title: Efficient Fine Arrhythmia Detection Based on DCG P-T Features.
abstract: Due to the high mortality associated with heart disease, there is an urgent demand for advanced detection of abnormal heart beats. The use of dynamic electrocardiogram (DCG) provides a useful indicator of heart condition from long-term monitoring techniques commonly used in the clinic. However, accurately distinguishing sparse abnormal heart beats from large DCG data sets remains difficult. Herein, we propose an efficient fine solution based on 11 geometrical features of the DCG PQRST(P-T) waves and an improved hierarchical clustering method for arrhythmia detection. Data sets selected from MIT-BIH are used to validate the effectiveness of this approach. Experimental results show that the detection procedure of arrhythmia is fast and with accurate clustering.
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing, China.
authors.forename: Rongfang
authors.initials: R
authors.lastname: Bie
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing, China.
authors.forename: Shuaijing
authors.initials: S
authors.lastname: Xu
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing, China.
authors.forename: Guangzhi
authors.initials: G
authors.lastname: Zhang
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing, China.
authors.forename: Meng
authors.initials: M
authors.lastname: Zhang
authors.affiliation: Cardiac Department, Beijing Rehabilitation Hospital of Capital Medical University, Beijing, China.
authors.forename: Xianlin
authors.initials: X
authors.lastname: Ma
authors.affiliation: Cardiac Department, Beijing Rehabilitation Hospital of Capital Medical University, Beijing, China. xlzhang63@163.com.
authors.forename: Xialin
authors.initials: X
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis*; D015716:Electrocardiography, Ambulatory / Q000379:methods*; D006801:Humans; D012815:Signal Processing, Computer-Assisted; D060388:Support Vector Machine
keywords: Abnormal heart beats; Arrhythmia detection; Clustering; DCG; Feature vector