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Human body heart rate variability and respiration rate measuring method based on variational mode decomposition and constrained independent component analysis

A technology of independent component analysis and variational modal decomposition, applied in diagnostic recording/measurement, pattern recognition in signals, character and pattern recognition, etc. The effect of avoiding sorting ambiguity and improving robustness

Pending Publication Date: 2022-06-03
ANHUI UNIVERSITY +1
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Problems solved by technology

[0012] The object of the present invention is to provide a kind of HRV and RR measuring method based on variational mode decomposition (VMD) and constrained independent component analysis (cICA), extract HRV parameter and RR synchronously from human face video, avoid traditional method Inherent BVP source sorting fuzzy problem, and well overcome the difficult problem of BVP source signal noise residual in the extraction of physiological parameters

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  • Human body heart rate variability and respiration rate measuring method based on variational mode decomposition and constrained independent component analysis
  • Human body heart rate variability and respiration rate measuring method based on variational mode decomposition and constrained independent component analysis
  • Human body heart rate variability and respiration rate measuring method based on variational mode decomposition and constrained independent component analysis

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[0035] The human body HRV and RR measurement method of the present invention performs pixel coherent average operation on human face video data, and converts it into RGB observation signals. Then preprocess the RGB observation signal to obtain a standardized observation signal, and use the VMD algorithm to decompose the G channel signal into 4 channels, and calculate the BVP reference signal based on the component with the largest spectrum peak among the decomposed 4 channel components . Further, based on the reference signal, the BVP source signal is separated from the RGB observation signal by using the cICA algorithm, and the BVP source signal is decomposed into 4 channels by using the VMD algorithm, and high-quality pulse wave components are extracted from the decomposed 4-channel components. Finally, the HRV parameters were obtained based on high-quality pulse wave components: low frequency component power (LF), high frequency component power (HF), low frequency component...

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Abstract

The invention discloses a human heart rate variability (HRV) and respiratory rate (RR) measurement method based on variational mode decomposition (VMD) and constrained independent component analysis (cICA), which comprises the following steps: performing pixel coherent average operation on human face video data, converting the human face video data into RGB observation signals, and performing preprocessing operation on the RGB observation signals to realize standardization. Performing four-channel decomposition on the G-channel signal by using a VMD algorithm, and solving a reference signal of a blood flow pulse (BVP) on the basis of the component with the maximum spectrum peak value in the decomposed four-channel components; based on the reference signal, a cICA algorithm is used for separating a BVP source signal from the RGB observation signal, a VMD algorithm is used for conducting four-channel decomposition on the BVP source signal, high-quality pulse wave components are extracted from the separated four-channel components, and HRV parameters and RR are further obtained. According to the method, the inherent source sorting fuzzy problem in a traditional blind source separation / independent component analysis algorithm can be avoided, and the method has good noise interference resistance and has good application prospects in the field.

Description

technical field [0001] The present invention relates to the research field of extraction of facial video physiological parameters based on imaging photoplethysmography (IPPG) technology, including the extraction of heart rate variability (HRV) parameters and respiration rate (RR), in particular to the variational mode decomposition (VMD) algorithm , the constrained independent component analysis (cICA) algorithm. Background technique [0002] Heart rate variability (HRV) and respiration rate (RR) are important clinical physiological parameters of the human body. Exploring the non-contact measurement method of HRV and RR has become one of the research hotspots in the field of biomedical engineering and instrumentation. [0003] Imaging Photoplethysmography (IPPG) is a biomedical signal processing technology that analyzes the video data of sensitive areas on the human body surface through intelligent information processing algorithms, and then realizes the extraction of physi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62A61B5/0205
CPCA61B5/0205G06F2218/04G06F2218/08G06F18/2134
Inventor 卫兵吴小培吕钊张超张磊高浩渊吴蕊
Owner ANHUI UNIVERSITY
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