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Calibrate Artifact Subspace Reconstruction (ASR)

Source: R/asr.R
asrCalibrate.Rd

Learns the clean-baseline channel covariance and the per-component RMS thresholds that asrProcess uses to detect and reconstruct artifact subspaces (Mullen et al., 2015). Calibration data should be a relatively clean segment; supply calib_window to restrict it.

Usage

asrCalibrate(
  x,
  cutoff = 20,
  calib_window = NULL,
  window_len = 0.5,
  assay_name = NULL
)

Arguments

x

A PhysioExperiment object with a 2D (time x channels) assay.

cutoff

Rejection cutoff in robust standard deviations; a principal direction whose window RMS exceeds median + cutoff * MAD of the calibration distribution is treated as artifact (default: 20). Inf makes asrProcess an identity.

calib_window

Optional numeric c(start_sec, end_sec) selecting the calibration segment. If NULL (default) the whole signal is used.

window_len

Sliding-window length in seconds (default: 0.5).

assay_name

Input assay (default: defaultAssay(x)).

Value

An object of class "asr_calibration": a list with the clean covariance M, its square-root mixing matrix, the threshold matrix, per-component thresholds, and settings.

References

Mullen, T. R., et al. (2015). "Real-time neuroimaging and cognitive monitoring using wearable dry EEG." IEEE Transactions on Biomedical Engineering, 62(11), 2553-2567. doi:10.1109/TBME.2015.2481482

See also

asrProcess, cleanRawdata