Investigating Genioglossal Muscle Activity in Obstructive Sleep Apnea Patients by Polysomnography

Abstract

Obstructive Sleep Apnea is a prevalent sleep disorder characterized by repeated interruptions in breathing during sleep, often linked to reduced muscle tone in the airway musculature. Among these muscles, the genioglossal muscle plays a critical role in maintaining airway patency. This thesis aims to investigate the genioglossal muscle's activity patterns in OSA patients by analyzing chin electromyography signals during sleep, with a specific focus on arousal events. The objectives include characterizing chin EMG activity changes across arousal epochs (before, during, after), with each epoch consisting of 30 seconds, identifying key EMG features that differentiate between arousal states, exploring the physiological implications of these features on muscle activity, and highlighting the potential of chin EMG in sleep disorder diagnostics. 42 EMG features were extracted from the chin EMG and suggested possible genioglossal muscle activity at different arousal epochs. This feature set facilitated an analysis of muscle activity patterns associated with various sleep disturbances. Our methodology emphasized the use of the Kruskal-Wallis test to address the challenges posed by non-normalized EMG data, ensuring a robust feature selection process. The findings of this study underscore the significance of Kurtosis as a distinguishing feature, particularly for total and respiratory arousals, with a compelling p-value of less than 0.01 for total arousals. This evidence positions Kurtosis as a potential biomarker for detecting genioglossal muscle activity changes in response to arousal events, offering new avenues for understanding OSA and related sleep disorders. This research provides novel insights into the genioglossal muscle's behavior during sleep, contributing to the broader domain of sleep research and highlighting the value of chin EMG analysis.

Date of Award	17 Jul 2024
Original language	American English
Supervisor	AHSAN Khandoker (Supervisor)