A model for automatic identification of human pulse signals

Autor:	Pei-yong Zhang, Hui-yan Wang
Rok vydání:	2008
Předmět:	Engineering business.industry Pulse (signal processing) Feature extraction General Engineering Bayesian network Wavelet transform Pattern recognition Pulse diagnosis Identification (information) Rhythm Feature (computer vision) Artificial intelligence business
Zdroj:	Journal of Zhejiang University-SCIENCE A. 9:1382-1389
ISSN:	1862-1775 1673-565X
Popis:	This paper presents a quantitative method for automatic identification of human pulse signals. The idea is to start with the extraction of characteristic parameters and then to construct the recognition model based on Bayesian networks. To identify depth, frequency and rhythm, several parameters are proposed. To distinguish the strength and shape, which cannot be represented by one or several parameters and are hard to recognize, the main time-domain feature parameters are computed based on the feature points of the pulse signal. Then the extracted parameters are taken as the input and five models for automatic pulse signal identification are constructed based on Bayesian networks. Experimental results demonstrate that the method is feasible and effective in recognizing depth, frequency, rhythm, strength and shape of pulse signals, which can be expected to facilitate the modernization of pulse diagnosis.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::53a97cce4e5fbea10955385f63ae5fed https://doi.org/10.1631/jzus.a0820332 Zobrazit plný text záznamu Full text from SpringerLink