Conference paper · Journal article
Detection of K-complexes based on the wavelet transform
Sleep scoring needs computational assistance to reduce execution time and to assure high quality. In this pilot study a semi-automatic K-Complex detection algorithm was developed using wavelet transformation to identify pseudo-K-Complexes and various feature thresholds to reject false positives. The algorithm was trained and tested on sleep EEG from two databases to enhance its general applicability.
When testing on data from subjects from the DREAMS© database, a mean true positive rate of 74 % and a positive predictive value of 65 % were achieved. After adjusting a few thresholds to adapt to the second database, the Danish Center for Sleep Medicine, a similar performance was achieved. The algorithm performs at the level of the State of the Art and surpasses the inter-rater agreement rate.
Language: | English |
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Publisher: | IEEE |
Year: | 2014 |
Pages: | 5450-5453 |
Proceedings: | 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
ISBN: | 1424479274 , 1424479290 , 9781424479276 and 9781424479290 |
ISSN: | 1557170x , 23757477 and 26940604 |
Types: | Conference paper and Journal article |
DOI: | 10.1109/EMBC.2014.6944859 |
ORCIDs: | 0000-0001-6986-5254 , Hansen, Rie B. , Christensen, Julie Anja Engelhard and Sørensen, Helge Bjarup Dissing |