Dynamic Wavelet Coherence Network for EMG

Builds a time-varying coordination network by computing wavelet coherence between channel pairs and aggregating coherence within sliding windows.

Usage

emgDynamicWaveletNetwork(
  x,
  frequencies = seq(5, 120, by = 5),
  freq_band = NULL,
  channels = NULL,
  window_sec = 0.5,
  step_sec = 0.1,
  n_cycles = 7,
  smoothing_cycles = 3,
  assay_name = NULL,
  aggregate = c("mean", "max", "median"),
  threshold = NULL,
  respect_coi = TRUE
)

Arguments

x

A PhysioExperiment object.

frequencies

Numeric vector of wavelet center frequencies (Hz).

freq_band

Optional numeric vector c(low, high) for aggregation.

channels

Integer vector of channel indices to include. If NULL, uses all.

window_sec

Sliding window length in seconds.

step_sec

Sliding window step in seconds.

n_cycles

Number of Morlet cycles (default: 7).

smoothing_cycles

Smoothing width in cycles (default: 3).

assay_name

Input assay name. If NULL, uses default assay.

aggregate

Aggregation across time-frequency bins: "mean", "max", or "median".

threshold

Optional threshold for binary adjacency network per window.

respect_coi

Logical; if TRUE, masks frequencies below COI before aggregation.

Value

A list with:

network

3D array (window x channel x channel).

adjacency

Logical 3D array thresholded from network, or NULL.

window_times

Window center times in seconds.

static_summary

Mean network across windows.

frequencies

Frequency vector used for wavelet transform.

coi

Cone-of-influence frequency at each time sample.

See also

emgCoherenceNetwork() for static spectral network, emgInterpretNetworkKG() for annotation-aware interpretation.