Skip to contents

Burst-Suppression Detection

Source: R/eeg-clinical.R
eegSuppression.Rd

Identifies periods of burst and suppression in EEG data by computing the root mean square (RMS) amplitude in sliding windows. Suppression segments are defined as consecutive windows where RMS falls below the specified threshold for at least min_duration_ms.

Usage

eegSuppression(
  x,
  threshold = 10,
  min_duration_ms = 500,
  window_ms = 500,
  assay_name = NULL
)

Arguments

x

A PhysioExperiment object with EEG data.

threshold

RMS amplitude threshold below which signal is considered suppressed (default: 10).

min_duration_ms

Minimum duration in milliseconds for a segment to be classified as suppression (default: 500).

window_ms

Window length in milliseconds for RMS computation (default: 500).

assay_name

Name of the input assay. If NULL, the default assay is used.

Value

A data.frame with columns:

type

Character: "burst" or "suppression".

start_sample

Integer start sample of the segment.

end_sample

Integer end sample of the segment.

duration_ms

Numeric duration of the segment in milliseconds.

An attribute "bsr" (Burst-Suppression Ratio) is attached, representing the percentage of total time in suppression.

References

Nuwer, M. R., et al. (1999). IFCN standards for digital recording of clinical EEG. Electroencephalography and Clinical Neurophysiology, 106(3), 259-261.

See also

eegSpikeDetect(), eegQEEG(), eegSlowing()

Examples

if (FALSE) { # \dontrun{
pe <- make_eeg(n_time = 10000, n_channels = 4, sr = 500)
result <- eegSuppression(pe, threshold = 10)
print(attr(result, "bsr"))
} # }