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Normalize movement data

Source: R/ops-normalize.R
normalizeMovement.Rd

Normalizes movement data using various methods appropriate for different task types.

Usage

normalizeMovement(
  x,
  method = c("cycle", "phase", "landmark", "dtw", "absolute"),
  norm_length = 101L,
  schema = NULL,
  events = NULL,
  reference = NULL,
  ...
)

Arguments

x

Data to normalize:

  • PhysioExperiment object

  • Matrix (time x channels)

  • segmented_phases object

  • List of matrices (multiple trials)

method

Normalization method:

  • "cycle" - Normalize entire movement to fixed length (0-100%)

  • "phase" - Normalize each phase independently

  • "landmark" - Align to a specific event

  • "dtw" - Dynamic time warping alignment

  • "absolute" - Keep original time (no normalization)

norm_length

Target length after normalization (default 101 for 0-100%)

schema

Optional TaskSchema for context

events

Optional detected_events for landmark alignment

reference

Reference trial for DTW (default: mean of all trials)

...

Additional arguments passed to specific methods

Value

Normalized data in the same format as input (or matrix for segmented_phases)

References

Winter DA (2009). "Biomechanics and Motor Control of Human Movement." 4th ed. Wiley.

See also

batchNormalize(), normalizedTimeAxis(), segmentPhases()

Examples

# Normalize a matrix to 101 points
data <- matrix(rnorm(500), nrow = 500, ncol = 3)
normalized <- normalizeMovement(data, method = "cycle", norm_length = 101)