Electromechanical Delay via Cross-Correlation — neuromechElectromechanicalDelay • PhysioMSKNet

Computes the electromechanical delay (EMD) between EMG and kinematic signals for muscle-bone pairs connected in the MSK hypergraph. Optionally correlates EMD with MSK network distance.

Usage

neuromechElectromechanicalDelay(
  emg,
  kinematics,
  hg = NULL,
  emg_mapping = NULL,
  kin_mapping = NULL,
  sr = NULL,
  max_lag_ms = 200,
  window_sec = NULL,
  n_perm = 999L
)

Arguments

emg: EMG data: SummarizedExperiment, matrix (time x channels), or vector.
kinematics: Kinematic data: matrix (time x segments) or SummarizedExperiment.
hg: An MSKHypergraph object (NULL loads default).
emg_mapping: Optional pre-computed data.frame from emgToMSKMapping().
kin_mapping: Optional pre-computed data.frame from mocapToMSKMapping() or imuToMSKMapping().
sr: Optional sampling rate (overrides detected value).
max_lag_ms: Numeric, maximum lag in milliseconds (default: 200).
window_sec: Optional numeric, window size in seconds for sliding window EMD analysis (NULL for global only).
n_perm: Integer, number of permutations for correlation test (default: 999).

Value

A list with:

emd: Data.frame with muscle, bone, emd_ms, peak_correlation per pair
network_distance: Corresponding MSK shortest path distance
correlation: Pearson correlation between EMD and network distance
p_value: Permutation p-value for the correlation
time_varying: Data.frame with per-window EMD (if window_sec set)

Examples

if (FALSE) { # \dontrun{
result <- neuromechElectromechanicalDelay(emg_data, kin_data)
} # }