255 results about "Respiratory status" patented technology

The invention provides an expectoration auxiliary control method and device. The method comprises the steps that audio signals of breathing sounds and cough sounds at multiple positions of the chest of a patient are collected through an audio sensor array, and a standardized audio feature data set is obtained through noise reduction, segmentation and feature extraction; a dynamic weighted graph model is constructed, and a random edge sampling algorithm and a parallel batch processing dynamic algorithm are combined to analyze and obtain a sputum viscosity index and a sputum distribution position map; based on the result, mapping the vibration parameter space into an unweighted disk diagram, and obtaining a personalized vibration treatment scheme by using a shortest path algorithm; in combination with the real-time breathing cycle of the patient, working parameters of the sound wave vibrator and the negative pressure suction device are synchronously controlled, and a coordinated and consistent multi-mode treatment execution instruction is obtained; and collecting real-time feedback data in treatment, and dynamically adjusting working parameters through reinforcement learning to obtain an optimized expectoration adjuvant therapy scheme. Intelligent adjustment can be achieved based on the real-time breathing state and sputum characteristics of the patient, the expectoration efficiency is improved, and discomfort of the patient is reduced.

The invention belongs to the technical field of sleep respiratory disease detection, and relates to a sleep apnea identification method based on a hybrid neural network, which comprises the following steps of: sensing human sleep in a bed surrounding environment by using a millimeter wave radar, and positioning a thoracic cavity position by adopting spatial two-dimensional analysis; the problem that interference exists in radar sign signal extraction of different targets at the same distance is solved. And a respiration signal Shannon entropy is constructed as an iterative index of the whale optimization algorithm, and the index is minimized to realize iterative optimization of variational mode extraction parameters, so that different respiration states are matched with different parameters, and thus a dominant frequency narrowband respiration signal is accurately extracted. A breathing time-frequency energy diagram obtained by data processing is used as input, and a CNN network and a bidirectional long-short-term memory module are used together to construct a feature extraction module, so that the method can recognize the change trend of frequency along with time, capture more comprehensive features, and recognize target sleep apnea more accurately. In addition, the hybrid network enables accurate classification of unmanned scenarios, apnea, hypopnea, and normal respiration.

The invention belongs to the technical field of ablation puncture navigation, and particularly relates to an ablation puncture surgery navigation system under AI visual guidance. Through cooperative work of the phase monitoring module, the channel construction module, the needle moving control module, the displacement prediction module and the feedback control module, an intelligent surgical navigation system is constructed, breathing phase information and multi-modal medical image data of a patient can be obtained in real time, and therefore a safe and optimized needle moving path is accurately planned, and the operation accuracy is improved. Meanwhile, through real-time monitoring and quantitative evaluation of parameters such as tissue deformation and pressure distribution in the needle moving process, potential operation risks can be found and corrected in time, smooth operation is ensured, in addition, the system can dynamically adjust the needle moving path and the puncture angle according to the real-time breathing state of a patient, and the operation safety is improved. The accuracy and the safety of the operation are further improved, so that intelligent management and personalized treatment in the ablation puncture operation process are realized.

Disclosed herein is a medical system (100, 400) comprising: a magnetic resonance imaging system (102) configured for providing a respiratory signal. The respiratory signal is descriptive of a respiratory position as well as of inhalation and exhalation of the subject. The execution of machine executable instructions (140) causes the computational system to repeatedly: perform (200) the individual acquisition of k-space data using the magnetic resonance imaging system; receive (202) the respiratory signal; bin (204) the individually acquired k-space data into one of a predetermined number of k-space bins (148) using the respiratory signal and perform outlier rejection. Execution of the machine executable instructions further causes the computational system to reconstruct (208) a magnetic resonance image for each of the predetermined number of k-space bins to provide a respiratory-state resolved magnetic resonance image (150).

The invention discloses a radiotherapy beam output control method, system, device and equipment and a medium, and relates to the technical field of radiotherapy control, and the method comprises the steps: obtaining the spatial position information of a patient body surface marking module in real time; wherein the marking module comprises a fluorescent marking ball, and the fluorescent marking ball is fixed in a breathing movement remarkable area of a patient; performing information conversion processing on the spatial position information according to a time axis direction to obtain target breathing state change information of the patient, and importing the target breathing state change information into a corresponding preset breathing standard normal form to check whether the target breathing state change information meets a radiotherapy treatment condition; and if the target breathing state change information meets the radiotherapy treatment condition, recommending a corresponding breathing gating window threshold value, and dynamically controlling the output of the radiotherapy beam according to the breathing gating window threshold value. The automatic monitoring of the breathing state change is realized, and the output of the radiotherapy beam is accurately controlled according to the monitoring result.

