Wendt, Sabrina Lyngbye3; Christensen, Julie A. E.1; Kempfner, Jacob1; Leonthin, Helle L.4; Jennum, Poul5; Sorensen, Helge B. D.6
1 Department of Electrical Engineering, Technical University of Denmark2 Biomedical Engineering, Department of Electrical Engineering, Technical University of Denmark3 Department of Applied Mathematics and Computer Science, Technical University of Denmark4 Copenhagen University Hospital5 University of Copenhagen6 Copenhagen Center for Health Technology, Center, Technical University of Denmark
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Many of the automatic sleep spindle detectors currently used to analyze sleep EEG are either validated on young subjects or not validated thoroughly. The purpose of this study is to develop and validate a fast and reliable sleep spindle detector with high performance in middle aged subjects. An automatic sleep spindle detector using a bandpass filtering approach and a time varying threshold was developed. The validation was done on sleep epochs from EEG recordings with manually scored sleep spindles from 13 healthy subjects with a mean age of 57.9 ± 9.7 years. The sleep spindle detector reached a mean sensitivity of 84.6 % and a mean specificity of 95.3 %. The sleep spindle detector can be used to obtain measures of spindle count and density together with quantitative measures such as the mean spindle frequency, mean spindle amplitude, and mean spindle duration.
Ieee Engineering in Medicine and Biology Society Conference Proceedings, 2012, Vol 2012, p. 4250-4253
Evaluation Studies; Journal Article; Validation Studies; automatic sleep spindle detectors; bandpass filtering approach; biomedical equipment; EEG recordings; electroencephalography; fast sleep spindle detector; filtering theory; manually scored sleep spindles; mean spindle amplitude; mean spindle duration; mean spindle frequency; medical signal detection; medical signal processing; middle aged subjects; neurophysiology; quantitative measurement; reliable sleep spindle detector; sleep; sleep EEG; sleep epochs; time varying threshold
Main Research Area:
34th Annual International Conference of the IEEE EMBS, 2012