Detail publikace

Robust multichannel QRS detection

Originální název

Robust multichannel QRS detection

Anglický název

Robust multichannel QRS detection

Jazyk

en

Originální abstrakt

The task of the CinC Challenge 2014 was to develop an algorithm for robust detection of a QRS complex throughout different measurement data. Our proposed approach starts with filtering and detection of the QRS complex in channel with electric activity using standard deviation and defines preliminary QRS annotations. The averaged shape (length of 640 ms) for each channel is found by accumulating data close to preliminary annotations through the whole record (max. 10 minutes). The weight of each averaged shape is computed by average correlation of the shape with its original signal through all preliminary QRS annotations. The correlation of each averaged shape to the corresponding channel is multiplied by its weight and forms a new channel containing the total correlation response channels. The resulting QRS annotations are found by tresholding this total correlation response. The final version of our method leads to results of SE+ = 99.87 and P+ = 99.96 for the Challenge Training data set containing 100 records. The overall score was 73.85 at the end of stage I (using an early version of this method) and 83.73 at the end of stage 111.

Anglický abstrakt

The task of the CinC Challenge 2014 was to develop an algorithm for robust detection of a QRS complex throughout different measurement data. Our proposed approach starts with filtering and detection of the QRS complex in channel with electric activity using standard deviation and defines preliminary QRS annotations. The averaged shape (length of 640 ms) for each channel is found by accumulating data close to preliminary annotations through the whole record (max. 10 minutes). The weight of each averaged shape is computed by average correlation of the shape with its original signal through all preliminary QRS annotations. The correlation of each averaged shape to the corresponding channel is multiplied by its weight and forms a new channel containing the total correlation response channels. The resulting QRS annotations are found by tresholding this total correlation response. The final version of our method leads to results of SE+ = 99.87 and P+ = 99.96 for the Challenge Training data set containing 100 records. The overall score was 73.85 at the end of stage I (using an early version of this method) and 83.73 at the end of stage 111.

BibTex


@inproceedings{BUT128410,
  author="Filip {Plešinger} and Juraj {Jurčo} and Pavel {Jurák} and Josef {Halámek}",
  title="Robust multichannel QRS detection",
  annote="The task of the CinC Challenge 2014 was to develop an algorithm for robust detection of a QRS complex throughout different measurement data. Our proposed approach starts with filtering and detection of the QRS complex in channel with electric activity using standard deviation and defines preliminary QRS annotations. The averaged shape (length of 640 ms) for each channel is found by accumulating data close to preliminary annotations through the whole record (max. 10 minutes). The weight of each averaged shape is computed by average correlation of the shape with its original signal through all preliminary QRS annotations. The correlation of each averaged shape to the corresponding channel is multiplied by its weight and forms a new channel containing the total correlation response channels. The resulting QRS annotations are found by tresholding this total correlation response. The final version of our method leads to results of SE+ = 99.87 and P+ = 99.96 for the Challenge Training data set containing 100 records. The overall score was 73.85 at the end of stage I (using an early version of this method) and 83.73 at the end of stage 111.",
  address="CCAL",
  booktitle="Computing in Cardiology",
  chapter="128410",
  edition="2014",
  howpublished="print",
  institution="CCAL",
  year="2014",
  month="september",
  pages="557--560",
  publisher="CCAL",
  type="conference paper"
}