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Plot gait cycle normalized waveforms

Source: R/vis-biomech.R
plotGaitCycle.Rd

Plots waveforms normalized to gait cycle (0-100%) with options for displaying multiple trials, mean, and variability bands.

Usage

plotGaitCycle(
  x,
  events = NULL,
  normalize_to = 101,
  show_events = TRUE,
  show_mean = TRUE,
  show_sd = TRUE,
  show_individual = TRUE,
  event_labels = c(HS = 0, TO = 60, HS = 100),
  title = "Gait Cycle",
  ylab = "Value"
)

Arguments

x

A PhysioExperiment, matrix, or list of matrices.

events

Optional data.frame with gait events (heel strike, toe off).

normalize_to

Length to normalize (default: 101 for 0-100%).

show_events

Logical; show vertical lines at gait events.

show_mean

Logical; show mean waveform.

show_sd

Logical; show SD bands.

show_individual

Logical; show individual trials.

event_labels

Labels for gait events.

title

Plot title.

ylab

Y-axis label.

Value

A ggplot object.

References

Wickham H (2016). "ggplot2: Elegant Graphics for Data Analysis." Springer.

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

See also

plotWaveformComparison() for multi-group comparisons, plotSpaghetti() for individual waveform overlays, calculateGaitParameters() for computing gait metrics.

Examples

# Normalize and plot knee angle across gait cycle
set.seed(123)
data <- sapply(1:10, function(i) {
  n <- sample(90:110, 1)  # Variable cycle length
  sin(seq(0, 2*pi, length.out = n)) * 60 + rnorm(n, 0, 3)
})

plotGaitCycle(data, show_mean = TRUE, show_sd = TRUE,
              ylab = "Knee Flexion (deg)")