Authors: Ramin Soltanzadeh Zahra Moussavi
Publish Date: 2015/03/05
Volume: 43, Issue: 10, Pages: 2530-2537
Abstract
Sleep stage detection is needed in many sleep studies and clinical assessments Generally sleep stages are identified using spectral analysis of electrocephologram EEG and electrooculogram EOG signals This study for the first time has investigated the feasibility of detecting sleep stages using tracheal breathing sounds and whether the change of breathing sounds due to sleeping stage differs at different periods of sleeping time the motivation was seeking an alternative technique for sleep stage identification The tracheal breathing sounds of 12 individuals who were referred for full overnight polysomnography PSG assessment were recorded using a microphone placed over the suprasternal notch and analyzed using higher order statistical analysis Five noiseandsnorefree breathing cycles from wakefulness REM and Stage II of sleep were selected from each subject for analysis Data of the REM and Stage II were selected from beginning middle and close to end of sleeping time Hurst exponent was calculated from the bispectra of the inspiratory sounds of each subject at each sleeping stage in different periods of sleeping time The participants’ sleep stage were determined by sleep lab technologists during the PSG study using EEG and EOG signals The results show separate and nonoverlapping clusters for wakefulness REM and Stage II for each subject Thus using a simple linear classifier we were able to classify REM and Stage II of each subject with 100 accuracy In addition the results show that the same pattern existed as long as the REM and Stage II segments were close less than 3 h to each other in terms of time
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