title: Characteristic wave detection in ECG signal using morphological transform.
abstract: BACKGROUND
  Detection of characteristic waves, such as QRS complex, P wave and T wave, is one of the essential tasks in the cardiovascular arrhythmia recognition from Electrocardiogram (ECG).
  
  
  METHODS
  A multiscale morphological derivative (MMD) transform-based singularity detector, is developed for the detection of fiducial points in ECG signal, where these points are related to the characteristic waves such as the QRS complex, P wave and T wave. The MMD detector is constructed by substituting the conventional derivative with a multiscale morphological derivative.
  
  
  RESULTS
  We demonstrated through experiments that the Q wave, R peak, S wave, the onsets and offsets of the P wave and T wave could be reliably detected in the multiscale space by the MMD detector. Compared with the results obtained via with wavelet transform-based and adaptive thresholding-based techniques, an overall better performance by the MMD method was observed.
  
  
  CONCLUSIONS
  The developed MMD method exhibits good potentials for automated ECG signal analysis and cardiovascular arrhythmia recognition.
authors.affiliation: Bioinformatics Institute, 138671, Singapore. sunyan@bii.a-star.edu.sg
authors.forename: Yan
authors.initials: Y
authors.lastname: Sun
authors.forename: Kap Luk
authors.initials: KL
authors.lastname: Chan
authors.forename: Shankar Muthu
authors.initials: SM
authors.lastname: Krishnan
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D012815:Signal Processing, Computer-Assisted