Research Symposium

22nd annual Undergraduate Research Symposium

Astrid Daugherty Poster Session 1: 9:00-9:45/Poster #19


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BIO


My name is Astrid Daugherty and I'm 20 years old. I grew up in the Republic of Panama, and transferred from FSU Republic of Panama to Tallahassee in Summer 2021. My major is Biomedical Engineering and I'm considering either going to Graduate School or applying to Medical School. I'm a math tutor at the Strozier Library and at The Academic Center for Excellence (ACE). I also used to tutor at the Math Learning Center of FSU Panama. I've been tutoring since Spring 2020. Another thing I like to invest my time in is doing research. I got an assistantship through Undergraduate Research Opportunity Program (UROP), and now I'm helping in training artificial intelligence into classifying human heartbeats into "normal" or "abnormal" as a diagnosis tool for heart diseases. The training also involves the generation of synthetic data. My favorite things are cats, plants, and tea. I enjoy spending time with friends, exercise, play the piano, and just have a good time.

Training Artificial Intelligence Using Synthetic Data and a Convolutional Neural Network for Sound Classification of a Heartbeat

Authors: Astrid Daugherty, Jonathan Adams
Student Major: Biomedical Engineering
Mentor: Jonathan Adams
Mentor's Department: Audio
Mentor's College: College of Communication and Information
Co-Presenters:

Abstract


The diagnosis of a heart disease is not as easy as hearing a human heart through a stethoscope. Sometimes it requires the thorough study of a PCG (phonocardiograms), or ECG (electrocardiogram), which sometimes might not be as efficient and straightforward as one wishes it should. Doctors train their whole lives to be able to identify and treat the emergence of one. Technology now aims to help these hardworking doctors do the hard work for them, so that the diagnosis is efficient and accurate.

Keywords: Artificial Intelligence, Synthetic Data, Neural Networks, Heartbeats