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Detection of K-complexes based on the wavelet transform.
https://arctichealth.org/en/permalink/ahliterature267577
Source
Conf Proc IEEE Eng Med Biol Soc. 2014;2014:5450-3
Publication Type
Article
Date
2014
More detail
Author
Laerke K Krohne
Rie B Hansen
Julie A E Christensen
Helge B D Sorensen
Poul Jennum
Source
Conf Proc IEEE Eng Med Biol Soc. 2014;2014:5450-3
Date
2014
Language
English
Publication Type
Article
Keywords
Adult
Aged
Algorithms
Automation
Databases, Factual
Denmark
Electroencephalography
Female
Humans
Male
Middle Aged
Pilot Projects
Predictive value of tests
Reproducibility of Results
Signal Processing, Computer-Assisted
Sleep
Time Factors
Wavelet Analysis
Young Adult
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. 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.
PubMed ID
25571227
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