Title :
Variations of snoring properties with macro sleep stages in a population of Obstructive Sleep Apnea patients
Author :
Akhter, Shameem ; Abeyratne, U.R. ; Swarnkar, Vinayak
Author_Institution :
Sch. of ITEE, Univ. of Queensland, Brisbane, QLD, Australia
Abstract :
Snoring is common in Obstructive Sleep Apnea (OSA) patients. Snoring originates from the vibration of soft tissues in the upper airways (UA). Frequent UA collapse in OSA patients leads to sleep disturbances and arousal. In a routine sleep diagnostic procedure, sleep is broadly divided into rapid eye movement (REM), non-REM (NREM) states. These Macro-Sleep States (MSS) are known to be involved with different neuromuscular activities. These differences should influence the UA mechanics in OSA patients as well as the snoring sound (SS). In this paper, we propose a logistic regression model to investigate whether the properties of SS from OSA patients can be separated into REM/NREM group. Analyzing mathematical features of more than 500 SS events from 7 OSA patients, the model achieved 76% (± 0.10) sensitivity and 75% (± 0.10) specificity in categorizing REM and NREM related snores. These results indicate that snoring is affected by REM/NREM states and proposed method has potential in differentiating MSS.
Keywords :
diseases; muscle; neurophysiology; patient diagnosis; regression analysis; sleep; OSA patients; REM-NREM states; logistic regression model; macrosleep stages; mathematical features; neuromuscular activity; nonREM states; obstructive sleep apnea patient population; rapid eye movement states; sleep diagnostic procedure; sleep disturbance; snoring properties; snoring sound; soft tissue vibration; upper airway mechanics; Microphones; Muscles; Sensitivity; Sleep apnea; Testing; Training;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location :
Osaka
DOI :
10.1109/EMBC.2013.6609751