Error handling method for calculating hrv signal in human body impedance signal

Abstract

The invention discloses an error processing method for calculating an HRV signal in a human body impedance signal. In the method, the RRI error identification unit first obtains the position information of the signal where the RRI may be incorrectly identified; The RRI information sets the quality level of the signal to calculate the interpolation information, and finally the interpolation unit performs interpolation according to the calculated interpolation information to obtain a new reliable RRI sequence. The present invention can be used as an effective method to reduce the impact of RRI error recognition with interference impedance signal on the calculation of HRV algorithm, so that the HRV calculation of impedance method can reach the standard of HRV calculation of electrocardiography method, and can improve the usability of human body impedance measurement signal and correct the error. The accurate identification of the RRI sequence can minimize the impact of the wrong RRI sequence on the subsequent HRV calculation.

Description

technical field [0001] The invention belongs to the field of calculation and analysis of human body impedance signals, in particular to a processing method for error signals in the process of extracting and calculating HRV from human body impedance signals. Background technique [0002] The heart rate variability signal (Heart rate variability, HRV for short) refers to the minute change of the instantaneous heart rate or the instantaneous cardiac cycle. Heart rate variability signals contain rich physiological and pathological information of the cardiovascular system and are widely used to fund quantitative assessment of the nervous system. Modern medical research shows that heart rate is the result of the coordinated control of the autonomic nervous system, and factors such as cardiovascular disease, physiological state, and life pressure have a great impact on the regulation of the autonomic nervous system. Extracting heart rate variability signals and identifying abnorma...

AI Technical Summary

Problems solved by technology

After obtaining the RRI sequence based on the data output by the PPG heart rate sensor, the application uses the least square method to fit the data points to obtain a curve, and uses the slope of the straight line part of the curve (ie, the h index) to judge the heart rate trend, and then make a detrending judgment After resampling, this method does not make any difference to the collected overall RRI sequence, which is not conducive to distinguishing and accurately processing wrong RRI signals

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