author = {Julien Oster and Olivier Pietquin and Roger Abächerli and Michel Kraemer and Jacques Felblinger},
title = {A Specific QRS Detector for Electrocardiography during MRI: Using Waveltets and Local Regularity Characterization},
year = {2009},
booktitle = {Proceedings of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2009)},
pages = {341-344},
month = {April},
address = {Taipei (Taiwan)},
url = {http://doi.ieeecomputersociety.org/10.1109/ICASSP.2009.4959590},
doi = {10.1109/ICASSP.2009.4959590},
abstract = {Automatic Electrocardiogram (ECG) analysis, especially QRS detection, is still a challenging task. This is even more the case when the ECG is acquired during Magnetic Resonance (MR) examination. The MR environment highly distorts ECG, with Hall Effect, due to the important magnetic static field, and artifacts, due to fast switching magnetic field gradients. Detection of the QRS complexes is then affected. In this paper, a new specific MR QRS detector is presented. This method is based on the modulus maximum lines and on the Lipschitz exponent estimation they offer. The use of this regularity characterization permits to distinguish between QRS complexes and MR artifacts. This detector outperforms existing algorithms with almost 99% sensitivity and positive prediction value.}