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Computer-based detection and analysis of heart sound and murmur.
El-Segaier, M; Lilja, O; Lukkarinen, S; Sörnmo, L; Sepponen, R; Pesonen, E.
Affiliation
  • El-Segaier M; Department of Paediatrics, Division of Paediatric Cardiology, Lund University Hospital, Sweden. milad.el-segaier@skane.se
Ann Biomed Eng ; 33(7): 937-42, 2005 Jul.
Article in En | MEDLINE | ID: mdl-16060534
ABSTRACT
To develop a digital algorithm that detects first and second heart sounds, defines the systole and diastole, and characterises the systolic murmur. Heart sounds were recorded in 300 children with a cardiac murmur, using an electronic stethoscope. A Digital algorithm was developed for detection of first and second heart sounds. R-waves and T-waves in the electrocardiography were used as references for detection. The sound signal analysis was carried out using the short-time Fourier transform. The first heart sound detection rate, with reference to the R-wave, was 100% within 0.05-0.2R-R interval. The second heart sound detection rate between the end of the T-wave and the 0.6R-R interval was 97%. The systolic and diastolic phases of the cardiac cycle could be identified. Because of the overlap between heart sounds and murmur a systolic segment between the first and second heart sounds (20-70%) was selected for murmur analysis. The maximum intensity of the systolic murmur, its average frequency, and the mean spectral power were quantified. The frequency at the point with the highest sound intensity in the spectrum and its time from the first heart sound, the highest frequency, and frequency range were also determined. This method will serve as the foundation for computer-based detection of heart sounds and the characterisation of cardiac murmurs.
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Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Signal Processing, Computer-Assisted / Heart Murmurs Type of study: Diagnostic_studies Limits: Adolescent / Child / Child, preschool / Female / Humans / Infant / Male Language: En Journal: Ann Biomed Eng Year: 2005 Document type: Article Affiliation country:
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Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Signal Processing, Computer-Assisted / Heart Murmurs Type of study: Diagnostic_studies Limits: Adolescent / Child / Child, preschool / Female / Humans / Infant / Male Language: En Journal: Ann Biomed Eng Year: 2005 Document type: Article Affiliation country:
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