Abstract
Pulse wave contains human physiological and pathological information. Different people will exhibit different characteristics, and hence determining the characteristic points of the pulse wave of human physiological health makes sense. It is common that we extract the characteristic value of pulse wave signal with the method based on wavelet transform on a small scale, and then determine the locations of the characteristic points by modulus maxima and modulus minima. Before determining characteristic value by detecting modulus maxima and modulus minima, we need to determine every period of the pulse wave. This paper presents a new kind of adaptive threshold determination method which is more effective. It can accurately determine every period of the pulse wave, and then extract characteristic values by modulus maxima and modulus minima in every period of the pulse wave. The method presented in this paper promotes the research utilizing pulse wave on health life.
Highlights
The contraction-relaxation cycle in the heart makes the blood in the heart chamber entering the aorta in the form of waves
It is common that we extract the characteristic value of pulse wave signal with the method based on wavelet transform on a small scale, and determine the locations of the characteristic points by modulus maxima and modulus minima
Because the changes of the blood volume reflect the changes of blood vessels, we use infrared photoelectric pulse sensor to record changes of blood volume, and blood volume changing over time produce pulse wave [2]
Summary
The contraction-relaxation cycle in the heart makes the blood in the heart chamber entering the aorta in the form of waves. Pulse wave (main wave, tidal waves, dicroticwave etc.) contains a wealth of physiological information [4] These characteristic values extracted can provide much valuable diagnostic information, and they have an important medical value [5]. Zhao Zhiqiang [6] proposed differential threshold method He took differential operations on rising and falling edges of the pulse wave signal to highlight its characteristics. Researchers have applied wavelet transform to processing and analyzing the pulse wave in recent years. At the same time these methods do not have a universal type To solve these problems, this paper proposes a new approach to extract characteristic points based on wavelet transform.
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