5 results about "Respiratory effort" patented technology

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.

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.

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.

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.