System for detecting blood flow parameters based on pulse wave measurement and analysis
A technology of parameter detection and pulse wave, which is applied in the field of blood flow parameter detection system, can solve the problems that the characteristics of pulse wave cannot be quantified, the peak 4 of dicrotic wave is blurred and disappears, etc.
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Embodiment 1
[0073] Such as Figure 9 As shown, in this example, the blood flow parameter detection system includes: a data acquisition module, which is used to collect pulse wave signals. Conversion and other processing; the data analysis module is used to analyze the pulse wave digital signal from the data acquisition module, quantify the pulse wave waveform characteristics into characteristic indicators, and the system also uses the characteristic indicators as calculation factors to perform further calculations to generate a series of quantified hemodynamics academic indicators. Perform time domain and frequency domain analysis on the above indicators to generate parameter lists and statistical charts.
[0074] These characteristic indicators include:
[0075] 1) The overall and local area under the pulse wave curve and its area coefficient, including the entire pulse wave area A', the wave area Ad' of the corresponding part of the ascending branch and its area coefficient Cd, and th...
Embodiment 2
[0084] Embodiment 2 clinical application
[0085]Apply the system of the present invention to collect data through fingertips and analyze them. Table 1 shows a total of 2000 samples of general healthy people in six different age groups randomly selected, the age span ranges from 18 to 82 years old, the fingertip volume blood flow pulse wave signal of each individual is collected in a quiet state, and the system of the present invention is used The obtained pulse wave characteristic indexes are calculated and counted, and the results are as follows:
[0086] Table 1 Analysis of pulse wave morphological characteristics of general healthy people in different age groups
[0087]
generation
average age
Number of samples
(X2-X) / (X-X1)
Mean age characteristic index
standard deviation
18 to 30 years old
24.10
380
0.345
0.061
31-40 years old
34.00
310
0.385
0.055
...
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