NDLI: Recognizing specific human pulse signal based on clustering analysis

Content Provider	IEEE Xplore Digital Library
Author	Menglong Liu Sijie Zhu Baojian Gao Beiyun Li
Copyright Year	2015
Description	Author affiliation: Dept. of Pharmacy, Memorial Univ. of Newfoundland, St. John's, NL, Canada (Beiyun Li) \|\| Dept. of Inf. Sci. & Technol., Northwest Univ., Xi'an, China (Menglong Liu; Baojian Gao) \|\| Dept. of Electron. & Inf. Eng., South-Central Univ. for Nat., Wuhan, China (Sijie Zhu)
Abstract	In this paper, we propose a pattern classification approach to learn and recognize human pulse signal. Different from previous work, the approach introduced in this paper of processing signals is oriented by the perspective of system analysis, and is aimed to recognize the pulse signal of pregnant objects from that of unfertilized female adults. Firstly, we apply homomorphic deconvolution model to get two types of human pulse signal curves in cepstrum domain and extract its Mel-Frequency Cepstrum Coefficient. This step is the learning process which learns characteristic parameters of human pulse signal, and besides, frequency characteristics and formant parameters of human pulse transmission system. Secondly, the Mel-Frequency Cepstrum Coefficient is processed via Dynamic Time Warping and Fuzzy C-Means Clustering, thus detecting parameter ranges of human pulse signal and utilizing them as the classifier in the subsequent recognition process. Instead of optimizing by solely applying Dynamic Time Warping, our approach, which combines Fuzzy C-Means Clustering and Dynamic Time Warping, tends to optimize the recognition rate significantly due to its advantage of searching for the globally optimal solution.
Starting Page	800
Ending Page	805
File Size	405217
Page Count	6
File Format	PDF
e-ISBN	9781479980475
DOI	10.1109/IADCC.2015.7154817
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-12
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pregnancy Heart Mel-Frequency Cepstrum Coefficient (MFCC) Deconvolution Human pulse signal Frequency-domain analysis Dynamic Time Warping (DTW) Cepstrum Fuzzy C-Means Clustering (FCM) Mathematical model homomorphic deconvolution model Mel frequency cepstral coefficient
Content Type	Text
Resource Type	Article

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