Shailesh Gullipalli
Pronouns: he/him
Research Mentor(s): Sardar Ansari
Research Mentor School/College/Department: Weil Institute for Critical Care Research and Innovation / Medicine
Program:
Authors: Shailesh Gullipalli, Brittany Baur
Session: Session 2: 10:00 am – 10:50 am
Poster: 36
Abstract
For many diseases, it is difficult to diagnose symptoms accurately in a short amount of time. Our project aims to improve the accuracy of predictions for diseases using a combination of features derived from gas chromatography (GC) of a patient’s sweat and Electrocardiograms (ECGs). ECG data will be collected using a Movesense chest strap device from patients who volunteer to take part in this project. From this data, we will look at Heart Rate Variability (HRV), a measure of variation in the intervals between heartbeats. HRV can provide us with information about a patient’s risk for cardiovascular disease and conditions afflicting the autonomic nervous system. In this project, we will annotate heartbeats and noisy portions of the ECG signal. This will lead to clean signals that are appropriate for data analysis, such as the identification of HRV features. We will also be annotating arrhythmias such as premature ventricular contractions (PVCs) and premature atrial contractions (PACs), as these can also impact subsequent HRV analysis. The project will continue to collect data over the next few years, but currently the focus is to create a “gold standard” set of ECG beats. This ECG data, combined with data from a wearable micro-gas chromatography device, will allow us to create models that are predictive of disease.
