Sleep-Disordered Breathing Clinical Trial
The diagnosis and treatment of sleep disordered breathing have come to the forefront of
clinical medicine following recognition of the high prevalence and associated morbidity of
sleep apnea. The effects on quality of life as well as societal costs have been well
documented. The NYU Sleep Research Laboratory has spent the last several years working on
the problem of improving the diagnosis of mild sleep disordered breathing which manifests as
the upper airway resistance syndrome. Our approach has been to develop a non-invasive
technique to detect increased upper airway resistance directly from analysis of the airflow
signal. A characteristic intermittent change of the inspiratory flow contour, which is
indicative of the occurrence of flow limitation, correlates well with increased airway
resistance.
Currently all respiratory events are identified manually and totaled. This is time consuming
and subject to variability. The objective of the present project is to improve upon the
manual approach by implementing an artificially intelligent system for the identification
and quantification of sleep disordered breathing based solely on non-invasive
cardiopulmonary signals collected during a routine sleep study. The utility of other
reported indices of sleep disordered breathing obtained during a sleep study will be
evaluated.
Successful development of an automated system that can identify and classify upper airway
resistance events will simplify, standardize and improve the diagnosis of sleep disordered
breathing, and greatly facilitate research and clinical work in this area. Using a
physiological based determination of disease should allow better assessment of treatment
responses in mild disease.
n/a
Primary Purpose: Diagnostic
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