Detail publikačního výsledku

Single-Feature Method for Fast Atrial Fibrillation Detection in ECG Signals

MARŠÁNOVÁ, L.; NĚMCOVÁ, A.; SMÍŠEK, R.; SMITAL, L.; VÍTEK, M.

Originální název

Single-Feature Method for Fast Atrial Fibrillation Detection in ECG Signals

Anglický název

Single-Feature Method for Fast Atrial Fibrillation Detection in ECG Signals

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

Atrial fibrillation (AF) is the most common arrhthmia in adults and is associated with higher risk of heart failure or death. Here, we introduce simple and efficient method for automatic AF detection based on symbolic dynamics and Shannon entropy. This method comprises of three parts. Firstly, QRS complex detection is provided, than the raw RR sequence is transformed into a sequence of specific symbols and subsequently into a word sequence and finally, Shannon entropy of the word sequence is calculated. According to the value of Shannon entropy, it is decided, whether AF is present in the current cardiac beat. We achieved sensitivity Se=96.32% and specificity Sp=98.61 on MIT-BIH Atrial Fibrillation database, Se=91.30% and Sp=90.80% on MIT-BIH Arrhythmia database, Se=95.6% and Sp=80.27% for CinC Challenge database 2020. The achieved results of our one-feature method are comparable with other authors of more complicated and computationally expensive methods.

Anglický abstrakt

Atrial fibrillation (AF) is the most common arrhthmia in adults and is associated with higher risk of heart failure or death. Here, we introduce simple and efficient method for automatic AF detection based on symbolic dynamics and Shannon entropy. This method comprises of three parts. Firstly, QRS complex detection is provided, than the raw RR sequence is transformed into a sequence of specific symbols and subsequently into a word sequence and finally, Shannon entropy of the word sequence is calculated. According to the value of Shannon entropy, it is decided, whether AF is present in the current cardiac beat. We achieved sensitivity Se=96.32% and specificity Sp=98.61 on MIT-BIH Atrial Fibrillation database, Se=91.30% and Sp=90.80% on MIT-BIH Arrhythmia database, Se=95.6% and Sp=80.27% for CinC Challenge database 2020. The achieved results of our one-feature method are comparable with other authors of more complicated and computationally expensive methods.

Klíčová slova

ECG, atrial fibrillation, phasor transform, symbolic dynamic

Klíčová slova v angličtině

ECG, atrial fibrillation, phasor transform, symbolic dynamic

Autoři

MARŠÁNOVÁ, L.; NĚMCOVÁ, A.; SMÍŠEK, R.; SMITAL, L.; VÍTEK, M.

Rok RIV

2021

Vydáno

28.12.2020

Nakladatel

IEEE

Místo

Rimini, Italy

Kniha

Computing in Cardiology 2020

ISSN

2325-887X

Periodikum

Computing in Cardiology

Svazek

47

Číslo

1

Stát

Spojené státy americké

Strany od

1

Strany do

4

Strany počet

4

URL

http://www.cinc.org/archives/2020/pdf/CinC2020-335.pdf

Plný text v Digitální knihovně

http://hdl.handle.net/11012/196703

BibTex

@inproceedings{BUT166074,
  author="Lucie {Šaclová} and Andrea {Němcová} and Radovan {Smíšek} and Lukáš {Smital} and Martin {Vítek}",
  title="Single-Feature Method for Fast Atrial Fibrillation Detection in ECG Signals",
  booktitle="Computing in Cardiology  2020",
  year="2020",
  journal="Computing in Cardiology",
  volume="47",
  number="1",
  pages="1--4",
  publisher="IEEE",
  address="Rimini, Italy",
  doi="10.22489/CinC.2020.335",
  url="http://www.cinc.org/archives/2020/pdf/CinC2020-335.pdf"
}