Publication Type:

Conference Paper


International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE), IEEE (2014)

Accession Number:




Cardiovascular Diseases, Cardiovascular system, Daubechies algorithm, Daubechies wavelet, Daubechies wavelet filter, digitized ECG input signal, Diseases, ECG, ECG analysis system, ECG diagnostic system, electrical activity measurement, electrical activity recording, Electrocardiography, Feature extraction, Filter banks, filtering theory, highly accurate ECG feature extraction, Lattices, medical signal processing, MIT-BIH arrhythmia database, multiresolution analysis, multiresolution wavelet transform, sensitive diagnostic tool, Signal resolution, wavelet transform, Wavelet transforms


An ECG is a sensitive diagnostic tool used to detect various cardio-vascular diseases by measuring and recording the electrical activity of the heart. The efficiency and speed of the feature extraction scheme has a major role in the ECG diagnostic system. The proposed work tries to develop an ECG feature extraction system based on the multi-resolution wavelet transform. This system tries to improve the performance of ECG analysis system by extracting highly accurate ECG features. The Daubechies wavelet filter is used here for extracting ECG features. MIT-BIH Arrhythmia database is used in this work to obtain the digitized ECG input signal.

Cite this Research Publication

A. Balachandran, Ganesan, M., and Sumesh, E. P., “Daubechies algorithm for highly accurate ECG feature extraction”, in International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE), 2014.