Photoelectric volume wave-based breathing rate monitoring method

Abstract

The invention discloses a photoelectric volume wave-based breathing rate monitoring method. The method is characterized by comprising the following steps: first, acquiring a photoelectric volume wave digital signal of the change of the blood volume on a capillary bed on the surface of skin at a position to be monitored, wherein the signal is an original photoelectric volume wave signal which has not been filtered, contains breathing information and has a sampling frequency over 500 Hz; then, preprocessing an acquired photoelectric volume wave by using a mathematical morphology method; next, detecting a peak point and a valley point of each beat of a volume pulse wave by adopting a characteristic point positioning method by the preprocessed signal; later on, calculating time interval variable of each beat and the difference variable between the peak point and the valley point of each beat; and finally, detecting obtained the breathing rhythms of the time interval variable and an amplitude variable, and calculating a breathing rate.

Description

technical field [0001] The invention relates to a digital signal processing method, in particular to a method for monitoring respiration rate based on photoelectric volumetric wave with high sampling rate. Background technique [0002] Photoplethysmography (Photoplethysmograph, PPG) is a non-invasive detection method that uses photoelectric conversion technology to measure blood volume changes in microvascular beds on the skin surface. Photoplethysmography based on this method has been widely used in the monitoring of blood oxygen saturation and heart rate. Due to the interaction and influence between different systems of the human body, respiratory movement will also cause changes in the peripheral circulation, so the photoplethysmographic signal can be used to realize respiratory monitoring. Compared with existing respiratory monitoring methods, such as thoracic impedance and mouth-nasal airflow, the respiratory monitoring based on photoplethysmographic technology is more...

AI Technical Summary

Problems solved by technology

Relatively speaking, the temperature drift of extremely low frequency is easier to eliminate, but the influence of the Meyer wave component that is very close to the respiratory frequency or even overlaps with each other on the respiratory wave cannot be ignored, especially when the frequencies of the two waveforms overlap, the filtering method It is difficult to extract two different waveforms in the same frequency band separately

Although the Chinese patent ZL03808327.2 points out the corresponding phase change characteristics of respiratory waves and Meyer waves, under the condition that two different waveforms are clearly obtained, it can be judged as respiratory waves or Meyer waves by the phase relationship, but this invention does not No clear technical solution is proposed on how to separate the two waveforms with frequency aliasing

On the other hand, when studying breath detection, it is considered that the breath information is only included in the baseline components below 0.5Hz extracted by filtering, and the breath research is limited to the baseline components

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