The invention relates to the technical field of respiratory training, in particular to a gamification guide system for respiratory rehabilitation training, which comprises a data acquisition module, a data analysis module, a training adaptation module, a training guide module and a training adjustment module, the breathing state parameter and the thoracic cavity fluctuation reference value are determined, the data analysis module calculates the breathing abnormity characterization value by determining the breathing difference value and the facial feature fluctuation value, divides the breathing rehabilitation training abnormity tendency and calls the corresponding module, and the training adaptation module adjusts the number of breathing force bearing points. The training guide module determines a stress reference value, a training operation characterization value is calculated by combining the stress reference value with the thoracic cavity fluctuation reference value, and the training adjustment module adjusts the number of times of training based on the training operation characterization value. According to the breathing rehabilitation training method and device, the breathing pre-training is carried out, the appropriate training parameters are determined in a targeted mode, the training content is determined according to the real-time training condition, and the breathing rehabilitation training efficiency is improved.

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 discloses a thoracoscope-assisted intelligent navigation system and method for thoracic surgery, and the method comprises the steps: recording the respiratory capacity of a patient and shooting a focus image in a breathing state, precisely calculating the position change amplitude and range of a focus in a breathing process, and drawing a dynamic graph for visual presentation; selecting an electromagnetic navigation system positioning method and performing preoperative planning according to lesion characteristics and positions, and adopting a transbronchial or transthoracic navigation positioning technology; wherein different anatomical regions of a human body are divided according to the focus position and the anatomical structure, a navigation path algorithm is planned for each anatomical region, parameters of the electromagnetic navigation system are adjusted according to the characteristics of tissues passed by the navigation path, and final positioning is confirmed; the television is combined with the thoracoscope to assist the thoracoscope, so that the focus is accurately marked and cut off; according to the method, the safety and success rate of the operation are improved, operation wounds are reduced, better treatment effect and experience are brought to patients, and the method conforms to the development trend of precision and intelligence of the medical technology.

The invention relates to a method for identifying a hypoventilation type, computer equipment and a storage medium. The method comprises the following steps: acquiring breathing state data of a target user; determining breathing characteristic information according to the breathing state data; the breathing characteristic information comprises a breathing peak change rate, a breathing pressure change rate and a breathing flow ratio; and according to the breathing peak change rate, the breathing pressure change rate and the breathing flow ratio, the hypoventilation type of the target user is determined. By means of the collected breathing state data, whether a hypoventilation event occurs or not can be judged, the specific hypoventilation type can be determined in combination with the characteristics of the hypoventilation type, only the breathing-related data is collected, the obtained data is not affected by motion artifacts and changes of the elastic inertia of the pipeline, and the accuracy of hypoventilation is improved. The accuracy of the data for determining the hypoventilation type is improved, so that the accuracy of identifying the hypoventilation type is improved.

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 present invention provides a sleep breathing monitoring method and a non-contact sleep breathing monitoring device, including: collecting air pressure vibrations caused by the vibrations of the sleeper's body based on an air pressure sensor to obtain air pressure vibration data; extracting breathing-related features from the air pressure vibration data; performing cluster analysis on the breathing-related features to obtain corresponding cluster clusters; performing pattern recognition on the cluster clusters to determine the breathing pattern category; generating a breathing pattern model according to the breathing pattern category, and monitoring the breathing state of the sleeper based on the breathing pattern model to monitor whether the sleeper's breathing is normal. In the present invention, the air pressure vibrations caused by the vibrations of the sleeper's body are collected based on the air pressure sensor, without contacting the sleeper and without causing interference to the sleeper; the air pressure vibration data is analyzed, thereby realizing contactless sleep breathing monitoring of the user.

