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Computer-Based Detection and Analysis of Heart Sound and Murmur
- Source :
- Annals of Biomedical Engineering. 33:937-942
- Publication Year :
- 2005
- Publisher :
- Springer Science and Business Media LLC, 2005.
-
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.
- Subjects :
- Male
medicine.medical_specialty
Adolescent
Acoustics
Biomedical Engineering
Diastole
Internal medicine
otorhinolaryngologic diseases
Humans
Medicine
Child
Phonocardiogram
Heart Murmurs
medicine.diagnostic_test
Cardiac cycle
business.industry
Sound detection
Phonocardiography
Infant
Signal Processing, Computer-Assisted
Sound intensity
Echocardiography
Child, Preschool
Heart sounds
cardiovascular system
Cardiology
Heart murmur
Female
medicine.symptom
business
Electrocardiography
Algorithms
Subjects
Details
- ISSN :
- 15739686 and 00906964
- Volume :
- 33
- Database :
- OpenAIRE
- Journal :
- Annals of Biomedical Engineering
- Accession number :
- edsair.doi.dedup.....8e123affa51d91522123475ea5ba2cdd
- Full Text :
- https://doi.org/10.1007/s10439-005-4053-3