Research And Implementation Of Key Technologies For Sleep Ventilator Respiratory Detection

The basis of better work of sleep ventilator is to accurately detect and judge the patient's respiratory rhythm,respiratory rate,breath strength and respiratory events as the basis for the adjustment of therapeutic pressure regulation parameters.Therefore,sleep ventilators are very important for the detection of respiratory parameters,respiratory follow-up,and recognition of respiratory events.At the same time,it is of great medical significance to detect the patient's respiratory ventilation during sleep.In this paper,human sleep breathing is taken as the research object.The pressure sensor and differential pressure sensor are used as the detection sensor of the system.Combined with the signal processing technology,the human body is treated with the sleep ventilator to realize the accurate and timely follow-up of the human body's breathing and compensation.Breathing ventilation pressure,and detecting human respiratory events,and finally achieving automatic pressure regulation.In this paper,the pressure sensor and differential pressure sensor of the system respectively collect the airflow pressure of the ventilator output and the pressure difference signal inside the pipeline,which are filtered and sent into the microprocessor to provide the source of data for software algorithm processing.According to the characteristics of airflow changes during sleep,a respiratory pressure following algorithm is proposed.The method detects the patient's breathing in real time and accurately identifies the critical point of the transition between exhalation and inspiration.At the same time,the output pressure is compensated according to the change of the breath.To ensure that the actual pressure output is consistent with the preset treatment pressure.According to the characteristics of respiratory obstructive apnea and central apnea,this paper proposes a method of apnea detection and discrimination,using this detection algorithm to compare with a domestic ventilator.The experimental results show that the detection method proposed in this paper can be detected in time and accurately.Aiming at the problem of obstructive hypoventilation in patients,this paper proposes a method based on double blocking factor.The method compares the normal respiratory waveform with the respiratory waveform of the obstruction based on the characteristics of the waveform of the patient's obstructed hypopnea.Experiments show that the method can effectively and accurately detect obstructive hypopnea,and the real-time discrimination is higher.Aiming at the problem of dryness caused by disturbances such as coughing and swallowing during the exhalation phase,a method of respiratory effort detection is proposed.According to the latest interpretation rules of respiratory events proposed by the American Academy of Sleep Medicine(AASM),an automatic pressure regulation algorithm was proposed.The experimental results show that the proposed automatic pressure regulation algorithm can effectively treat patients with Sleep Apnea Syndrome(SAS),and can improve the comfort and compliance of patients during the treatment,thus improving the patient's sleep.Ventilation status.