Simulate Synthetic EDA Signals

Generates synthetic electrodermal activity (EDA) signals with known tonic (SCL) and phasic (SCR) components for testing and demonstration. SCRs are modeled as biexponential impulse responses (Bateman function).

Usage

edaSimulate(
  n_time = 6000,
  n_channels = 1,
  sr = 10,
  scr_count = 5,
  scl_level = 5,
  scr_amplitude = 0.5,
  noise_sd = 0.01,
  seed = NULL
)

Arguments

n_time: Number of time points (default: 6000).
n_channels: Number of EDA channels (default: 1).
sr: Sampling rate in Hz (default: 10).
scr_count: Number of SCRs to embed (default: 5).
scl_level: Baseline skin conductance level in microsiemens (default: 5.0).
scr_amplitude: Mean SCR amplitude in microsiemens (default: 0.5).
noise_sd: Standard deviation of Gaussian noise (default: 0.01).
seed: Random seed for reproducibility (default: NULL).

Value

A PhysioExperiment object with a single "raw" assay containing the simulated EDA signal (time x channels matrix). Channel metadata has type = "EDA" and unit = "uS". The sampling rate is set to sr. The ground-truth components used to build the signal are stored in metadata(x)$eda_truth as a list with:

tonic: time x channels matrix of the true tonic (SCL) component.
phasic: time x channels matrix of the true phasic (SCR) component.
onsets: a data.frame of the true SCR onsets with columns channel, sample, time_sec, and amplitude.

This lets edaSimulate() serve as a ground-truth oracle for testing decomposition (e.g. edaDecompose with method="cvxeda").

References

Boucsein, W. (2012). Electrodermal Activity. 2nd ed. Springer. doi:10.1007/978-1-4614-1126-0

Benedek, M., & Kaernbach, C. (2010). "A continuous measure of phasic electrodermal activity." Journal of Neuroscience Methods, 190(1), 80-91. doi:10.1016/j.jneumeth.2010.04.028

Usage

Arguments

Value

References

See also