Method for detecting quality of physiological signal based on self-correlation function

Abstract

The invention discloses a method for detecting the quality of a physiological signal based on a self-correlation function. According to the method disclosed by the invention, a physiological signal model under a theoretical condition is self-correlated with a physiological signal acquired under a practical condition; a relationship between the theoretical condition and the practical condition is obtained by analysis; simultaneously, the invention provides a universal method for detecting the quality of the physiological signal by utilizing the characteristic that the physiological signal has quasi-periodicity; and the method comprises the steps of respectively obtaining amplitude scaling factors under the theoretical condition and the practical condition, judging whether a difference value rate satisfies set requirements or not, and obtaining a quality detecting result. The method disclosed by the invention is applicable to all physiological signals; furthermore, the quality detecting result can be obtained only by adopting a certain segment of function in the physiological signals; therefore, the calculation amount is effectively reduced; and the signals can be evaluated in real time.

Description

technical field [0001] The invention relates to physiological signal quality detection, in particular to a physiological signal quality detection method based on an autocorrelation function. Background technique [0002] Physiological signals are physiological information sent by human organs and tissues, generally including ECG signals, blood oxygen volume waves, respiratory signals, blood pressure signals, brain wave signals, etc. Physiological signals, as a comprehensive manifestation of the electrical activity of the body, are one of the important bases for diagnosing diseases and evaluating whether the body is functioning well. [0003] In the actual collection process, due to the influence of the external environment, the influence of electromagnetic interference, the influence of temperature, the influence of power frequency signals, the noise introduced by equipment, the EMG interference introduced by testers and wearers, etc., the collected physiological signals are...

AI Technical Summary

Problems solved by technology

However, the disadvantages of doing this are:

[0005] 1. Since a long signal needs to be analyzed, it needs to collect the signal within a certain period of time. In this way, it will not be possible to evaluate the signal in real time, and the calculation amount is large and the technical complexity is high

[0006] 2. Since physiological signals include ECG signals, blood oxygen volume waves, respiratory signals, blood pressure signals, brain wave signals, etc., in the existing quality detection algorithms, usually for different signals to be detected in physiological signals, according to their waveform characteristics, Obtain eigenvalue points, and then use different algorithms for quality inspection, but cannot use one algorithm for inspection at the same time, which brings inconvenience

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