title: Detection of Heart Sounds in Children with and without Pulmonary Arterial Hypertension--Daubechies Wavelets Approach.
abstract: BACKGROUND
  Automatic detection of the 1st (S1) and 2nd (S2) heart sounds is difficult, and existing algorithms are imprecise. We sought to develop a wavelet-based algorithm for the detection of S1 and S2 in children with and without pulmonary arterial hypertension (PAH).
  
  
  METHODS
  Heart sounds were recorded at the second left intercostal space and the cardiac apex with a digital stethoscope simultaneously with pulmonary arterial pressure (PAP). We developed a Daubechies wavelet algorithm for the automatic detection of S1 and S2 using the wavelet coefficient 'D6' based on power spectral analysis. We compared our algorithm with four other Daubechies wavelet-based algorithms published by Liang, Kumar, Wang, and Zhong. We annotated S1 and S2 from an audiovisual examination of the phonocardiographic tracing by two trained cardiologists and the observation that in all subjects systole was shorter than diastole.
  
  
  RESULTS
  We studied 22 subjects (9 males and 13 females, median age 6 years, range 0.25-19). Eleven subjects had a mean PAP < 25 mmHg. Eleven subjects had PAH with a mean PAP ≥ 25 mmHg. All subjects had a pulmonary artery wedge pressure ≤ 15 mmHg. The sensitivity (SE) and positive predictivity (+P) of our algorithm were 70% and 68%, respectively. In comparison, the SE and +P of Liang were 59% and 42%, Kumar 19% and 12%, Wang 50% and 45%, and Zhong 43% and 53%, respectively. Our algorithm demonstrated robustness and outperformed the other methods up to a signal-to-noise ratio (SNR) of 10 dB. For all algorithms, detection errors arose from low-amplitude peaks, fast heart rates, low signal-to-noise ratio, and fixed thresholds.
  
  
  CONCLUSIONS
  Our algorithm for the detection of S1 and S2 improves the performance of existing Daubechies-based algorithms and justifies the use of the wavelet coefficient 'D6' through power spectral analysis. Also, the robustness despite ambient noise may improve real world clinical performance.
authors.affiliation: Department of Mathematics and Computing Science, University of Alberta, Edmonton, Canada.
authors.forename: Mohamed
authors.initials: M
authors.lastname: Elgendi
authors.affiliation: Pediatric Pulmonary Hypertension Service and Cardiac Critical Care, Stollery children's Hospital, Mazankowski Heart Institute, University of Alberta, Edmonton, Canada.
authors.forename: Shine
authors.initials: S
authors.lastname: Kumar
authors.affiliation: Pediatric Pulmonary Hypertension Service and Cardiac Critical Care, Stollery children's Hospital, Mazankowski Heart Institute, University of Alberta, Edmonton, Canada.
authors.forename: Long
authors.initials: L
authors.lastname: Guo
authors.affiliation: Department of Pediatrics, Stollery Children's Hospital, University of Alberta, Edmonton, Canada.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Rutledge
authors.affiliation: Department of Pediatrics, Stollery Children's Hospital, University of Alberta, Edmonton, Canada.
authors.forename: James Y
authors.initials: JY
authors.lastname: Coe
authors.affiliation: Department of Biomedical Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.
authors.forename: Roger
authors.initials: R
authors.lastname: Zemp
authors.affiliation: Department of Mathematics and Computing Science, University of Alberta, Edmonton, Canada.
authors.forename: Dale
authors.initials: D
authors.lastname: Schuurmans
authors.affiliation: Pediatric Pulmonary Hypertension Service and Cardiac Critical Care, Stollery children's Hospital, Mazankowski Heart Institute, University of Alberta, Edmonton, Canada.|Department of Pediatrics, Stollery Children's Hospital, University of Alberta, Edmonton, Canada.
authors.forename: Ian
authors.initials: I
authors.lastname: Adatia
mesh_terms: D000293:Adolescent; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D005260:Female; D006347:Heart Sounds; D006801:Humans; D006976:Hypertension, Pulmonary / Q000175:diagnosis / Q000503:physiopathology*; D007223:Infant; D008297:Male; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D019023:Stethoscopes; D058067:Wavelet Analysis; D055815:Young Adult