Method and system for extracting respiratory signal based on clustering algorithm

Abstract

The invention provides a method and system for extracting respiratory signals based on a clustering algorithm. According to the method of the present invention, first, frequency band division and dimensionality reduction processing are performed on each of the multiple related signals obtained to obtain multiple frequency band signals; then, based on a clustering algorithm, the multiple frequency band signals are clustered to obtain Obtain multiple clusters; then analyze the characteristics of each cluster to obtain the respiratory signal. Since the relevant information comes from the signal collected by the mattress life monitor, it can be used without any impact on the monitored person. , to monitor the breathing of the monitored person during sleep, so as to screen out patients with sleep apnea syndrome.

Description

technical field [0001] The invention relates to the field of respiratory feature analysis, in particular to a method and system for extracting respiratory signals based on a clustering algorithm. Background technique [0002] With the improvement of people's living standards, attention to health issues has begun to rise, especially sleep quality issues. Common unhealthy sleep conditions include: sleep snoring, mouth breathing, even temporary stop of breathing, repeated awakening during sleep, restless sleep, frequent nocturnal angina and arrhythmia, etc. [0003] Sleep apnea syndrome is a disease with a high incidence rate in middle-aged and elderly people. Snoring is snoring, which is the main manifestation of the disease. The snoring sound of ordinary snorers is uniform and regular, and usually occurs after sleeping in the supine position, exertion or drinking. If the snoring is loud and irregular, intermittent, high and low, it indicates that the narrowing of the airwa...

AI Technical Summary

Problems solved by technology

[0007] Since the existing monitoring methods require the monitored personnel to wear relevant devices, the monitoring is extremely inconvenient. Therefore, a respiratory signal acquisition method without wearing is needed to accurately extract the respiratory signals of the people in need.

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