Paper Info
Title
Time-domain ECG signal analysis based on smart-phone.
Abstract
In this paper, a time domain algorithm architecture is presented and implemented on a smart-phone for ECG signal analysis. Using the QRS detection algorithm suggested by Pan-Tompkins and the beat classification method, the heart beats are detected and classified as normal beats and premature ventricular contractions (PVCs). Subsequently, a computationally efficient method is presented to separate ventricular tachycardia (VT) and ventricular fibrillation (VF). This method utilizes Lempel and Ziv complexity analysis combined with K-means algorithm for the coarse-graining process. In addition, a new classification rule is presented to recognize VT and VF in our study. The proposed system provides fairly good performance when applied to the MIT-BIH Database. This algorithm architecture can be efficiently used on the mobile platform.
Year
DOI
Venue
2011
10.1109/IEMBS.2011.6090713
EMBC
Keywords
Field
DocType
electrocardiography,medical signal detection,ventricular fibrillation,coarse-graining process,time-domain algorithm architecture,time-domain ecg signal analysis,mit-bih database,premature ventricular contraction,ventricular tachycardia,heart beat,medical signal processing,vf,smart-phone,k-means algorithm,pvc,time-domain analysis,ziv complexity analysis,signal classification,qrs detection algorithm,vt,smart phones,mobile computing,lempel complexity analysis,beat classification method,algorithm design and analysis,signal analysis,rhythm,time domain,computer architecture,databases,algorithm design,classification algorithms,k means algorithm
Time domain,Signal processing,Classification rule,Algorithm design,Computer science,Electronic engineering,Ventricular tachycardia,QRS complex,Statistical classification,Electrocardiography
Conference
Volume
Issue
ISSN
2011
null
1557-170X
ISBN
Citations 
PageRank 
978-1-4244-4122-8
1
0.36
References 
Authors
4
3
Name
Order
Citations
PageRank
Shijie Zhou119535.04
Zichen Zhang212.72
Jason Gu342174.77