Enhanced Machine Learning Feature Selection Algorithm for Cardiac Arrhythmia in a Personal Healthcare Application - Details

author：

Jiang, Su-Ya (Jiang, Su-Ya.) ^[1] | Wang, Liang-Hung (Wang, Liang-Hung.) ^[2] (Scholars：王量弘)

Indexed by：

EI Scopus

Abstract：

In　this　paper,　we　propose　a　personal　healthcare　system　to　diagnosis,　monitor,　identify　ectopic　heartbeats　and　provide　services　for　heart　diseases　patients.　The　proposed　system　includes　three　subsystems,　(1)　the　Electrocardiograph　signal　acquisition　device,　(2)　the　mobile　device　with　APP　software　for　signal　processing　and　communication,　and　(3)　Web　service　for　feature　extraction,　selection　and　heartbeat　classification　based　on　the　support　vector　machine.　The　proposed　system　can　identify　16　kinds　of　heartbeats　and　it　can　be　used　in　daily　life.　©　2018　IEEE.

Keyword：

Application programs Biomedical signal processing Classification (of information) Diagnosis Diseases Electrocardiography Feature extraction Health care Microelectronics Support vector machines Web services

Community：

[ 1 ] [Jiang, Su-Ya]Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
[ 2 ] [Wang, Liang-Hung]Department of Microelectronics, College of Physics and Information Engineering, Fuzhou University, Fuzhou, China

Reprint 's Address：

王量弘
[wang, liang-hung]department of microelectronics, college of physics and information engineering, fuzhou university, fuzhou, china

Email：

eetommy@fzu.edu.cn

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Version：

Enhanced Machine Learning Feature Selection Algorithm for Cardiac Arrhythmia in a Personal Healthcare Application
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Source ：

ISSN： 2159-2144

Year： 2018

Volume： 2018-October

Page： 39-42

Language： English

Cited Count：

WoS CC Cited Count：

SCOPUS Cited Count： 7

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 4

Affiliated Colleges：

物理与信息工程学院、微电子学院本学院/部未明确归属的数据

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