Arrhythmia detection in single-lead ECG by combining beat and rhythm-level information

Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:3236-9. doi: 10.1109/EMBC.2014.6944312.

Abstract

In this paper, we propose a method for detecting arrhythmia in single-lead electro-cardiogram (ECG) signal. By applying a sequence of pre-processing steps (filtering, baseline correction), beat classification and rhythm identification, six different beat-types and four abnormal rhythms are detected. Beat classification uses fast Fourier transform (FFT) as the feature and a support vector machine (SVM) classifier. Subsequently rhythm identification uses a deterministic finite state machine to detect abnormal rhythms. We evaluate the performance of our technique on the MIT-BIH database, to obtain 97% beat classification accuracy and perfect rhythm identification result.

MeSH terms

  • Algorithms
  • Arrhythmias, Cardiac / diagnosis*
  • Arrhythmias, Cardiac / physiopathology*
  • Electrocardiography / methods*
  • Electrodes
  • Fourier Analysis
  • Heart Rate / physiology*
  • Humans
  • ROC Curve
  • Signal Processing, Computer-Assisted