SNOROSALAB: A Method Facilitating the Diagnosis of Sleep Breathing Disorders Before Polysomnography - 26/08/21
Cet article a été publié dans un numéro de la revue, cliquez ici pour y accéder
Abstract |
Objective |
The aim of this study is to develop a new method that will facilitate the diagnosis of sleep breathing disorders (SBD; primary snoring and obstructive sleep apnea syndrome (OSAS)).
Methods |
In this study, we had 22 volunteers, 16 men and 6 women, having the complaint of snoring (Age; 49.2 ± 6.76 and Body Mass Index 42.6 ± 8.16); their diagnoses of OSAS and primary snoring were established with polysomnography (PSG). The number and severity of apnea episodes were compared between the classical method PSG and the new method SNOROSALAB.
Results |
As a result, no statistically significant differences could be found between the two methods (Paired Sample Test: p=0.78; Pearson Correlation Coefficient: ). After “Kolmogorov-Smirnov” analysis, “Mann-Whitney U” test was performed and we demonstrated that there was not any statistical difference between the two methods (Mann-Whitney U value: 224.5; p>0.05). When comparisons were made with Kohen's kappa criteria, the numbers of apnea identified by the two methods did not differ significantly (kappa value: −0.002; p>0.05).
Conclusions |
SNOROSALAB is a simple voice-recording device that does not have any cables attached and it is easy to use. It serves as a screening and diagnostic tool that attempts to detect individuals with suspected snoring and sleep apnea before they enter PSG at their homes.
Le texte complet de cet article est disponible en PDF.Graphical abstract |
Highlights |
• | For people with snoring who are suspected of having sleep breathing disorder. |
• | Before placing the cable and electrode systems (PSG) in the sleep laboratory. |
• | A screening test at home before long sleep lab appointments. |
• | A new method that detects the number of apnea by snoring sound analysis. |
Keywords : Snoring, Signal analysis, Sleep electrophysiology, Diagnosis, OSAS, Feature extraction
Plan
☆ | Conference ACTA PHYSIOLOGICA Publication date 2019/12/1, Vol. 227, Pages 100-100, Publisher WILEY. A Novel Approach that Makes Diagnosing Sleep Breathing Disorders Easier by Analyzing in A Computer Environment the Physiological Features of Sound Tapes Recorded from Snorers. A New Product Diagnosing Sleep Breathing Disorder at Home. National Patent Application Number: 2018/02441 Date: 21.02.2018. Ethical Committee Permission Number: 2018/09-59. |
Bienvenue sur EM-consulte, la référence des professionnels de santé.
L’accès au texte intégral de cet article nécessite un abonnement.
Déjà abonné à cette revue ?