Title :
Real-time classification of electrocardiogram based on fractal and correlation analyses
Author :
Lai, K.T. ; Chan, K.L.
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong
fDate :
29 Oct-1 Nov 1998
Abstract :
The objective of this project is to develop algorithms for real-time electrocardiogram (ECG) classification. The program is made to be concise and accurate enough for use on an ambulatory monitor. A reliable QRS detection algorithm based on a one-pole filter has been developed. Automatic ECG classification using fractal and cross correlation analyses is investigated. The computation demand is not high and real-time analysis is possible. Testing is carried out using the American Heart Association (AHA) ventricular arrhythmia ECG data. The types of beat being selected in the study are: normal (N), premature ventricular contraction (V), and fusion of ventricular and normal beats (F). The classification accuracy of 100% for N and V beats can be achieved in some ECG records
Keywords :
correlation methods; electrocardiography; fractals; medical signal processing; signal classification; waveform analysis; ambulatory monitoring; automatic ECG classification; cross correlation analysis; fractal analysis; fusion of beats; normal beat; one-pole filter; premature ventricular contraction; real-time ECG classification; reliable QRS detection algorithm; ventricular arrhythmia; Algorithm design and analysis; Cardiac disease; Detection algorithms; Electrocardiography; Electronic mail; Fractals; Heart; Patient monitoring; Reliability engineering; Testing;
Conference_Titel :
Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-5164-9
DOI :
10.1109/IEMBS.1998.745844