title: An APN model for Arrhythmic beat classification.
abstract: BACKGROUND
  Changes in the normal rhythm of a human heart may result in different cardiac arrhythmias, which may be immediately fatal or cause irreparable damage to the heart sustained over long periods of time. Therefore, the ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment. In this article, classification by using associative Petri net (APN) for personalized ECG-arrhythmia-pattern identification is proposed for the first time in literature.
  
  
  RESULTS
  A rule-based classification model and reasoning algorithm of APN are created for ECG arrhythmias classification. The performance evaluation using MIT-BIH arrhythmia database shows that our approach compares well with other reported studies.
authors.affiliation: Department of Information Management, National Taichung University of Science and Technology, 129, Section 3, Sanmin Road, Taichung City 404, Taiwan, Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu City, Yunlin County, Taiwan, College of Business Administration, BE321, Louisiana State University in Shreveport, Shreveport, LA 71115, USA and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.
authors.forename: Hsiu-Sen
authors.initials: HS
authors.lastname: Chiang
authors.affiliation: Department of Information Management, National Taichung University of Science and Technology, 129, Section 3, Sanmin Road, Taichung City 404, Taiwan, Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu City, Yunlin County, Taiwan, College of Business Administration, BE321, Louisiana State University in Shreveport, Shreveport, LA 71115, USA and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.
authors.forename: Dong-Her
authors.initials: DH
authors.lastname: Shih
authors.affiliation: Department of Information Management, National Taichung University of Science and Technology, 129, Section 3, Sanmin Road, Taichung City 404, Taiwan, Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu City, Yunlin County, Taiwan, College of Business Administration, BE321, Louisiana State University in Shreveport, Shreveport, LA 71115, USA and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.
authors.forename: Binshan
authors.initials: B
authors.lastname: Lin
authors.affiliation: Department of Information Management, National Taichung University of Science and Technology, 129, Section 3, Sanmin Road, Taichung City 404, Taiwan, Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu City, Yunlin County, Taiwan, College of Business Administration, BE321, Louisiana State University in Shreveport, Shreveport, LA 71115, USA and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.
authors.forename: Ming-Hung
authors.initials: MH
authors.lastname: Shih
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000145:classification / Q000175:diagnosis*; D004562:Electrocardiography; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D055815:Young Adult