38 results about "Respiratory effort" patented technology

The invention relates to the technical field of sleep medical diagnosis, and discloses a method for diagnosing obstructive sleep apnea of a patient. The method comprises the steps that nasal pressure airflow, thoracico-abdominal breathing effort and blood oxygen saturation waveform of all-night sleep are obtained, and standardized signal flow is generated through quality evaluation and compensation. And executing sleep stage perception respiratory event analysis, and outputting an event sequence with a time sequence and a type label. And inputting the sequence into an apnea association network for event chain mining and mode extraction, and generating an event association graph and a key pathological feature vector. And performing severity grading of sleep structure dependence, outputting severity indexes of sleep stages, and finally deducing a personalized treatment path. According to the method, the accuracy of event interpretation is improved by sensing the sleep stages, the dynamic mode between the events is mined by using the association network, and more refined diagnosis is realized.

The invention discloses a child mouth breathing monitoring method, device and equipment and a medium, and the method comprises the steps that a non-contact sensor group is used for synchronously collecting multi-mode physiological data of a target child in the sleep period, and the multi-mode physiological data at least comprises a face thermal imaging video stream, a thoracic and abdominal micro-motion signal and an environment audio signal; the multi-modal physiological data is processed, multi-modal features related to respiration are extracted respectively, and the multi-modal features comprise thermodynamic change features of mouth and nose areas extracted based on a face thermal imaging video stream, respiratory effort waveforms extracted based on thoracic and abdominal micro-motion signals, and the respiratory effort waveforms extracted based on the thoracic and abdominal micro-motion signals; extracting a sound source spatial position and a spectrum feature of breathing sound based on the environment audio signal; inputting the multi-modal features into a pre-trained mouth breathing recognition model, and outputting a judgment result of the functional mouth breathing event of the target child within a specific time period; and generating a mouth breathing monitoring report of the target child based on the judgment result.

The invention relates to the technical field of respiration monitoring, and provides a sensor-based respiration monitoring system which comprises a non-contact radar sensor, a signal preprocessing unit, an active state monitoring module, a dynamic threshold adjusting unit, a respiration signal reconstruction module, a respiration event judging module and a data fusion calibration unit. The sensor collects original respiratory vibration data of the thoracic cavity, and initial baseband signals are extracted through preprocessing; the monitoring module evaluates an activity state and adjusts unit self-adaptive configuration parameters; the reconstruction module generates a high-fidelity respiratory effort signal through filtering and phase compensation; the judgment module extracts features, recognizes and classifies respiratory events, and the calibration unit fuses multi-source data to verify a correction result. The system can be deployed on multiple devices, interference-free long-term monitoring is achieved, respiratory events can be accurately recognized, types can be subdivided, and the monitoring precision and adaptability are greatly improved.

The present application relates to the technical field of medical monitoring, and discloses a portable blood oxygen signal OSA intelligent detection system, which comprises the following steps: collecting a pulse wave signal through a blood oxygen sensor, generating an amplitude difference sequence and a period difference sequence in parallel, analyzing the rhythm synchronism of the two, and determining a respiratory effort event when a real-time relationship index deviates from a reference value. The present application captures the pulse wave timing-amplitude decoupling phenomenon, realizes direct sensing of the specific mode process of the invalid respiratory effort signal, avoids the traditional lag monitoring mode which relies on blood oxygen decline, has the inherent ability to distinguish physiological fluctuations from the specific mode struggle of the signal, and provides a new solution for early screening of mild and moderate OSA.

The invention relates to the technical field of signal processing, in particular to a vital sign risk assessment method for ballistocardiogram signals, which comprises the following steps of: calculating heart rate index data, sleep quality index data and sleep apnea index data based on the ballistocardiogram signals and respiratory effort signals acquired in a user monitoring process; the vital sign risk assessment method and device are used for performing vital sign risk assessment and improving the accuracy and efficiency of vital sign risk assessment.

