Apnea Detection by Acoustical Means

In this paper a new non-invasive method for apnea detection is proposed. Eight healthy subjects participated in this study. They were instructed to breathe very shallow with different periods of breath hold to simulate sleep apnea. Following our previous study in successful use of entropy for flow estimation, in this study the Otsu threshold was used to classify the calculated entropy into two classes of breathing and apnea. The results show that the method is capable of detecting the apnea periods even when the subjects breathe at very shallow flow rates. The overall lag and duration errors between the estimated and actual apnea periods were found to be 0.207plusmn0.062 and 0.289plusmn0.258 s, respectively. The results are encouraging for the use of the proposed method as a fast, easy and promising tool for apnea detection