Automatic AASM sleep staging

Stages each 30-second epoch using a pre-trained LightGBM model originally developed for YASA (Vallat & Walker, 2021) and shipped as a cross-language serialised model in inst/models/yasa_staging.txt. Features are computed in R to match the Python feature extraction pipeline exactly; bit-exact parity is validated in the package test suite.

Usage

stage_epochs(
  psg,
  eeg_channel = NULL,
  eog_channel = NULL,
  emg_channel = NULL,
  artefacts = NULL,
  model_path = system.file("models", "yasa_staging.txt", package = "mrpheus")
)

Arguments

psg

An mrpheus_psg object from prepare_psg().

eeg_channel

Character. Central EEG channel (e.g. "EEG Fpz-Cz"). If NULL (default), the first non-bad EEG channel is used.

eog_channel

Character or NULL. EOG channel. If NULL (default), the first non-bad EOG channel is used (EOG features are omitted if none found).

emg_channel

Character or NULL. Chin EMG channel. If NULL (default), the first non-bad EMG channel is used (EMG features are omitted if none found).

artefacts

Tibble or NULL. Output of detect_artifacts(). Artefact epochs are assigned NA stage and excluded from the model. If NULL, all epochs are staged.

model_path

Character. Path to the serialised LightGBM model. Defaults to the bundled model at system.file("models/yasa_staging.txt", package = "mrpheus").

Value

A tibble with one row per epoch:

epoch

Integer.

stage

Character. AASM stage: W, N1, N2, N3, REM, or NA (artefact).

prob_W, prob_N1, prob_N2, prob_N3, prob_REM

Numeric. Posterior class probabilities from the LightGBM model.

Details

Stages returned follow standard AASM nomenclature: W (wake), N1, N2, N3, REM.

References

Vallat, R., & Walker, M. P. (2021). An open-source, high-performance tool for automated sleep staging. eLife, 10, e70092. doi:10.7554/eLife.70092

See also

export_hypnogram()