The invention relates to the technical field of medical identification, in particular to a sleep apnea real-time monitoring and early warning system, which comprises an acquisition module used for acquiring PSG data of a target user from a sleep moment to a current moment; the determination module is used for determining all OSA events from the sleep moment to the current moment according to a spectrogram of respiratory effort waves and a spectrogram of airflow of a window corresponding to each moment in the PSG data; the determining module is further used for determining the blood oxygen consumption time period of the current OSA event; the determination module is also used for determining a trusted OSA event; and the early warning module is used for constructing an early warning model of the target user by using the PSG data of the credible OSA event, and performing sleep apnea early warning on the target user by using the real-time PSG data of the target user acquired in real time and the early warning model. According to the invention, the accuracy of OSA diagnosis is improved.

Ventilator (1) with at least a sensor for detecting at least one parameter of a breathing gas, a control device for specifying settings, a storage unit a control unit connected to the storage unit, a first computer program product for implementing the settings taking into account a specification and a second computer program product that regulates data transfer to and from the control unit via at least one interface (8); wherein the ventilator (1) is designed such that at least one interface allows for the mutual exchange of data between the ventilator (1) and external storage media and / or devices (12), the exchange of parameters, and the loading of parameters and / or a configuration of the ventilator from external storage media and / or devices, wherein the ventilator has at least two interfaces that support different standards and communication protocols, wherein one of the interfaces is designed as a radio interface and another of the interfaces is designed as a memory card interface, wherein the memory card interface is suitable for a Secure Digital card, a Multimedia card, a Memory Stick PRO card, an xD-Picture card, a SmartMedia card or a CompactFlash card, where data from the ventilator can be saved to an inserted memory card via the memory card interface, and data from an inserted memory card can be loaded into the ventilator, where, in the area of ​​the ventilator, a firmware or software is installed as the second computer program product, which runs as a client and enables a connection of the ventilator to the Internet, where the client is responsible for initiating contact during data transmission and is configured to determine the timing of the transmission, where reading or saving ventilation and usage information to the respective storage medium must be initiated by an event, and the event is the expiration of a specific period of time since the start or end of ventilation therapy, where, when reading usage data from the ventilator, an assignment to the correct patients is automatically performed via a stored database. wherein the ventilator contains relevant information about its setting parameters and their setting limits as well as its stored therapy information and is designed to make the relevant information available to a PC, wherein the ventilator is configured to provide, via the respective interface or storage medium, an application directly executable by a PC operating system, wherein the ventilator contains executable logic in non-volatile memory, wherein the executable logic is not executable by the ventilator itself but by the PC, thus enabling the installation of software on the PC without requiring a user to obtain the software directly from the ventilator manufacturer or a service provider via CD, download, or storage medium. wherein the ventilator further comprises a data cable as a data exchange means inserted into the respective interface, wherein the data cable is connected to an interface converter outside the ventilator, wherein the interface converter is designed to enable communication between the ventilator and another device via at least one transmission standard not provided in the ventilator itself, wherein at least one additional sensor in the form of a pulse oximeter and / or a sensor for CO2 measurement and / or a sensor for measuring respiratory effort and / or an ECG device and / or an EEG device is additionally connected to the ventilator via the interface converter.

The present application belongs to the technical field of medical general equipment, and relates to a ventilator phase switching method and device based on respiratory effort recognition, a ventilation equipment and a storage medium. The method comprises the following steps: monitoring a patient's proximal ventilation flow and airway pressure; according to a set logical enabling condition, avoiding an undesirable recognition period; the undesirable recognition period is an initial unstable stage after the ventilator inflation or breathing starts; outside the undesirable recognition period, based on the waveform trajectory change characteristics of the ventilation flow and the airway pressure, the time when the patient's inspiratory effort ends, the expiratory effort starts or the inspiratory effort starts is recognized; and according to the recognition result, the ventilator is controlled to switch between the inflation phase and the exhalation phase. The present application can improve the sensitivity and accuracy of respiratory effort recognition, improve the time synchronization of ventilation triggering and switching, reduce the phenomenon of man-machine asynchronization, and improve the comfort and effectiveness of mechanical ventilation support.

