| dc.description.abstract | The primary focus of this review article is to
investigate acoustic analysis techniques for detecting
obstructive sleep apnea (OSA). OSA causes the upper
airway to collapse partially or entirely during sleep, which
reduces oxygen saturation. The existing diagnostic
techniques for obstructive sleep apnea, such as
polysomnography, are hindered by the challenges related to
their cost, invasiveness, and limited accessibility.
Alternative non-invasive and economical diagnostic
methods are therefore required. The purpose of this review
study is to analyse the strengths and limitations of the
current acoustic analysis techniques as more accessible,
non-invasive, and cost-effective approaches to detect OSA.
Acoustic analysis, which examines the acoustic features of
speech, snoring, and breathing, has the potential to serve as
a diagnostic method for OSA. This study thoroughly
examines the possibility of snoring and speech acoustic
traits as diagnostic indications for obstructive sleep apnea,
using both automated classification methodologies and
acoustic analytic tools (MDVP and Praat). By analysing the
existing research outcomes, this article offers a
comprehensive overview of the advancements in acoustic
analysis for OSA detection. Further research is needed in
speech and OSA analysis, considering clinical factors and
acoustic properties to establish a comprehensive
understanding. | en_US |
