Name
Title | ||
|---|---|---|
Automatic detection of sleep spindles using Teager energy and spectral edge frequency |
Abstract | ||
|---|---|---|
Sleep spindles are the hallmark of N2 stage of sleep. They are transient waveforms observed on sleep electroencephalogram and their identification is required for sleep staging. Due to the large number of sleep spindles appearing on an overnight sleep EEG, automating the detection of sleep spindles would be desirable, not only to save specialist time but also for fully automated sleep staging systems. A simple algorithm for automatic sleep spindle detection is presented in this paper using only one channel of EEG input. This algorithm uses Teager energy and spectral edge frequency to mark sleep spindles and results in a sensitivity of 80% and specificity of about 98%. It is also shown that more than 91% of spindles detected by the algorithm were in N2 and N3 stages combined. |
Year | Venue | Keywords |
|---|---|---|
2013 | 2013 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS) | sleep,electroencephalography,signal detection |
Field | DocType | ISSN |
Sleep electroencephalogram,Sleep spindle,Detection theory,Computer science,Waveform,Speech recognition,Spectral edge frequency,Electroencephalography | Conference | 2163-4025 |
Citations | PageRank | References |
6 | 0.95 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Syed Anas Imtiaz | 1 | 22 | 6.03 |
| siavash saremiyarahmadi | 2 | 6 | 0.95 |
| E Rodriguez-Villegas | 3 | 103 | 19.22 |