Abstract
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.
Original language | English |
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Journal | I E E E Engineering in Medicine and Biology Society. Conference Proceedings |
Volume | 2014 |
Pages (from-to) | 5450-5453 |
Number of pages | 4 |
ISSN | 2375-7477 |
DOIs | |
Publication status | Published - 2 Nov 2014 |