Sleep apnea event judgment method

Abstract

The invention discloses a sleep apnea event judgment method. The method includes the steps that ballistocardiogram signals and abdomen-thorax respiration signals of a human body are collected in a contactless mode; interval signals are extracted from the ballistocardiogram signals and subjected to interpolation resampling; a cross power spectrum, the coherence coefficients and a coupling spectrum of the interval signals and the respiration signals are calculated; a high frequency curve, a low frequency curve and a ratio curve of the coupling spectrum are obtained; according to the waveform features of the interval signals, the low frequency curve value, the ratio curve value, whether or not a continuous or enhanced thorax-abdomen movement exists and the duration of an event, the sort of the sleep apnea event is judged. According to the method, based on multi-signal processing of the ballistocardiogram signals and the respiration signals and multi-parameter judgment of the waveform features of the interval signals, the low frequency curve value, the ratio curve value, whether or not the continuous or enhanced thorax-abdomen movement exists and the duration of the event, precise judgment of the sort of the sleep apnea event is achieved.

Description

technical field [0001] The present invention relates to the technical field of apnea discrimination, and more specifically, the present invention relates to a sleep apnea discrimination method. Background technique [0002] Sleep apnea monitoring is an important part of sleep monitoring. Sleep apnea monitoring includes 3 main parts: measuring / probing respiratory airflow, respiratory effort, and arterial oxygen saturation. Respiratory events can be interpreted by continuous monitoring of these three, specifically: apnea events, hypopnea events, and respiratory effort-related awakening events. Among them, apnea refers to the complete cessation of oronasal airflow for more than 10 seconds during sleep, which can be divided into obstructive type (continuous breathing effort), central type (no breathing effort) or mixed type (obstructive component after central component). [0003] Clinically, polysomnography is often used to monitor sleep status, combined with manual interpreta...

AI Technical Summary

Problems solved by technology

The wearable detection method simplifies the recording electrodes and sensors, and the patient can perform sleep monitoring at home, but it still has a great impact on the patient's physical and mental state

There are still deficiencies in the existing non-contact detection methods. For example, the antenna is directional, and during sleep, body movements often occur, which will have a certain impact on the results; or only a single signal is monitored, and the type of apnea cannot be judged.

Images