Type: Package
Title: Imports, Processes, and Visualizes Biomechanical Pressure Data
Version: 0.2.5
Description: Allows biomechanical pressure data from a range of systems to be imported and processed in a reproducible manner. Automatic and manual tools are included to let the user define regions (masks) to be analyzed. Also includes functions for visualizing and animating pressure data. Example methods are described in Shi et al., (2022) <doi:10.1038/s41598-022-19814-0>, Lee et al., (2014) <doi:10.1186/1757-1146-7-18>, van der Zward et al., (2014) <doi:10.1186/1757-1146-7-20>, Najafi et al., (2010) <doi:10.1016/j.gaitpost.2009.09.003>, Cavanagh and Rodgers (1987) <doi:10.1016/0021-9290(87)90255-7>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2
URL: https://github.com/Telfer/pressuRe
Imports: abind, dplyr, gdistance, ggmap, ggplot2, magick, magrittr, Morpho, pracma, raster, readxl, Rvcg, scales, sf, stringr, zoo
Depends: R (≥ 2.10)
NeedsCompilation: no
Packaged: 2025-02-20 23:50:13 UTC; telfe
Author: Scott Telfer ORCID iD [aut, cre, cph], Ellen Li ORCID iD [aut]
Maintainer: Scott Telfer <scott.telfer@gmail.com>
Repository: CRAN
Date/Publication: 2025-02-21 00:10:02 UTC

pressuRe: Imports, Processes, and Visualizes Biomechanical Pressure Data

Description

Allows biomechanical pressure data from a range of systems to be imported and processed in a reproducible manner. Automatic and manual tools are included to let the user define regions (masks) to be analyzed. Also includes functions for visualizing and animating pressure data. Example methods are described in Shi et al., (2022) doi:10.1038/s41598-022-19814-0, Lee et al., (2014) doi:10.1186/1757-1146-7-18, van der Zward et al., (2014) doi:10.1186/1757-1146-7-20, Najafi et al., (2010) doi:10.1016/j.gaitpost.2009.09.003, Cavanagh and Rodgers (1987) doi:10.1016/0021-9290(87)90255-7.

Author(s)

Maintainer: Scott Telfer scott.telfer@gmail.com (ORCID) [copyright holder]

Authors:

See Also

Useful links:

Animate pressure

Description

Produces animation (gif) of pressure data

Usage

animate_pressure(
  pressure_data,
  plot_colors = "default",
  fps,
  dpi = 96,
  file_name
)

Arguments

pressure_data

Array. A 3D array covering each timepoint of the measurement. z dimension represents time

plot_colors

String

fps

Numeric. Number of frames per second in animation

dpi

Numeric. Resolution of gif

file_name

Name (inlcuding path) of export file

Value

Animation in gif format

Examples


emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
animate_pressure(pressure_data, fps = 10, file_name = "pli_gif.gif")

Calculate Arch Index.

Description

Calculate Arch Index.

Usage

arch_index(pressure_data, plot = TRUE)

Arguments

pressure_data

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

plot

Logical. Not implemented yet

Value

Numeric. Arch index value

Examples

emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
arch_index(pressure_data)

Detect foot side

Description

Detects which foot plantar pressure data is from (left or right), usually would only be needed for barefoot pressure plate data. Generally reliable but may be thrown off by severe deformities or abnormal walking patterns

Usage

auto_detect_side(pressure_data)

Arguments

pressure_data

List. First item should be a 3D array covering each timepoint of the measurement. z dimension represents time

Value

String. "LEFT" or "RIGHT"

Examples

emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
auto_detect_side(pressure_data)

Center of pressure

Description

Generates xy coordinates for center of pressure during each frame of measurement

Usage

cop(pressure_data)

Arguments

pressure_data

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

Value

Data frame with x and y coordinates of COP throughout trial

Examples

emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
cop(pressure_data)

