Title :
Automatic detection of REM sleep in subjects without atonia
Author :
Kempfner, J. ; Jennum, Poul ; Nikolic, Marija ; Christensen, Julie A. E. ; Sorensen, Helge Bjarup Dissing
Author_Institution :
Dept. of Electr. Eng., Tech. Univ. of Denmark, Lyngby, Denmark
fDate :
Aug. 28 2012-Sept. 1 2012
Abstract :
Idiopathic Rapid-Eye-Movement (REM) sleep Behavior Disorder (iRBD) is a strong early marker of Parkinson´s Disease and is characterized by REM sleep without atonia (RSWA) and increased phasic muscle activity. Current proposed methods for detecting RSWA assume the presence of a manually scored hypnogram. In this study a full automatic REM sleep detector, using the EOG and EEG channels, is proposed. Based on statistical features, combined with subject specific feature scaling and post-processing of the classifier output, it was possible to obtain an mean accuracy of 0.96 with a mean sensititvity and specificity of 0.94 and 0.96 respectively.
Keywords :
electro-oculography; electroencephalography; medical disorders; muscle; sleep; statistical analysis; vision; EEG channels; EOG channels; automatic detection; classifier output; full automatic REM sleep detector; idiopathic rapid-eye-movement sleep behavior disorder; manually scored hypnogram; mean accuracy; parkinsons disease; phasic muscle activity; post-processing; specific feature scaling; statistical features; Band pass filters; Electroencephalography; Electrooculography; Manuals; Medical diagnostic imaging; Muscles; Sleep; Diagnosis, Computer-Assisted; Electroencephalography; Electrooculography; Epilepsy, Generalized; Female; Humans; Male; Middle Aged; Polysomnography; REM Sleep Parasomnias; Reproducibility of Results; Sensitivity and Specificity; Sleep, REM;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6346903
