Abstract Title

Phonocardiogram Signal Classification using RNN

Author Information

Krysh RajendranFollow

Is this project an undergraduate, graduate, or faculty project?

Graduate

individual

What campus are you from?

Daytona Beach

Authors' Class Standing

Graduate Student

Lead Presenter's Name

Krysh Rajendran

Faculty Mentor Name

Dr Khem Poudel

Abstract

Phonocardiogram(PCG) signals are widely used for screening heart conditions. The goal is to develop a model that can accurately classify PCG signals. Suitable preprocessing(Wavelet Transforms) to denoise signals will be used and then will be used to train a RNN.

Did this research project receive funding support from the Office of Undergraduate Research.

No

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Phonocardiogram Signal Classification using RNN

Phonocardiogram(PCG) signals are widely used for screening heart conditions. The goal is to develop a model that can accurately classify PCG signals. Suitable preprocessing(Wavelet Transforms) to denoise signals will be used and then will be used to train a RNN.