Name
Abstract | ||
|---|---|---|
This paper extends our previous work on automated detection and classification of neonate EEG sleep stages. In [19] we adapted and integrated a range of computational, mathematical and statistical tools for the analysis of neonatal electroencephalogram (EEG) sleep recordings with the aim of facilitating the assessment of neonatal brain maturation and dismaturity by studying the structure and temporal patterns of their sleep. That work relied on algorithms using a single channel of EEG. The present paper builds on our previous work by incorporating a larger selection of EEG channels that capture both the spatial distribution and temporal patterns of EEG during sleep. Using a multivariate analysis approach, we obtain the "optimal" selection of the EEG channels and characteristics that are most suitable for EEG sleep state separation. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.cmpb.2011.08.002 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
previous work,optimal channel selection,multivariate analysis approach,present paper,neonatal brain maturation,temporal pattern,eeg-sleep pattern,eeg channel,automated detection,single channel,larger selection,neonatal electroencephalogram,multivariate analysis | Computer science,Communication channel,Speech recognition,Multivariate analysis,Sleep Stages,Electroencephalography | Journal |
Volume | Issue | ISSN |
106 | 1 | 1872-7565 |
Citations | PageRank | References |
6 | 0.54 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexandra Piryatinska | 1 | 22 | 2.24 |
| Wojbor A Woyczynski | 2 | 31 | 9.85 |
| Mark S Scher | 3 | 20 | 2.54 |
| Kenneth A Loparo | 4 | 162 | 22.22 |