Evaluation of an automated pipeline for large-scale EEG spectral analysis: the National Sleep Research Resource.

ABSTRACT:

Study objectives

We present an automated sleep electroencephalogram (EEG) spectral analysis pipeline that includes an automated artifact detection step, and we test the hypothesis that spectral power density estimates computed with this pipeline are comparable to those computed with a commercial method preceded by visual artifact detection by a sleep expert (standard approach).

Methods

EEG data were analyzed from the C3-A2 lead in a sample of polysomnograms from 161 older women participants in a community-based cohort study. We calculated the sensitivity, specificity, accuracy, and Cohen's kappa measures from epoch-by-epoch comparisons of automated to visual-based artifact detection results; then we computed the average EEG spectral power densities in six commonly used EEG f

SUBMITTER: Mariani S 

PROVIDER: S-EPMC5976521 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature