mask_analysis {pressuRe}

Analyze masked regions of pressure data

Description

Analyze masked regions of pressure data

Usage

mask_analysis(
  pressure_data,
  partial_sensors = FALSE,
  variable = "press_peak_sensor",
  pressure_units = "kPa",
  area_units = "cm2"
)

Arguments

pressure_data

List. Includes a 3D array covering each timepoint of the measurement. z dimension represents time

partial_sensors

Logical Defines how sensors that do not lie wholly within mask are dealt with. If FALSE, they will be excluded; if TRUE, for relevant variables their contribution will be weighted by the proportion of the sensor that falls within the mask border

variable

String. Variable to be determined. "press_peak_sensor", "press_peak_mask", "contact_area_peak", "pti_1", "pti_2", "force_time_integral", "force_peak", "dpli", "press_peak_sensor_ts", "force_ts". Variables ending in "_ts" produce time series data

pressure_units

String. Default "kPa". Other options: "MPa", "Ncm2" (Newtons per square centimeter)

area_units

String. Default is "cm2" (square centimeters). Other options "m2" (square meters); "mm2" (square millimeters)

Value

Data frame. Contains values for each mask plus additional information relevant to the data including cycle/step and foot side

Examples

emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
pressure_data <- create_mask_auto(pressure_data, "automask_simple", plot = FALSE)
mask_analysis(pressure_data, FALSE, variable = "press_peak_sensor")