CLASSIFIER ENSEMBLE FOR DETECTION OF ABNORMAL HEART SOUNDS

Various embodiments of the inventions of the present disclosure provide a combination of feature-based approach and deep learning approach for distinguishing between normal heart sounds and abnormal heart sounds. A feature-based classifier (60) is applied to a phonocardiogram (PCG) signal to obtain...

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Bibliographic Details
Main Authors CONROY, Bryan, PARVANEH, Saman, POTES BLANDON, Cristhian, Mauricio, RAHMAN, Asif
Format Patent
LanguageEnglish
French
German
Published 17.07.2019
Subjects
DIAGNOSIS
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
MEDICAL OR VETERINARY SCIENCE
SURGERY
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Summary:Various embodiments of the inventions of the present disclosure provide a combination of feature-based approach and deep learning approach for distinguishing between normal heart sounds and abnormal heart sounds. A feature-based classifier (60) is applied to a phonocardiogram (PCG) signal to obtain a feature-based abnormality classification of the heart sounds represented by the PCG signal and a deep learning classifier (70) is also applied to the PCG signal to obtain a deep learning abnormality classification of the heart sounds represented by the PCG signal. A final decision analyzer (80) is applied to the feature-based abnormality classification and the deep learning abnormality classification of the heart sounds represented by the PCG signal to determine a final abnormality classification decision of the PCG signal.
Bibliography:Application Number: EP20170764564