The moment segmentation analysis of heart sound pattern.
This paper presents two new ideas. The first one is to apply the Viola integral waveform method to analyze the heart sounds recorded by an electric stethoscope, and the multi-scale moment analysis is proposed to locate each cycle of heart sounds. A fast algorithm for calculating characteristic waveform (CW) and characteristic moment waveform (CMW) of heart sound can be expressed by the Viola integral method, and their calculation time has nothing to do with their scales. The second idea is easier to segment the heart sound based on its approximate cyclical characteristic than the ordinary methods. Each heart sound cycle can be quickly found by CMW's Local Extreme Points (LEPs). Based on the information of LEPs and CW, a high accurate search algorithm to segment S1 and S2 sounds is submitted. By numerical experiments, the important parameters of time scale delta=0.05s for CW and l=0.45s for CMW are obtained and validated for segmentation of heart sound.


CONCLUSIONS
More exact segmentation boundaries of the heart sound signal could be located fast in an automated way, and a further performance analysis is presented. Owing to the use of the rhythm of CMW curves, the proposed method not only gives a higher success segmentation rate, but also it is actually simpler and faster than the wavelet method.
Yan
Zhonghong
Z
Biomedical Department, ChongQing Institute of Technology, China. yzh816@msn.com
Jiang
Zhongwei
Z
Miyamoto
Ayaho
A
Wei
Yunlong
Y
D000465:Algorithms; D001185:Artificial Intelligence; D005583:Fourier Analysis; D006347:Heart Sounds; D006801:Humans; D010701:Phonocardiography / Q000706:statistics & numerical data*; D012815:Signal Processing, Computer-Assisted