A Framework for Automatic Time-Domain Characteristic Parameters Extraction of Human Pulse Signals

Abstract

A methodology for the automated time-domain characteristic parameter extraction of human pulse signals is presented. Due to the subjectivity and fuzziness of pulse diagnosis, the quantitative methods are needed. Up to now, the characteristic parameters are mostly obtained by labeling manually and reading directly from the pulse signal, which is an obstacle to realize the automated pulse recognition. To extract the parameters of pulse signals automatically, the idea is to start with the detection of characteristic points of pulse signals based on wavelet transform, and then determine the number of pulse waves based on chain code to label the characteristics. The time-domain parameters, which are endowed with important physiological significance by specialists of traditional Chinese medicine (TCM), are computed based on the labeling result. The proposed methodology is testified by applying it to compute the parameters of five hundred pulse signal samples collected from clinic. The results are mostly in accord with the expertise, which indicate that the method we proposed is feasible and effective, and can extract the features of pulse signals accurately, which can be expected to facilitate the modernization of pulse diagnosis.

Study of central aortic pressure in hypertensive patients and characteristic of radial artery pressure waveform in Traditional Chinese Medicine

“…Chinese Medicine [20] , Wavelet transform (WT) [21] [17] , and Hilbert-Huang Transform (HHT) [22] [23] in signal processing have been used to extract more features of TCM pulse waveforms. However, these features have no physiological and pathological meanings.…”

“…It is well known that the existing TCM pulse collection instruments can acquire reliable and high-fidelity pulse waveforms [13] . Many methods in signal processing such as time-domain analysis [13] [17] , frequency-domain analysis and time-frequency representation analysis have been applied to the feature extraction of the TCM pulse waveforms. Time-domain analysis is extremely intuitive and can provide the features of TCM pulses with specific physiological and pathological significance.…”

Exploring the conventional pulse conditions using bi-sensing pulse diagnosis instrument

“…The analysis method was roughly divided into two parts: the time domain and the frequency domain. A number of studies have defined many parameters based on wrist pulse waveform in time domain [3,4]. These parameters include: the amplitude of a percussion wave, a tidal wave, and a dicrotic wave, etc.…”

A Quantitative Method for Pulse Strength Classification Based on Decision Tree

“…Therefore, quantitative methods are needed to classify pulse signal. A lot of effort is being spent on pulse signal analysis [1][2][3][4][5][6][7]. In Traditional Chinese Medicine (TCM), pulse signals are considered carrying important information that can reflect the health state of human body.…”

“…The time-domain parameters can reflect the specificity and be representative of pulse signals. So they are endowed with important physiological significance by specialists of TCM and have obvious medical diagnostic importance [6][7]. DT can be built off-line from a training dataset [11].…”