The invention discloses a cone beam CT full respiratory cycle image reconstruction method based on a four-dimensional neural network. The method comprises the following steps: step 1, acquiring cone beam projection data and a respiratory signal in a respiratory state; 2, a respiratory cycle is divided into N phases, multi-phase cone beam projection data Qi are obtained, i = 1, 2,..., N, the Qi is reconstructed through a filtered back projection algorithm, and a multi-phase under-sampling CT reconstructed image # imgabs0 # is obtained; 3, # imgabs1 # is input into a four-dimensional neural network, and a three-dimensional deformation field Di is obtained; 4, performing weighted summation after deformation on the # imgabs2 # by using the Di to obtain a reference phase reconstruction image Xref after motion correction; and step 5, performing inversion on the Di to obtain a three-dimensional reverse deformation field # imgabs3 #, for any breathing phase, performing image deformation on the reference phase reconstruction image Xref by using the corresponding # imgabs4 #, and performing reconstruction to obtain a motion correction image Xi. According to the method, the breathing movement correction can be quickly carried out on the cone beam CT image.

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 embodiment of the present invention provides a flow regulation method for ventilation therapy equipment and ventilation therapy equipment, including: detecting the current breathing parameters of the user, and determining the current breathing state of the user according to the breathing parameters; then outputting with a corresponding flow output value according to the current breathing state of the user; after controlling the output valve according to the flow output value, obtaining the breathing parameters of the user again, and adjusting the flow value of the output valve according to the change of the breathing parameters; by monitoring the breathing state of the user, adjusting the output airflow flow value of the equipment in real time, specifying different ventilator output working plans according to the breathing needs of different users, so as to solve the problem in the prior art that the adjustment result of the preset algorithm of the equipment is too uniform and the support for the different needs of different users is poor.

The invention relates to the technical field of atomization drug delivery, in particular to an anti-infection drug precise atomization drug delivery system based on respiratory physiological characteristics, comprising a respiratory parameter acquisition module used for acquiring respiratory data of a patient in real time; the breathing mode recognition module is used for classifying breathing modes of the patient and generating breathing mode labels; the dose-parameter cooperative calculation module is used for adjusting the atomization dose and the initial atomization parameter required by the patient at a time; the atomization parameter optimization module is used for monitoring the actual output effect of an atomizer in real time and adjusting dynamic atomization parameters in real time through a PID controller; and the breathing auxiliary intervention module is used for guiding the patient to perform deep and slow breathing through acousto-optic feedback. By collecting the breathing data of the patient in real time and dynamically adjusting the atomization dosage and parameters in combination with breathing mode classification, the limitation of traditional fixed dosage and parameters is broken through, administration is accurately matched with the real-time breathing state of the patient, and the deposition rate and utilization rate of the medicine at the target part are increased.

The invention provides a snore stopping method and device, and the method comprises the steps: obtaining an original vibration signal of the neck of a user, and carrying out the preprocessing of the original vibration signal, and obtaining a target vibration signal; analyzing the breathing state of the user according to the target vibration signal to obtain a breathing state analysis result; judging whether intervention conditions are met or not according to the respiration state analysis result; when the intervention condition is met, the breathing state of the user is intervened according to the breathing state analysis result and a preset self-adaptive intervention rule. The breathing behavior related to the snoring behavior is detected based on the vibration signal, flexible intervention on the breathing state of the user is achieved in combination with the detection result and the self-adaptive intervention rule, sound collection is not needed, interference of snore of other users can be avoided, user privacy is not involved, meanwhile, smooth intervention experience can be provided for the user, and the user experience is improved. Therefore, the method can be widely applied to the technical field of smart home.

The invention relates to a working parameter adjusting method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring gas pressure and gas flow rate output by a breathing machine and collected by a breathing machine sensor; determining breathing information of the target user according to the gas pressure and the gas flow rate; the breathing information comprises at least one of breathing frequency, real-time tidal volume and breathing quality data; determining physiological state information of the target user according to the breathing information and a physiological state threshold value; and adjusting working parameters of the breathing machine based on the physiological state information. By analyzing the gas pressure and flow velocity data collected by the respirator sensor in real time, the breathing frequency, tidal volume and other key parameters of a user can be accurately determined, the breathing state of a patient is intelligently evaluated, the working parameters of the respirator are automatically adjusted according to the evaluation result, and the flexibility of the working parameters is improved.

