Open AccessOptimization Audicor for Normal and Abnormal Heart Sounds Characteristic
Author(s) -
Dedi Kurniadi,
Surfa Yondri,
Albar,
Roza Susanti,
David Eka Putra,
Gwo-Jia Jong
Publication year - 2020
Publication title -
international journal of data science
Language(s) - English
Resource type - Journals
ISSN - 2722-2039
DOI - 10.18517/ijods.1.2.99-106.2020
Subject(s) - heart sounds , sound (geography) , feature (linguistics) , noise (video) , fast fourier transform , signal (programming language) , computer science , speech recognition , pattern recognition (psychology) , medicine , artificial intelligence , acoustics , cardiology , physics , linguistics , philosophy , algorithm , image (mathematics) , programming language
Heart Sounds are important things in the human body that can deliver information related to the heart condition. However, a recorded signal such as PCG and ECG that getting through Audicor still contain unexpected components or noise while the recording process happens it makes the result data from Audicor cannot directly use to recognize the condition of the heart. This research presents signal processing and data analysis to suppress the noise of the heart sounds that getting while the process of recording data happens. The cleaned heart sound will be processed in feature extraction by using FFT and PCA that capable to produce the feature both of the normal and abnormal heart sounds. For the normal case, we get the data from some healthy volunteers recorded by using Audicor. While the abnormal heart sound we focus to observe the data that contain Ventricular Septal Defect (VSD) that getting from a partner hospital. As a result, feature both normal and abnormal heart sounds can be separated.