Automatic K-complexes Detection in Sleep EEG Recordings using Likelihood Thresholds

被引：32

作者：

Devuyst, S. ^{[1
]}

Dutoit, T. ^{[1
]}

Stenuit, P. ^{[2
]}

Kerkhofs, M. ^{[2
]}

机构：

[1] Univ Mons, TCTS Lab, B-7000 Mons, Belgium

[2] Montigny le Tilleul, Sleep Lab CHU Vesale, Mons, Belgium

来源：

2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2010年

关键词：

ELECTROENCEPHALOGRAM;

D O I：

10.1109/IEMBS.2010.5626447

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In this paper, we present an automatic method for K-complexes detection based on features extraction and the use of fuzzy thresholds. The validity of our process was examined on the basis of two visual K-complexes scorings performed on 5 excerpts of 30 minutes. Results were investigated through all different sleep stages. The algorithm provides global true positive rates of 61.72% and 60.94%, respectively with scorer 1 and scorer 2. The false positive proportions (compared to the total number of visually scored K-complexes) are of 19.62% and 181.25%, while the false positive rates estimated on a one 1 second resolution are only of 0.53% and 1.53%. These results suggest that our approach is completely suitable since its performances are similar to those of the human scorers.

引用

页码：4658 / 4661

页数：4

共 13 条

[1] FEATURE-BASED DETECTION OF THE K-COMPLEX WAVE IN THE HUMAN ELECTROENCEPHALOGRAM USING NEURAL NETWORKS [J].