CPEI

Description

Determine Center of Pressure Excursion Index (CPEI) for footprint pressure data

Usage

cpei(pressure_data, foot_side, plot_result = TRUE)

Arguments

pressure_data

List. First item is a 3D array covering each timepoint of the measurement. Not currently available for pedar.

foot_side

String. "right" or "left". Required for automatic detection of points

plot_result

Logical. Plots pressure image with COP and CPEI overlaid

Value

Numeric. CPEI value

Author(s)

Scott Telfer scott.telfer@gmail.com

Examples


emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
cpei(pressure_data, foot_side = "auto", plot_result = FALSE)

Automatically mask pressure footprint

Description

Automatically creates mask for footprint data

Usage

create_mask_auto(
  pressure_data,
  masking_scheme,
  foot_side = "auto",
  res_value = c(20000, 20000, 1e+05, 20000),
  plot = TRUE,
  template_mask = NULL
)

Arguments

pressure_data

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

masking_scheme

String. "automask_simple", "automask_novel", "pedar_mask1", "pedar_mask2", "pedar_mask3", "template". "simple_automask" applies a simple 3 part mask (hindfoot, midfoot, forefoot) "automask_novel" attempts to apply a 9-part mask (hindfoot, midfoot, mets, hallux, lesser toes), similar to the standard novel automask "pedar_mask1" splits the insole into 4 regions using sensel boundaries: hindfoot, midfoot, forefoot, and toes- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9470545/ "pedar_mask2" splits the insole into 4 regions using percentages: hindfoot, forefoot, hallux, and lesser toes- https://jfootankleres.biomedcentral.com/articles/10.1186/1757-1146-7-18 "pedar_mask3" splits the foot into 9 regions using sensel boundaries: medial hindfoot, lateral hindfoot, medial midfoot, lateral midfoot, MTPJ1, MTPJ2-3, MTPJ4-5, hallux, and lesser toes- https://jfootankleres.biomedcentral.com/articles/10.1186/1757-1146-7-20

foot_side

String. "RIGHT", "LEFT", or "auto". Auto uses auto_detect_side function

res_value

Numeric vector. Adjusting these values can help if the heel, midfoot, toe, and hallux lines aren't correct. Default values are c(10000, 10000, 100000, 10000). These lines are calculated using a least cost function and the parameter essentially adjusts the resistance of the pressure value for that algorithm

plot

Logical. Whether to play the animation

template_mask

Data frame. Mask to be used if "template_mask" is selected as the masking scheme

Value

List. Masks are added to pressure data variable

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_novel",
res_value = c(20000, 20000, 100000, 20000), foot_side = "auto", plot = FALSE)

Create masking

Description

Allows user to manually define mask regions

Usage

create_mask_manual(
  pressure_data,
  mask_definition = "by_vertices",
  n_masks = 1,
  n_verts = 4,
  n_sens = 4,
  threshold = 0.005,
  plot_existing_masks = TRUE,
  mask_names = "default",
  plot = TRUE
)

Arguments

pressure_data

List. First item is a matrix covering each timepoint of the measurement.

mask_definition

String. "by_vertices" or "by_sensors". The first option let's you draw a shape around the area you want to select, the second allows you to define this area by clicking on specific sensors

n_masks

Numeric. Number of masks to add

n_verts

Numeric. Number of vertices in mask

n_sens

Numeric. Number of sensors mask will contain

threshold

Numeric. Distance between adjacent mask vertices before sharing vertex coordinates

plot_existing_masks

Logical. Show existing masks

mask_names

List. Mask names. Default is "custom_mask#"

plot

Logical. Show new maks on pressure image

Value

List. Mask(s) are added to pressure data variable

Examples


emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
pressure_data <- create_mask_manual(pressure_data, mask_definition = "by_vertices",
n_masks = 1, n_verts = 4)
pressure_data <- create_mask_manual(pressure_data, mask_definition = "by_sensors",
n_masks = 1, n_sens = 8)

