Time series Clustering and Analysis of ECG heart-beats using Dynamic Time Warping

Author

Annam, Jagadeeswara Rao ; Mittapalli, Sai Sudheer ; Bapi, R.S.

Author_Institution

DCIS, Univ. of Hyderabad, Hyderabad, India

fYear

2011

fDate

16-18 Dec. 2011

Firstpage

1

Lastpage

3

Abstract

A novel Time series Clustering and Analysis Method for ECG (Electro Cardiogram) heart-beat Analysis is proposed using K-medoids Clustering with Dynamic Time Warping (DTW) distance. The main objective of this paper is to identify the abnormalities in ECG heart beats through Clustering and Validation by using QRS complexes of ECG heart-beats. The ECG data obtained from MIT-BIH Arrhythmia Database, is used for experimentation. The 5 types of classes in ECG heart beats, used in this study are Normal (N), Left bundle branch blocks (LBBB), Right bundle branch blocks (RBBB), Premature ventricular contraction (PVC), Atrial premature contraction (APC).

Keywords

electrocardiography; medical signal processing; pattern clustering; time series; ECG heart-beats; MIT-BIH arrhythmia database; QRS complexes; atrial premature contraction; dynamic time warping; k-medoids clustering; left bundle branch blocks; premature ventricular contraction; right bundle branch blocks; time series clustering; Biomedical measurements; Data models; Electrocardiography; Feature extraction; Heart beat; Heuristic algorithms; Time series analysis; DTW; ECG; Heart-beat; QRS; Time Series Clustering; k-medoid;

fLanguage

English

Publisher

ieee

Conference_Titel

India Conference (INDICON), 2011 Annual IEEE

Conference_Location

Hyderabad

Print_ISBN

978-1-4577-1110-7

Type

conf

DOI

10.1109/INDCON.2011.6139394

Filename

6139394