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Detect events in movement data

Source: R/ops-events.R
detectEvents.Rd

Automatically detects events defined in a TaskSchema based on signal data.

Usage

detectEvents(
  x,
  schema,
  signals = NULL,
  method = c("auto", "manual", "hybrid", "zeni"),
  sampling_rate = NULL,
  ...
)

Arguments

x

PhysioExperiment object or matrix (time x channels)

schema

TaskSchema object defining events to detect

signals

Named list of signal vectors for detection. If NULL and x is a PhysioExperiment, signals are extracted from column names. If x is a matrix with named columns, signals are auto-created from those names; otherwise provide signals explicitly.

method

Detection approach:

  • "auto" - Automatic detection using schema definitions

  • "manual" - Use typical_timing from schema as event times

  • "hybrid" - Try auto first, fall back to typical_timing if failed

sampling_rate

Sampling rate in Hz. Required if x is a matrix.

...

Additional arguments passed to detection methods

Value

A data.frame with columns:

  • event - Event name

  • label - Human-readable label

  • index - Sample index of event

  • time - Time in seconds

  • percent - Percent of movement (if applicable)

  • method - Detection method used

  • confidence - Detection confidence (0-1)

References

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

See also

manualEvents(), segmentPhases(), TaskSchema()

Examples

# Create synthetic gait data
set.seed(123)
n <- 1000
t <- seq(0, 1, length.out = n)
vGRF <- c(rep(0, 100), sin(seq(0, pi, length.out = 500)) * 800, rep(0, 400))
vGRF <- vGRF + rnorm(n, 0, 10)

signals <- list(vGRF = vGRF)
events <- detectEvents(as.matrix(vGRF), schema_gait,
                       signals = signals, sampling_rate = 1000)