Edit mask

Description

Allows user to manually adjust mask vertices

Usage

edit_mask(
  pressure_data,
  n_edit,
  threshold = 0.002,
  edit_list = seq(1, length(pressure_data[[5]])),
  image = "max"
)

Arguments

pressure_data

List. First item is a 3D array covering each timepoint of the measurement.

n_edit

Numeric. Number of vertices to edit

threshold

Numeric. Distance between point clicked and vertex that is selected

edit_list

List. Mask numbers that want to be edited. (Default is to load all masks so that adjacent masks with shared coordinates are modified together)

image

String."max" = footprint of maximum sensors. "mean" average value of sensors over time

Value

List. Edited mask is added to the pressure data variable

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_novel",
foot_side = "auto", plot = FALSE)
pressure_data <- edit_mask(pressure_data, n_edit = 1, threshold = 0.002,
image = "max")

Footprint

Description

Determines footprint of pressure data

Usage

footprint(pressure_data, variable = "max", frame = NULL, plot = FALSE)

Arguments

pressure_data

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

variable

String. "max" = maximum value of each sensor across full dataset. "mean" = average value of sensors over full dataset."frame" = an individual pressure frame. "meanmax" average max values across cycles ( currently just for pedar)

frame

Integer. Only used if variable = "frame".

plot

Logical. Display pressure image

Value

Matrix. Maximum or mean values for all sensors

Examples

emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
footprint(pressure_data, plot = FALSE)

Load emed data

Description

Imports and formats .lst files collected on emed system and exported from Novel software

Usage

load_emed(pressure_filepath, trim_active = FALSE)

Arguments

pressure_filepath

String. Filepath pointing to emed pressure file

trim_active

Logical. Restricts frames to only the first continuous foot contact

Value

A list with information about the pressure data.

Examples

emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)

Load footscan data

Description

Imports and formats files collected on footscan systems (formerly RSScan)

Usage

load_footscan(pressure_filepath)

Arguments

pressure_filepath

String. Filepath pointing to emed pressure file

Value

A list with information about the pressure data.

Examples

footscan_data <- system.file("extdata", "footscan_test.xls", package = "pressuRe")
pressure_data <- load_footscan(footscan_data)

Load pedar data

Description

Imports and formats .asc files collected on pedar system and exported from Novel software

Usage

load_pedar(pressure_filepath)

Arguments

pressure_filepath

String. Filepath pointing to pedar pressure file

Value

A list with information about the pressure data.

Examples

pedar_data <- system.file("extdata", "pedar_example.asc", package = "pressuRe")
pressure_data <- load_pedar(pedar_data)

Load pliance data

Description

Imports and formats .asc files collected on pliance system and exported from Novel software

Usage

load_pliance(pressure_filepath)

Arguments

pressure_filepath

String. Filepath pointing to pliance pressure file

Value

A list with information about the pressure data.

Examples

pliance_data <- system.file("extdata", "pliance_test.asc", package = "pressuRe")
pressure_data <- load_pliance(pliance_data)

Load Tekscan data

Description

Imports and formats files collected on tekscan systems and exported from Tekscan software

Usage

load_tekscan(pressure_filepath)

Arguments

pressure_filepath

String. Filepath pointing to emed pressure file

Value

A list with information about the pressure data.

Examples

tekscan_data <- system.file("extdata", "fscan_testL.asf", package = "pressuRe")
pressure_data <- load_tekscan(tekscan_data)

Load xsensor data

Description

Imports and formats files collected on xsensor insole systems

Usage

load_xsensor(pressure_filepath)

Arguments

pressure_filepath

String. Filepath pointing to emed pressure file

Value

A list with information about the pressure data.

