DocumentCode
2417562
Title
Unravelling unique qualitative and quantitative characteristics of the surface submentalis EMG in OSA polysomnograms
Author
Daulatzai, Mak ; Karmakar, Chandan ; Khan, Neela ; Khandoker, Ahsan ; Palaniswami, Marimuthu
Author_Institution
Dept. of EEE, Sleep Disorders Group, Univ. of Melbourne, Melbourne, VIC, Australia
fYear
2010
fDate
7-10 Dec. 2010
Firstpage
309
Lastpage
314
Abstract
The functional integrity of genioglossus and suprahyoid submentalis muscles plays an important role in upper airway patency. A combination of inadequate genioglossal function and UA associated anatomy and physiology underlies obstructive sleep apnoea (OSA). The gold standard for diagnosing OSA is polysomnography that provides important physiological information. Although nocturnal laryngospasm, epilepsy, or parasomnias may be missed in a one-night recording, however, surface submental EMG (sSMEMG) is invariably present in every polysomnogram. This study has assessed the polysomnographic sSMEMG, both qualitatively and quantitatively, during hypopneas in controls (AHI 5 and 10) and OSA patients with 40+ AHI. All analysed sSMEMG signals sampled at 160 HZ were digitally band-pass filtered at 10-100 HZ (notch filter at 50 HZ) for quantitation. The standard median filter with window length-9 subtracted the ECG template and eliminated the artefacts. Unlike controls, the OSA patients showed a predominantly phasic sSMEMG pattern, both qualitatively and quantitatively. This is ascribed to transformation of aerobic muscle fibers to phasic variety owing to prolonged exposure to intermittent hypoxia. We emphasize that unravelling hidden information in sSMEMG signals can be invaluable clinically.
Keywords
band-pass filters; cellular biophysics; electromyography; medical disorders; medical signal processing; neurophysiology; patient diagnosis; sleep; aerobic muscle fibers; digital band-pass filtering; frequency 10 Hz to 100 Hz; frequency 160 Hz; genioglossus; intermittent hypoxia; obstructive sleep apnoea; patient diagnosis; polysomnography; suprahyoid submentalis muscle; surface submentalis EMG signal; Electrocardiography; Electroencephalography; Electromyography; Entropy; Muscles; Optical fiber sensors; Sleep;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2010 Sixth International Conference on
Conference_Location
Brisbane, QLD
Print_ISBN
978-1-4244-7174-4
Type
conf
DOI
10.1109/ISSNIP.2010.5706780
Filename
5706780
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