# A SUPERVISED LEARNING APPROACH BASED ON THE CONTINUOUS WAVELET TRANSFORM FOR R SPIKE DETECTION IN ECG

### G. de Lannoy, A. de Decker, M. Verleysen

#### 2008

#### Abstract

One of the most important tasks in automatic annotation of the ECG is the detection of the R spike. The wavelet transform is a widely used tool for R spike detection. The time-frequency decomposition is indeed a powerful tool to analyze non-stationary signals. Still, current methods use consecutive wavelet scales in an a priori restricted range and may therefore lack adaptivity. This paper introduces a supervised learning algorithm which learns the optimal scales for each dataset using the annotations provided by physicians on a small training set. For each record, this method allows a specific set of non consecutive scales to be selected, based on the record characteristics. The selected scales are then used on the original long-term ECG signal recording and a hard thresholding rule is applied on the derivative of the wavelet coefficients to label the R spikes. This algorithm has been tested on the MIT-BIH arrhythmia database and obtains an average sensitivity rate of 99.7% and average positive predictivity rate of 99.7%.

Download#### Paper Citation

#### in Harvard Style

de Lannoy G., de Decker A. and Verleysen M. (2008). **A SUPERVISED LEARNING APPROACH BASED ON THE CONTINUOUS WAVELET TRANSFORM FOR R SPIKE DETECTION IN ECG** . In *Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)* ISBN 978-989-8111-18-0, pages 140-145. DOI: 10.5220/0001062501400145

#### in Bibtex Style

@conference{biosignals08,

author={G. de Lannoy and A. de Decker and M. Verleysen},

title={A SUPERVISED LEARNING APPROACH BASED ON THE CONTINUOUS WAVELET TRANSFORM FOR R SPIKE DETECTION IN ECG},

booktitle={Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)},

year={2008},

pages={140-145},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0001062501400145},

isbn={978-989-8111-18-0},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)

TI - A SUPERVISED LEARNING APPROACH BASED ON THE CONTINUOUS WAVELET TRANSFORM FOR R SPIKE DETECTION IN ECG

SN - 978-989-8111-18-0

AU - de Lannoy G.

AU - de Decker A.

AU - Verleysen M.

PY - 2008

SP - 140

EP - 145

DO - 10.5220/0001062501400145