Abstract-To investigate obstructive sleep apnea syndrome mechanisms, we developed a device to measure the surface electromyogram (EMG) time latency reflex of the genioglossus muscle stimulated by time and amplitude calibrated negative pharyngeal pressure drops. The reflex signals were found to be disturbed by transient signals that generate false alarms. Thus, to reduce false alarm occurrences we designed an adaptive multiscale method. Continuous wavelet transform (CWT) is widely used in biomedical signal event detection processes. The Berkner transform is an approximation of a CWT that is based on a hierarchical scheme similar to discrete wavelet transform. We used the Berkner transform to build a multiscale detector because it offers the possibility of maxima coefficients linkage that leads to good accuracy in reflex onset localization. As a contribution to this novel approach we used a reconstruction formula to develop an adaptive method for scale range determination in our surface EMG reflex detector. Finally, we characterized our detector in terms of accuracy and robustness, first on synthesized signals and second, on signals acquired on apneic patients and healthy subjects. Preliminary results showed a significant difference (p 0 01) between the two populations regarding the genioglossus muscle mean latency time. These physiological findings may partly explain why the upper airway protective reflex occurring when a negative pressure is applied to the upper airway is ineffective in OSA patients, leading to pharyngeal collapse.Index Terms-Continuous wavelet transform (CWT), sleep apnea syndrome, surface electromyography.

No abstract

Using a simplified model of the upper airways with two independent collapsible elements (nostrils and hypo-pharynx), we calculated the cross-sectional area of these two elements, taking into account pressure drops. We experimentally measured flow and pressure in the fossa and hypo-pharynx in various syndromes. This allowed us to compare the behaviour of the area supplied by our model with the aerodynamic resistance that is often used to analyse upper airway flow limitation events. We showed that nostril and hypo-pharyngeal areas are better correlated than the resistance values and thus concluded that the pressure divided by the square of the flow is a better parameter for analysing flow limitation in upper airways than resistance. Owing to its simplicity, our model is able to supply the area of the collapsible element in real time, which is impossible with more sophisticated models.