the technical field of sleep health monitoring, in particular to a sleep apnea-oriented monitoring and feedback system, which comprises a sleep sensing module for acquiring physiological parameters, sleep behavior data and sleep environment parameters in sleep; the sleep breathing state analysis center performs sleep apnea type identification, severity evaluation and correlation analysis on a sleep cycle and a breathing event; the self-adaptive intervention feedback module dynamically adjusts intervention parameters according to the real-time analysis result and the physiological tolerance of the user and generates a basic feedback strategy; the multi-level risk assessment unit assesses a night hypoxia risk, a sleep structure disorder risk and a cardiovascular stress risk in real time, quantifies a risk weight, and generates a target feedback strategy in combination with historical sleep data of the user; and the cross-end cooperation unit links the household sleep monitoring terminal and the medical early warning terminal according to the intervention execution and state return instruction, executes feedback intervention and returns data. Therefore, the problems of low data accuracy, insufficient adaptability and the like in the prior art are solved.

This invention relates to the field of nebulizer technology, specifically disclosing a medical nebulizer adaptive control method and system based on real-time expiratory volume feedback. The system includes a control module, a nebulization execution module, and a respiratory feature analysis module. The control module is communicatively connected to both the nebulization execution module and the respiratory feature analysis module. The respiratory feature analysis module acquires a user's dynamic respiratory feature dataset in real time and sends it to the control module. The control module acquires a respiratory assessment index based on the user's dynamic respiratory feature dataset and acquires nebulizer control information in real time. It then obtains the user's respiratory-nebulization matching degree based on the respiratory assessment index and the nebulizer control information. This invention enables a deep match between nebulization parameters and the patient's respiratory state and individual characteristics, improving drug deposition efficiency and treatment accuracy. In terms of data monitoring and application, the nebulization execution module monitors drug release data in stages.

The invention discloses an intelligent expectoration optimization system and method, and belongs to the technical field of medical health, the intelligent expectoration optimization system comprises a data monitoring module, and the data monitoring module comprises a respiration monitoring unit, a cough acquisition unit and a sputum detection unit; the respiration monitoring unit is used for monitoring the respiration frequency, depth and rhythm of the patient; the cough acquisition unit is used for acquiring cough sound and vibration signals of a patient and analyzing the strength of the cough; the sputum detection unit is used for detecting the color, viscosity and amount of sputum of a patient; the data calculation module is used for calculating the time interval between every two adjacent coughs of the patient, and in the time interval, the change of the breathing frequency of the patient is calculated on the basis of the previous cough. Through precise monitoring and intelligent optimization, the breathing state of the patient can be comprehensively evaluated, the expectoration effect is improved, discomfort of the patient is reduced, the infection risk is reduced, the medical efficiency is improved, and support is provided for treatment and rehabilitation of respiratory system diseases.