| Literature DB >> 26697170 |
Mohamed Elgendi1, Prashant Bobhate2, Shreepal Jain2, Long Guo2, Shine Kumar2, Jennifer Rutledge3, Yashu Coe3, Roger Zemp4, Dale Schuurmans5, Ian Adatia3.
Abstract
We hypothesized that vibrations created by the pulmonary circulation would create sound like the vocal cords during speech and that subjects with pulmonary artery hypertension (PAH) might have a unique sound signature. We recorded heart sounds at the cardiac apex and the second left intercostal space (2LICS), using a digital stethoscope, from 27 subjects (12 males) with a median age of 7 years (range: 3 months-19 years) undergoing simultaneous cardiac catheterization. Thirteen subjects had mean pulmonary artery pressure (mPAp) < 25 mmHg (range: 8-24 mmHg). Fourteen subjects had mPAp ≥ 25 mmHg (range: 25-97 mmHg). We extracted the relative power of the frequency band, the entropy, and the energy of the sinusoid formants from the heart sounds. We applied linear discriminant analysis with leave-one-out cross validation to differentiate children with and without PAH. The significance of the results was determined with a t test and a rank-sum test. The entropy of the first sinusoid formant contained within an optimized window length of 2 seconds of the heart sounds recorded at the 2LICS was significantly lower in subjects with mPAp ≥ 25 mmHg relative to subjects with mPAp < 25 mmHg, with a sensitivity of 93% and specificity of 92%. The reduced entropy of the first sinusoid formant of the heart sounds in children with PAH suggests the existence of an organized pattern. The analysis of this pattern revealed a unique sound signature, which could be applied to a noninvasive method to diagnose PAH.Entities:
Keywords: auscultation; congenital heart disease; language recognition; machine learning; pulmonary hypertension
Year: 2015 PMID: 26697170 PMCID: PMC4671737 DOI: 10.1086/683694
Source DB: PubMed Journal: Pulm Circ ISSN: 2045-8932 Impact factor: 3.017