Denoise EDA using dependency-light Haar wavelet shrinkage — denoise_gazepoint_eda

Applies simple Haar wavelet soft-threshold denoising to EDA signals within optional groups. This is a dependency-light wavelet denoising helper and should not be described as an exact reproduction of stationary-wavelet artifact-removal algorithms.

Usage

denoise_gazepoint_eda_wavelet(
  dat,
  eda_col = "GSR_US",
  group_cols = NULL,
  output_col = NULL,
  levels = 3,
  threshold_multiplier = 1,
  overwrite = FALSE
)

Arguments

dat: A data frame containing EDA data.
eda_col: EDA/conductance column.
group_cols: Optional grouping columns.
output_col: Optional output column.
levels: Number of Haar decomposition levels.
threshold_multiplier: Multiplier applied to the robust noise estimate.
overwrite: Logical. If FALSE, protect existing output columns.

Value

A data frame with denoised EDA and denoising attributes.