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.
Examples
pe <- make_eeg(n_time = 5000, n_channels = 19, sr = 500)
result <- eegSlowing(pe, method = "dtar")
print(result)
#> channel metric value classification
#> 1 1 dtar 1.281362 mild_slowing
#> 2 2 dtar 1.009824 mild_slowing
#> 3 3 dtar 1.226197 mild_slowing
#> 4 4 dtar 1.216584 mild_slowing
#> 5 5 dtar 1.045893 mild_slowing
#> 6 6 dtar 1.399565 mild_slowing
#> 7 7 dtar 1.359063 mild_slowing
#> 8 8 dtar 1.194493 mild_slowing
#> 9 9 dtar 2.576911 moderate_slowing
#> 10 10 dtar 2.041697 moderate_slowing
#> 11 11 dtar 3.418652 moderate_slowing
#> 12 12 dtar 5.516801 severe_slowing
#> 13 13 dtar 5.362880 severe_slowing
#> 14 14 dtar 5.119384 severe_slowing
#> 15 15 dtar 4.104294 severe_slowing
#> 16 16 dtar 4.415537 severe_slowing
#> 17 17 dtar 3.791294 moderate_slowing
#> 18 18 dtar 2.083023 moderate_slowing
#> 19 19 dtar 1.516108 mild_slowing