The invention relates to a breathing physical therapy device, belongs to the technical field of medical rehabilitation equipment, and solves the problem that existing breathing training equipment cannot intelligently adjust resistance according to the real-time breathing effort degree of a user. The device comprises a mouth-nose mask, an airflow resistance adjusting valve, a diaphragm myoelectricity sensor and a pressure difference sensor, a control module monitors the pressure difference rising rate and the current myoelectricity integral value in real time in the treatment stage based on a myoelectricity integral reference value calculated in the calibration stage, and accordingly resistance adjusting instructions including resistance increasing, resistance reducing and emergency resistance reducing instructions are generated; and an instruction priority and execution logic are set, so that timely intervention is ensured when the breathing of the user is abnormal. The device is mainly used for respiratory muscle strength training and rehabilitation treatment of patients with chronic respiratory diseases, and the training safety and the individuation level can be effectively improved.

An apparatus is disclosed. The invention relates to monitoring lung condition. The solution comprises non-invasive optical measurements (300) on a patient utilising at least two wavelengths; determining (302), based on the optical measurements, oxygen saturation, heart rate and heart rate variations of the patient; determining (304), based on heart rate and / or heart rate variations, breathing effort of the measurement subject; detecting (306) a change in breathing effort; detecting (308) a change in oxygen saturation level; determining (310), based the detected changes, a probability index for lung problem; comparing (312) the probability index to a given threshold and generating (314) an indication if the probability index is over a given threshold.

A method for monitoring lung function in a subject with respiratory dysfunction includes the steps of receiving a plurality of initial measurement data from a spirometry system indicative of a first plurality of respiratory efforts from the subject, calculating a first target value utilizing best-of-day data from the plurality of initial measurement data, receiving a plurality of subsequent measurement data from the spirometry system indicative of a second plurality of respiratory efforts from the subject, calculating a second target value utilizing best-of-day data from the plurality of subsequent measurement data, receiving a plurality of measurement data from the spirometry system indicative of a third plurality of respiratory efforts from the subject, and generating an alert if best-of-day data from the plurality of measurement data drops below a threshold set based on the second target value.

The invention relates to the technical field of medical equipment, in particular to a sleep breathing event monitoring method and device, a terminal and a storage medium. The method comprises the following steps: acquiring a first blood oxygen saturation signal when a user actively suffocuses, and calculating an average blood oxygen decline slope according to the first blood oxygen saturation signal; in the sleep monitoring process, physiological signals of the user are continuously collected, and the physiological signals at least comprise a second blood oxygen saturation degree signal and a respiratory effort related signal; the second blood oxygen saturation degree signal is monitored in real time, and when a blood oxygen decline event is detected, the blood oxygen decline slope of the blood oxygen decline event is calculated; the blood oxygen decline rate is compared with the average blood oxygen decline rate, and in combination with the respiratory effort related signal, whether a sleep breathing event occurs is determined. The problems that in the prior art, monitoring equipment is complex, cost is high, comfort and compliance are reduced, and monitoring accuracy is low can be solved.

And treating cardiac decompensation, pulmonary hyperemia and dyspnea. A method for treating a cardiac problem, the method comprising performing modulation of the heart rhythm of a patient by increasing the number of times during time intervals with high pleural pressure relative to the number of times the patient's heartbeat during low (negative) pleural pressure, the magnitude of the regulation of the heart rhythm between these segments is determined by the patient's respiratory effort and the severity of pulmonary congestion.

The present disclosure relates to a method (MO) for providing respiratory timing parameters from respiratory monitoring measurements of a subject, the method comprising the steps of: providing (M1) a respiratory effort signal (E) and a respiratory flow signal (F) of a subject; determining (M2a) an ensemble of peaks (pE) in the respiratory effort signal (E) and determining (M2b) an ensemble of valleys (vE) in the respiratory effort signal (E); and identifying (M3) times associated with the valleys (vE) as preliminary inspiratory onset times (t′io); refining (M4) preliminary inspiratory onset times (t′io) within respective peak-to-peak time intervals (Tpp) of the respiratory effort signal (E) by: determining (M41) first derivative (F1d) of the respiratory flow signal (F) in a respective peak-to-peak interval (Tpp); determining (M42) local peaks (pF1d) and valleys (vF1d) in the respiratory flow signal first derivative (F1d); determining (M43) a time midpoint (tmid) between the time of a local valley (vF1d) in the respiratory flow signal first derivative (F1d) closest in time to the later endpoint in the respective peak-to-peak time interval (Tpp) and the time of a local peak (pF1d) in the respiratory flow signal derivative (F1d) in the respective peak-to-peak time interval (Tpp); evaluating (M44) whether the respiratory effort signal (E) at the determined time midpoint (tmid) satisfies a predetermined inspiratory onset time condition, and if satisfied, selecting (M45) the determined time midpoint (tmid) as an inspiratory onset time (tio) instead of the preliminary inspiratory onset time (t′io) for that peak-to-peak interval (Tpp), whereas if the condition is not satisfied, keep the preliminary inspiratory onset time as the inspiratory onset time for that peak-to-peak interval.