The invention relates to a system for synchronized respiratory muscular electrical stimulation of a patient. The system comprises: a transcutaneous electrostimulation of the respiratory muscles (TERM) system comprising one or more skin electrodes configured to be placed over the respiratory muscles of the patient; at least one sensor for sensing the breathing state of the patient; and a processor configured to receive the breathing state of the patient from the at least one sensor and actuate the TERM system when the breathing state is in the inspiration phase and / or the expiration phase. The TERM system comprises at least one calibratable element, and the processor (30) is further configured to actuate the TERM system (10) in a predetermined way according to a previous calibration. The invention also relates to a method and computer program product thereof.

The invention relates to a CT-guided thoracic and abdominal puncture guiding method for reducing the influence of respiratory movement. The method comprises the following steps that S1, a respiratory movement curve of a target object in a free breathing state is obtained; s2, in the free breathing state of the target object, according to the breathing motion curve, controlling CT imaging equipment to scan the target tissue through breathing gating in the curve area of the target object, and obtaining a CT scanning image of the target object; s3, the CT image in the S2 is matched with the respiratory movement curve in the S1, and the marked curve serves as a reference curve of the puncture moment; s4, determining a body surface needle insertion position of the puncture target tissue according to the CT image obtained in S2; and S5, monitoring the respiratory movement of the target object during puncture, obtaining a respiratory movement curve, and when the respiratory movement curve is located at the target tissue image identification point in the reference movement curve in the S3, determining the puncture moment for the target tissue. According to the invention, the puncture accuracy can be improved.

The invention relates to the technical field of oxygen production equipment, and discloses an oxygen output control method and device, oxygen production equipment and a storage medium. An electromagnetic wave emission device is controlled to emit electromagnetic waves, echo signals of the electromagnetic waves reflected by the human body of a user are received, and the current breathing frequency of the user is determined based on the echo signals; the target valve opening degree is determined based on the preset corresponding relation between different breathing frequencies and different valve opening degrees and the current breathing frequency of the user, and finally the oxygen equipment is controlled to output oxygen based on the target valve opening degree, so that the valve opening degree is automatically adjusted to change the oxygen flow according to the breathing speed in the human body breathing speed changing state. And oxygen supply of the user in different breathing states is ensured.

The invention relates to the technical field of medical equipment, in particular to a spray dosing device and system for lung diseases, comprising a shell in which a medicine storage bin for storing liquid medicine and an atomizing component for atomizing and spraying the liquid medicine are mounted, the atomization assembly is communicated with the medicine storage bin, the respiration triggering assembly is installed at the end, away from the medicine storage bin, of the atomization assembly, the airflow adjusting assembly is installed in the atomization assembly, and the atomization assembly is communicated with the medicine storage bin. The airflow adjusting assembly is in signal connection with a controller, and the controller is in signal connection with the atomization assembly and the respiration triggering assembly. The system is used for achieving accurate and intelligent spray administration according to the breathing state of a patient, the deposition efficiency of medicine in the lung is improved, the treatment effect is optimized, and formulation of a personalized treatment scheme is achieved.

The invention discloses a transformer breathing state digital online monitoring system. Comprising a respirator online monitoring module used for collecting respirator working condition parameters, an oil conservator online monitoring module used for collecting oil conservator working condition parameters, a data collection and communication module used for receiving and transmitting the respirator and oil conservator working condition parameters, and a local processing and display module used for data processing and monitoring result displaying. And the remote management platform is used for remotely checking a monitoring result and adjusting parameters in the local processing and display module. According to the invention, comprehensive, real-time and quantitative monitoring can be carried out on the breathing state of the transformer and the internal state of the oil conservator, so that operation and maintenance personnel can intuitively and accurately master the operation state of equipment, regular maintenance is converted into predictive maintenance, the reliability, stability and economical efficiency of the operation of the transformer are remarkably improved, and the service life of the equipment is prolonged.

The utility model discloses an atomizer for providing medicine mist based on respiration detection, and belongs to the field of medical atomizers. The atomizer comprises an atomization working assembly, a breathing mask, a breathing sensor, a control module and a switching valve, the breathing sensor comprises a detection tube, the detection tube is provided with two tube openings at different positions, one tube opening is connected with the breathing mask, the other tube opening is communicated with the atmosphere, and the two tube openings are respectively provided with an airflow detection element. The airflow direction in the detection tube is determined according to the sequence of airflow detected by the two airflow detection elements, whether a patient exhales or inhales is accurately detected, the detection of the breathing state is rapid and accurate, the influence of the humidity and temperature of breathing air is small, and the working stability is good; meanwhile, the control module is used for controlling whether the mist outlet of the atomization working assembly generates medicine mist or not according to the expiration or inspiration state, medicine mist generated by inspiration of the patient and medicine mist generated by stopping expiration of the patient are accurately achieved, medicine waste is reduced, and the atomization treatment effect is guaranteed.

