Efficient Fine Arrhythmia Detection Based on DCG P-T Features.

Journal: Journal of medical systems
PMID: 27234479

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

  • Rongfang Bie
    College of Information Science and Technology, Beijing Normal University, Beijing, China.
  • Shuaijing Xu
    College of Information Science and Technology, Beijing Normal University, Beijing, China.
  • Guangzhi Zhang
    College of Information Science and Technology, Beijing Normal University, Beijing, China.
  • Meng Zhang
    College of Software, Beihang University, Beijing, China.
  • Xianlin Ma
    Cardiac Department, Beijing Rehabilitation Hospital of Capital Medical University, Beijing, China.
  • Xialin Zhang
    Cardiac Department, Beijing Rehabilitation Hospital of Capital Medical University, Beijing, China. xlzhang63@163.com.

Keywords

External Resources

Popular Topics
Recent Journals