The invention relates to the technical field of medical instruments, and discloses a lung rehabilitation breathing exercise device which comprises a breathing exercise module, a monitoring module, an adjusting module, a central processing and control module and an abnormity monitoring and processing module. The monitoring module collects a multi-modal physiological signal of a patient in real time. The central processing and control module processes the signals, calculates a respiratory effort index reflecting the real-time respiratory state of a patient, and dynamically controls the adjusting module to change the resistance of a respiratory channel by comparing the index with the deviation of the target training intensity, so that the personalized self-adaptive adjustment of the training intensity is realized. Meanwhile, the abnormity monitoring and processing module calculates the risk coefficient of the equipment by analyzing the state data of the equipment, thereby achieving the real-time monitoring and grading early warning of the equipment. The problems that an existing breathing exerciser cannot dynamically adjust training parameters according to the real-time physiological state of a patient and lacks intelligent abnormity monitoring are solved, and the safety and accuracy of lung rehabilitation training and the equipment reliability are improved.

The utility model discloses an airway opening pressure measuring device which comprises a breathing machine communicating pipe, a three-way pipe, a pressure measuring end pipe and an artificial airway fixator, the breathing machine communicating pipe is communicated with the pressure measuring end pipe through the three-way pipe, and the third opening end, different from the breathing machine communicating pipe and the pressure measuring end pipe, of the three-way pipe is a pressure zero calibration opening. The artificial airway fixator is clamped with an artificial airway outer opening and the pressure measuring end tube, and one end, deviating from the three-way tube, of the pressure measuring end tube extends into the artificial airway of the patient for pressure measurement; tracheotomy model number scales and trachea cannula model number scales are arranged on the pressure measuring end tube, the tracheotomy model number scales correspond to the tip opening in the lower trachea of the model number, and the trachea cannula model number scales correspond to the tip opening in the cannula of the model number. According to the utility model, the respiratory effort is measured by utilizing the synchronism and correlation of the fluctuation of the tip pressure in the artificial airway and the fluctuation of the pressure in the esophagus, the design and the operation are simple, the product consumable cost is low, the maintenance and the cleaning are simple, the labor cost is low, and the popularization is convenient.

The invention discloses a ventilation system of an anesthesia respirator and the anesthesia respirator, and relates to the technical field of anesthesia respirators, the ventilation system comprises a millisecond-level time sequence observation module, a coherent phase decomposition module, an anti-fact playback repair module, a double-mirror-image time scale calibration module, a dynamic coupling control law module and a closed-loop synchronous correction module; and the millisecond-level time sequence observation module is used for constructing a millisecond-level time sequence observation layer based on the dynamic difference between the breathing effort signal of the patient and the triggering signal of the breathing machine, and generating a triggering waveform baseline by using a high-precision flow channel and pressure channel sensing array. A stable breathing curve is generated through millisecond-level time sequence observation and anti-fact playback, small airway collapse is avoided, and gas exchange is guaranteed; meanwhile, closed-loop synchronization is achieved through double-mirror-image time scales, a self-adaptive window and inverse phase correction, abnormal negative pressure troughs are eliminated, and man-machine synchronism and ventilation safety are improved.

A method for treatment of cardiac problems includes performing modulation of a cardiac rhythm of a patient by increasing a number of heart beats the patient during time interval with high pleural pressure relative to the number during low (negative) pleural pressure, wherein an amplitude of the modulation of the cardiac rhythm between these segments is determined by severity of a respiratory effort and lung congestion of the patient.

