Author ORCID Identifier

https://orcid.org/0000-0002-8351-1660

Date Available

8-5-2022

Year of Publication

2022

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Engineering

Department/School/Program

Biomedical Engineering

First Advisor

Dr. Abhijit Patwardhan

Abstract

We investigated if listening to songs changes breathing pattern which changes autonomic responses such as heart rate (HR) and heart rate variability (HRV) or change in breathing pattern is a byproduct of listening to songs or change in breathing pattern as well as listening to songs causes changes in autonomic responses. Seven subjects (4 males and 3 females) participated in a pilot study where they listened to two types of songs and used a custom developed biofeedback program to control their breathing pattern to match the one recorded during listening to the songs.

Coherencies between EEG, breathing pattern and RR intervals (RRI) were calculated to study the interaction with neural responses. Trends in HRV varied only during listening to songs, suggesting that autonomic response was affected by listening to songs irrespective of control of breathing. Effective coherence during songs while spontaneously breathing was more than during silence and during control of breathing. These results, although preliminary, suggest that listening to songs as well as change in breathing patterns changes the autonomic response but the effect of listening to songs may surpass the effect of changes in breathing.

We explored feasibility of using non-contact measurements of HR and breathing rate (BR) by using recently developed Facemesh and other methods for tracking regions of interests from videos of faces of subjects. Performance was better for BR than HR, and over currently used methods. However, refinement of the approach would be needed to get the precision required for detecting subtle changes.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2022.286

Funding Information

This study was supported by the National Science Foundation grant (EPSCoR RII Track-2, 1539068) from 2016 to 2021

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