Detail publikace

Comparison of Baseline Wandering Removal Algorithms for Automatic Clas sification of Electrocardiogram

Originální název

Comparison of Baseline Wandering Removal Algorithms for Automatic Clas sification of Electrocardiogram

Anglický název

Comparison of Baseline Wandering Removal Algorithms for Automatic Clas sification of Electrocardiogram

Jazyk

en

Originální abstrakt

Baseline wandering (sometimes also baseline drift) is a noise that exacerbates the evaluation of ECG and reduces the success of automatic ECG classifiers. In previous works, many methods have been proposed to remove such noise. The aim of this article is to compare commonly used methods. Each signal is in parallel reprocessed by all analyzed methods a nd then enters an automatic classifier that is able to classify QRS complexes. According to the classification success, the proposed methods were compared. Based on the results of this work, the best method for removing baseline wandering in the ECG is wav elet filtration. The success of the classification is further improved by the combination of wavelet filtration and EEMD. The disadvantage of this combination is its very high computational complexity .

Anglický abstrakt

Baseline wandering (sometimes also baseline drift) is a noise that exacerbates the evaluation of ECG and reduces the success of automatic ECG classifiers. In previous works, many methods have been proposed to remove such noise. The aim of this article is to compare commonly used methods. Each signal is in parallel reprocessed by all analyzed methods a nd then enters an automatic classifier that is able to classify QRS complexes. According to the classification success, the proposed methods were compared. Based on the results of this work, the best method for removing baseline wandering in the ECG is wav elet filtration. The success of the classification is further improved by the combination of wavelet filtration and EEMD. The disadvantage of this combination is its very high computational complexity .

BibTex


@inproceedings{BUT139071,
  author="Radovan {Smíšek} and Martin {Vítek} and Jana {Kolářová}",
  title="Comparison of Baseline Wandering Removal Algorithms for Automatic Clas sification of Electrocardiogram",
  annote="Baseline  wandering   (sometimes  also  baseline  drift) is a noise that exacerbates the evaluation of  ECG and reduces the  success  of  automatic  ECG  classifiers.  In  previous  works,  many  methods  have  been  proposed  to  remove  such   noise.  The  aim  of  this article is to compare commonly used methods. Each signal is  in  parallel  reprocessed  by  all  analyzed  methods  a nd  then  enters  an  automatic  classifier  that  is  able  to  classify  QRS  complexes. According  to  the  classification  success,  the  proposed  methods  were  compared.  Based  on  the  results  of  this  work,  the  best  method  for  removing  baseline  wandering   in  the  ECG  is  wav elet  filtration. The success of the classification is  further  improved  by  the    combination    of    wavelet    filtration    and    EEMD.  The  disadvantage  of  this  combination  is  its  very  high  computational  complexity .",
  address="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  booktitle="Proceedings of IEEE Student Branch Conference Mikulov 2017",
  chapter="139071",
  howpublished="online",
  institution="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  year="2017",
  month="august",
  pages="63--66",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  type="conference paper"
}