title: A wavelet-based ECG delineation algorithm for 32-bit integer online processing.
abstract: BACKGROUND
  Since the first well-known electrocardiogram (ECG) delineator based on Wavelet Transform (WT) presented by Li et al. in 1995, a significant research effort has been devoted to the exploitation of this promising method. Its ability to reliably delineate the major waveform components (mono- or bi-phasic P wave, QRS, and mono- or bi-phasic T wave) would make it a suitable candidate for efficient online processing of ambulatory ECG signals. Unfortunately, previous implementations of this method adopt non-linear operators such as root mean square (RMS) or floating point algebra, which are computationally demanding.
  
  
  METHODS
  This paper presents a 32-bit integer, linear algebra advanced approach to online QRS detection and P-QRS-T waves delineation of a single lead ECG signal, based on WT.
  
  
  RESULTS
  The QRS detector performance was validated on the MIT-BIH Arrhythmia Database (sensitivity Se = 99.77%, positive predictive value P+ = 99.86%, on 109010 annotated beats) and on the European ST-T Database (Se = 99.81%, P+ = 99.56%, on 788050 annotated beats). The ECG delineator was validated on the QT Database, showing a mean error between manual and automatic annotation below 1.5 samples for all fiducial points: P-onset, P-peak, P-offset, QRS-onset, QRS-offset, T-peak, T-offset, and a mean standard deviation comparable to other established methods.
  
  
  CONCLUSIONS
  The proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, in spite of a simple structure built on integer linear algebra.
authors: Biomedical Engineering Group, Department of Electronics, Computer Science and Systems (DEIS), University of Bologna, I-40136 Bologna, Italy. luigiyuri.dimarco@unibo.it
authors: Luigi Y
authors: LY
authors: Di Marco
authors: Lorenzo
authors: L
authors: Chiari
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac; D016208:Databases, Factual; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D015716:Electrocardiography, Ambulatory / Q000379:methods*; D006801:Humans; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D058067:Wavelet Analysis