The invention belongs to the technical field of breathing machines, and relates to a respiratory effort evaluation system based on a respiratory flow autopower spectrum. The system comprises a signal acquisition module used for acquiring a continuous breathing flow signal acquired by a flow sensor of the breathing machine in real time; the self-power spectrum calculation module is used for carrying out preprocessing and time-frequency conversion on the respiratory flow signals and calculating to obtain a self-power spectrum; the extraction module is used for extracting energy of a preset high-frequency band as a high-frequency energy component in the autopower spectrum, and the high-frequency band is higher than a main frequency band corresponding to the basic respiratory frequency of the human body; the statistical analysis module is used for establishing a baseline value for evaluation based on statistical data of high-frequency energy components in the historical respiratory flow data; the evaluation output module is used for comparing the high-frequency energy component at the current moment with the baseline value, when the high-frequency energy component is smaller than the baseline value, the respiratory effort state is evaluated to be abnormal, and otherwise, the respiratory effort state is normal.

A system and method for determining respiratory effort of a subject is provided. The method includes obtaining a relaxation signal representing the subject breathing in a relaxed manner and a forced signal representing the subject breathing in a forced manner. A plurality of forced peaks is derived from the forced signal, and a candidate peak is selected from the plurality of forced peaks. The candidate peak is selected based on a characteristic of the forced peaks. A user selects a user-identified peak from the candidate peaks, and, as a result, respiratory effort is determined based on the relaxation signal and the user-identified peak.

Provided are systems, methods and computer-readable media for breathing signal analysis and event detection and systems, methods and computer-readable media for generating respiratory flow and / or effort signals from accelerometer signals using trained models. Breathing signal analysis may characterize at least one recorded signal as indicative of one of Obstructive Sleep Apnea (OSA) and Central Sleep Apnea (CSA). This analysis includes determining a frequency domain representation of an audio signal; sorting at least one frequency interval component into at least one corresponding frequency bin; determining a signal-to-noise ratio (SNR) signal for each frequency bin during a candidate time period; and determining an indication of an OSA event or a CSA event.

This application discloses a method and apparatus for detecting sleep apnea. The method includes: acquiring a thermal imaging video of a target subject during sleep; determining a first respiratory airflow signal and a first respiratory motion signal of the target subject in the video; segmenting the first respiratory airflow signal and the first respiratory motion signal using a preset sliding window to obtain second respiratory airflow signals and second respiratory motion signals under multiple time windows; within each time window, determining multiple respiratory airflow features, respiratory effort intensity features, and respiratory effort difference features based on the second respiratory airflow signal and the second respiratory motion signal, and combining these features as a feature vector corresponding to the time window; clustering the multiple feature vectors corresponding to the multiple time windows to obtain a classification result corresponding to each time window. This application solves the technical problem in related technologies of the difficulty in accurately detecting different types of sleep apnea.

The present application relates to the technical field of medical identification, in particular to a sleep apnea real-time monitoring and early warning system, which comprises: an acquisition module, configured to acquire PSG data of a target user from a sleep time to a current time; a determination module, configured to determine all OSA events from the sleep time to the current time according to a spectrum of a respiratory effort wave and a spectrum of airflow of a window corresponding to each time in the PSG data; the determination module is further configured to determine a blood oxygen consumption period of a current OSA event; the determination module is further configured to determine a credible OSA event; and an early warning module, configured to construct an early warning model of the target user by using PSG data of the credible OSA event, and to perform sleep apnea early warning on the target user by using real-time PSG data of the target user collected in real time and the early warning model. The present application improves the accuracy of OSA diagnosis.

The present disclosure relates to a method for assessing fluid responsiveness of a patient (3) connected to a breathing apparatus (2) providing mechanical ventilation to the patient (3). The method comprises the steps of monitoring a respiratory pressure of the patient (3), controlling a pneumatic unit (17) of the breathing apparatus (3) to provide baseline ventilation of the patient (3) with alternating inspiration phases and expiration phases during a period of baseline ventilation, monitoring at least one hemodynamic parameter related to fluid responsiveness of the patient (3), aborting baseline ventilation and initiating an end-expiratory fluid responsiveness assessment [EEFRA] period at an end of an expiration phase, and determining a degree of fluid responsiveness of the patient (3) based on a change in the at least one monitored hemodynamic parameter between the period of baseline ventilation and the EEFRA period. The method further comprises the step of dynamically controlling the pneumatic unit (17) during the EEFRA period based on the monitored respiratory pressure to counteract a change in an intrathoracic pressure of the patient (3) during spontaneous respiratory efforts by the patient (3).