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 relates to a human-computer interaction method and device of a medical system, the medical system and a storage medium, and is applied to the technical field of medical system control. The method comprises the following steps: displaying a preset identifier in an information display interface; acquiring a current breathing parameter; and controlling the preset identifier to move in the information display interface based on the breathing parameters. The preset identifier is displayed in the information display interface, and then the preset identifier is controlled to move in the information display interface according to the obtained current breathing parameter, so that the current breathing state of the patient is displayed in a visual manner, personalized visual interaction with the patient is performed, the experience of the patient in medical equipment is improved, and the medical equipment experience is improved. The psychological pressure of the patient in the medical treatment process is relieved, so that the medical treatment effect is improved.

The invention relates to the technical field of respiratory health monitoring, and discloses a remote respiratory health monitoring and management system and method. The method comprises the steps that an original respiration data set containing time sequence and frequency domain characteristics is collected through a multi-mode sensor, respiration cycle segments are divided through dynamic segmentation processing, key waveform mark points are extracted, and a respiration state transition network is constructed to form a dynamic topological structure. And generating a breathing environment coupling matrix in combination with environmental parameters, screening interfered abnormal breathing segments, training an analysis model to output a deviation score, triggering multi-level early warning and generating a report containing a backtracking path. User activity log timestamps are matched through cross-device verification, data are integrated to construct a breathing behavior association map, a model judgment threshold value is updated based on the map, and monitoring closed-loop feedback is completed. According to the method, accurate monitoring and dynamic management of respiratory health are achieved, and a complete solution is provided for remote respiratory health management and control.

The invention relates to the technical field of health management systems, in particular to a respiration monitor and a nursing monitoring device.The respiration monitor comprises a sound pickup tube bound to the throat of a patient and used for collecting respiration sound of the patient; the converter is used for sensing the breathing sound, converting the breathing sound into an electric signal and analyzing and processing the electric signal to obtain a real-time monitoring waveform; one end of the monitoring interface module is connected with the converter through a cable, the other end is connected with the monitor, and the monitoring interface module is used for transmitting real-time monitoring waveforms to the monitor; and the monitor is used for displaying the monitoring waveform so as to display the breathing frequency and the breathing mode of the patient, collecting the breathing sound through the throat and processing the breathing sound, so that the breathing state of the patient is effectively monitored, and the nursing efficiency of medical staff on the patient is improved.

According to the mode switching method, the controller, the airway clearance equipment, the storage medium and the program product provided by the embodiment of the invention, the oscillation airflow under different oscillation frequencies is output after operation is performed for the preset duration in the airway oscillation mode or the mechanical inhalation and exhalation mode, and the oscillation airflow under different oscillation frequencies is output for any oscillation frequency. The method comprises the following steps: acquiring response information of a user to oscillation airflow at oscillation frequencies, determining an impedance parameter of the user according to the response information at each oscillation frequency, determining an operation mode at the next moment according to the impedance parameter, and executing the operation mode, according to the method, the response information of the user under the oscillation airflow is obtained to determine the impedance parameter representing the blocking condition of the respiratory system of the user, so that the adopted airway clearance mode is automatically adjusted according to the real-time breathing state of the user, and the sputum discharge effect is improved.

The invention relates to the technical field of lung function detection, and particularly discloses a lung ventilation function detection system based on algorithm analysis, which adopts a data processing technology based on deep learning to carry out data analysis on breathing parameters of a patient, extracts semantic embedding feature representation of each breathing parameter data item, and obtains a semantic embedding feature representation of each breathing parameter data item; and on the basis of the semantic association topological relation among the breathing parameter data items, global depth association coding is performed on the semantic embedding features of the breathing parameter data items, so that global depth perception of the breathing state of the patient is realized, and whether the patient suffers from bronchial asthma or not is intelligently identified. In this way, the limitation of a traditional data analysis method can be effectively overcome, the dependence on professional knowledge of doctors is reduced, the accuracy and efficiency of pulmonary ventilation function detection are improved, and the risks of misdiagnosis and missed diagnosis are reduced.