Paper Info
Title
A Practical Approach to Wrist Pulse Segmentation and Single-period Average Waveform Estimation
Abstract
A practical method is proposed to segment the wrist pulse waveform and estimate the average waveform. Some key issues that would affect the performance of the tasks are addressed. A zero-phase filtering was used to accommodate low frequency variations and high frequency noise without the phase-shift distortion, and a moving-window adaptive threshold based segmentation algorithm was used to ensure the segmenting performance. Waveform rotating and scaling, outlier elimination, cross-covariance based alignment, and average waveform estimation were introduced. Testing results show the effectiveness of segmentation performance, and the resulting average waveform well reflect the typical characteristics of the analyzed wrist pulse trend.
Year
DOI
Venue
2008
10.1109/BMEI.2008.140
BMEI (2)
Keywords
Field
DocType
segmentation algorithm,high frequency noise,segmentation performance,low frequency variation,wrist pulse waveform,practical approach,average waveform,average waveform estimation,single-period average waveform estimation,testing result,key issue,wrist pulse trend,wrist pulse segmentation,cross covariance,phase shift,biomedical informatics,adaptive thresholding,high frequency,wavelet transforms,biomedical engineering,low frequency,low frequency noise,mechatronics
Computer vision,Pattern recognition,Infrasound,Cross-covariance,Computer science,Segmentation,Waveform,Filter (signal processing),Pulse (signal processing),Artificial intelligence,Distortion,Wavelet transform
Conference
ISSN
Citations 
PageRank 
1948-2914
11
1.06
References 
Authors
0
7
Name
Order
Citations
PageRank
Chunming Xia12410.70
Yan Li214132.35
Jianjun Yan3237.20
Yiqin Wang45716.28
Haixia Yan5319.47
Rui Guo6237.16
Fufeng Li7339.74