Automatic sleep staging: A computer assisted approach for optimal combination of features and polysomnographic channels

作者：

Highlights：

• A subject-independent automatic sleep staging method with application in sleep–wake detection and in multiclass sleep staging.

• An extensive dataset with 40 polysomnographic (PSG) recording.

• A time–frequency based feature extraction method using maximum overlap discrete wavelet transform (MODWT).

• A two-step feature selector to find the most discriminative features.

• The best combinations of the PSG channels in sleep–wake detection and in multiclass sleep staging.

摘要

•A subject-independent automatic sleep staging method with application in sleep–wake detection and in multiclass sleep staging.•An extensive dataset with 40 polysomnographic (PSG) recording.•A time–frequency based feature extraction method using maximum overlap discrete wavelet transform (MODWT).•A two-step feature selector to find the most discriminative features.•The best combinations of the PSG channels in sleep–wake detection and in multiclass sleep staging.

论文关键词：Automatic sleep staging,The maximum overlap discrete wavelet transform,Polysomnographic signals,Features selection,Sleep dataset

论文评审过程：Available online 25 June 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.06.023