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EEG Slowing Detection

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

Detects pathological EEG slowing using spectral analysis. Supports three methods: theta/delta ratio (TDR), delta-theta/alpha-beta ratio (DTAR), and peak frequency analysis. Each channel is classified into normal, mild, moderate, or severe slowing categories.

Usage

eegSlowing(
  x,
  method = c("tdr", "dtar", "peak_frequency"),
  bands = NULL,
  assay_name = NULL
)

Arguments

x

A PhysioExperiment object with EEG data.

method

Analysis method: "tdr" (theta/delta ratio), "dtar" (delta+theta over alpha+beta ratio), or "peak_frequency" (dominant frequency per channel).

bands

Named list of frequency bands for TDR and DTAR methods. Defaults to standard EEG bands.

assay_name

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

Value

A data.frame with columns:

channel

Integer channel index.

metric

Character name of the metric used.

value

Numeric value of the metric.

classification

Character: "normal", "mild_slowing", "moderate_slowing", or "severe_slowing".

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(), eegAsymmetry(), eegSuppression()

Examples

if (FALSE) { # \dontrun{
pe <- make_eeg(n_time = 5000, n_channels = 19, sr = 500)
result <- eegSlowing(pe, method = "dtar")
print(result)
} # }