Detection of K-complexes based on the wavelet transform

TY - JOUR

T1 - Detection of K-complexes based on the wavelet transform

AU - Krohne, Laerke K

AU - Hansen, Rie B

AU - Christensen, Julie A E

AU - Sorensen, Helge B D

AU - Jennum, Poul

PY - 2014/11/2

Y1 - 2014/11/2

N2 - 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.

AB - 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.

U2 - 10.1109/embc.2014.6944859

DO - 10.1109/embc.2014.6944859

M3 - Journal article

C2 - 25571227

SN - 0589-1019

VL - 2014

SP - 5450

EP - 5453

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

ER -