Early Automatic Detection of Parkinson's Disease Based on Sleep Recordings
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Early Automatic Detection of Parkinson's Disease Based on Sleep Recordings. / Kempfner, Jacob; Sorensen, Helge B D; Nikolic, Miki; Jennum, Poul.
In: Journal of Clinical Neurophysiology, Vol. 31, No. 5, 2014, p. 409-415.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Early Automatic Detection of Parkinson's Disease Based on Sleep Recordings
AU - Kempfner, Jacob
AU - Sorensen, Helge B D
AU - Nikolic, Miki
AU - Jennum, Poul
PY - 2014
Y1 - 2014
N2 - SUMMARY: Idiopathic rapid-eye-movement (REM) sleep behavior disorder (iRBD) is most likely the earliest sign of Parkinson's Disease (PD) and is characterized by REM sleep without atonia (RSWA) and consequently increased muscle activity. However, some muscle twitching in normal subjects occurs during REM sleep.PURPOSE: There are no generally accepted methods for evaluation of this activity and a normal range has not been established. Consequently, there is a need for objective criteria.METHOD: In this study we propose a full-automatic method for detection of RSWA. REM sleep identification was based on the electroencephalography and electrooculography channels, while the abnormal high muscle activity was detected from the electromyography channels, in this case the submentalis combined with left and right anterior tibialis. RSWA was identified by considering it an outlier problem, in which the number of outliers during REM sleep was used as a quantitative measure of muscle activity.RESULTS: The proposed method was able to automatically separate all iRBD test subjects from healthy elderly controls and subjects with periodic limb movement disorder.CONCLUSION: The proposed work is considered a potential automatic method for early detection of PD.
AB - SUMMARY: Idiopathic rapid-eye-movement (REM) sleep behavior disorder (iRBD) is most likely the earliest sign of Parkinson's Disease (PD) and is characterized by REM sleep without atonia (RSWA) and consequently increased muscle activity. However, some muscle twitching in normal subjects occurs during REM sleep.PURPOSE: There are no generally accepted methods for evaluation of this activity and a normal range has not been established. Consequently, there is a need for objective criteria.METHOD: In this study we propose a full-automatic method for detection of RSWA. REM sleep identification was based on the electroencephalography and electrooculography channels, while the abnormal high muscle activity was detected from the electromyography channels, in this case the submentalis combined with left and right anterior tibialis. RSWA was identified by considering it an outlier problem, in which the number of outliers during REM sleep was used as a quantitative measure of muscle activity.RESULTS: The proposed method was able to automatically separate all iRBD test subjects from healthy elderly controls and subjects with periodic limb movement disorder.CONCLUSION: The proposed work is considered a potential automatic method for early detection of PD.
U2 - 10.1097/WNP.0000000000000065
DO - 10.1097/WNP.0000000000000065
M3 - Journal article
C2 - 25271677
VL - 31
SP - 409
EP - 415
JO - Journal of Clinical Neurophysiology
JF - Journal of Clinical Neurophysiology
SN - 0736-0258
IS - 5
ER -
ID: 135274182