Methods and apparatus for treating a respiratory disorder, m one aspect, include an apparatus that delivers backup breaths at a sustained timed backup rate that is a function of the patient's spontaneous respiratory rate. Other aspects include apparatus that delivers backup breaths at a rate that gradually increases from a spontaneous backup rate to a sustained timed backup rate or, alternatively, apparatus that oscillates a treatment pressure in antiphase with the patient's spontaneous respiratory efforts when a measure indicative of ventilation is greater than a threshold. Other aspects include apparatus configured to treat Cheyne-Stokes respiration by computing the treatment pressure so as to bring a measure indicative of ventilation of the patient towards a target ventilation that is dependent on the measure indicative of ventilation or, alternatively, by periodically elevating the treatment pressure to a high level for a short time.

A photoplethysmogram system and method are disclosed. The system includes at least three light sources of different frequencies configured to emit light into a subject's skin. A PPG sensor detects the light from the multiple light sources after it has passed through the subject's skin and generates a PPG signal for each light source. A processor, communicatively coupled to the PPG sensor, receives the PPG signals and estimates physiological parameters from each PPG signal. The light sources may include a red light source, an infrared light source, and a green light source, with the green light source used for calibration in the measurement of blood oxygen saturation. The processor may dynamically perform amputation or imputation of the PPG signals based on the consistency of the signals from the different light sources. The physiological parameters may include respiratory effort and pulse rate and pulse rate variability.

The present application relates to the technical field of respiratory health monitoring, in particular to a respiratory health auxiliary monitoring method and system for chronic lung diseases, comprising: collecting a chest fluctuation image sequence, an environmental sound stream and a wearable chest and abdominal movement waveform to form multi-modal respiratory data, and obtaining a respiratory effort signal, a respiratory sound feature and a chest and abdominal breathing component through targeted processing. Relying on the respiratory physiological coupling relationship, a high-credibility comprehensive respiratory waveform is generated through an asynchronous adaptive fusion algorithm, multi-dimensional features such as respiratory rhythm, depth and symmetry are extracted, a pre-trained chronic disease state classification model is input, and a corresponding disease category and severity grade are output. The method can weaken the time sequence difference of multi-source signals, strengthen the expression of respiratory physiological features, improve the recognition accuracy of abnormal respiratory patterns, and realize continuous and refined respiratory state monitoring and disease grading evaluation for chronic lung diseases.

This invention is a respiratory monitoring device that uses two or more sensors to map a patient's respiratory movements to interpret them as respiratory effort and severity scores. The core components of this invention are contact-based sensors that measure relative movements of the chest, abdomen, and / or other key anatomical features; a processing unit that acquires data from all sensors; an algorithm that analyzes and compares data from each sensor to understand the relative movements and interpret them as clinically relevant information; and a display screen that shares this information with the clinician. These sensors are interconnected and connected to the information processing unit, which shares data with the screen to display a respiratory severity score based on analysis of respiratory effort using a thoracoabdominal asynchronous (TAA) or similar indicators measured by the sensor network and analyzed by the algorithm.

To provide a biological information processing apparatus and a biological information processing method capable of determining a type of a respiratory disorder without using a respiratory motion sensor worn on an abdomen or a chest.SOLUTION: A biological information processing apparatus detects, from a pulse wave during sleep, a low-respiratory or apnea section within a measurement period for the pulse wave. The biological information processing apparatus then determines presence or absence of respiratory effort on the basis of the pulse wave in the detected low-respiratory and / or apnea section. The biological information processing apparatus determines a type of a respiratory disorder for the detected low-respiratory and / or apnea section on the basis of the presence or absence of the respiratory effort.SELECTED DRAWING: Figure 2