Examples

xsensor_data <- system.file("extdata", "xsensor_data.csv", package = "pressuRe")
pressure_data <- load_xsensor(xsensor_data)

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")

pedar sensor size data

Description

Sensor sizes for different pedar insoles

Usage

pedar_insole_areas

Format

## 'pedar_insole_areas' A data frame with 198 rows and 8 columns:

u

areas for size u

v

areas for size v

w

areas for size w

x

areas for size x

y

areas for size y

uw

areas for size uw

xw

areas for size xw

vw

areas for size vw

Source

Scott Telfer

pedar sensor grid data

Description

Sensor outline coordinates

Usage

pedar_insole_grid

Format

## 'pedar_insole_grid' A data frame with 199 rows and 8 columns:

V1

x1 coordinate

V2

y1 coordinate

V3

x2 coordinate

V4

y2 coordinate

V5

x3 coordinate

V6

y3 coordinate

V7

x4 coordinate

V8

y4 coordinate

Source

Scott Telfer

Plot pressure

Description

Produces visualization of pressure data

Usage

plot_pressure(
  pressure_data,
  variable = "max",
  smooth = FALSE,
  frame,
  step_n = "max",
  plot_COP = FALSE,
  plot_outline = FALSE,
  plot_masks = FALSE,
  plot_colors = "default",
  break_values,
  break_colors,
  sensor_outline = TRUE,
  plot = TRUE,
  legend = TRUE
)

Arguments

pressure_data

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

variable

String. "max" = footprint of maximum sensors. "mean" = average value of sensors over time (usually for static analyses). "frame" = an individual frame

smooth

Logical. Not implemented. If TRUE, plot will interpolate between sensors to increase data density

frame

Integer.

step_n

If numeric, the step number to plot (only for insole data). If "max", the max across complete trial, if "meanmax", the max on a per step basis

plot_COP

Logical. If TRUE, overlay COP data on plot. Default = FALSE

plot_outline

Logical. If TRUE, overlay convex hull outline on plot

plot_masks

Logical. If TRUE, overlay mask outline on plot

plot_colors

String. "default": novel color scheme; "custom": user supplied

break_values

Vector. If plot_colors is "custom", values to split colors at

break_colors

Vector. If plot_colors is "custom", colors to use. Should be one shorter than break_values

sensor_outline

Logical. Sensor outline to be shown

plot

Logical. If TRUE, plot will be displayed

legend

Logical. If TRUE, legend will be added to plot

Value

ggplot plot object

Examples

emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
plot_pressure(pressure_data, variable = "max", plot_COP = FALSE)
plot_pressure(pressure_data, variable = "frame", frame = 20,
              plot_colors = "custom", break_values = c(100, 200, 300),
              break_colors = c("light blue", "light green", "yellow", "pink"))

Interpolate pressure data

Description

Resamples pressure data over time. Useful for normalizing to stance phase, for example

Usage

pressure_interp(pressure_data, interp_to)

Arguments

pressure_data

List. First item should be a 3D array covering each timepoint of the measurement. z dimension represents time.

interp_to

Integer. Number of frames to interpolate to

Value

Examples

emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
pressure_data <- pressure_interp(pressure_data, interp_to = 101)

Select steps

Description

Select steps, usually from insole data, and format for analysis

Usage

select_steps(
  pressure_data,
  threshold = "auto",
  min_frames = 10,
  n_steps = 5,
  skip = 2
)

Arguments

pressure_data

List. First item should be a 3D array covering each timepoint of the measurement. z dimension represents time.

threshold

Numeric. Threshold force to define start and end of step. If "auto", function will set threshold at minimum force in trial + 10N

min_frames

Numeric. Minimum number of frames that need to be in step

n_steps

Numeric. Target number of steps/cycles. User will be asked to keep selected steps until this target is reached or they run out of candidate steps

skip

Numeric. Usually the first few steps of a trial are accelerating and not representative of steady state walking so this removes them

Value

Examples


pedar_data <- system.file("extdata", "pedar_example.asc", package = "pressuRe")
pressure_data <- load_pedar(pedar_data)
pressure_data <- select_steps(pressure_data)

Whole pressure curve

Description

Generates vectors with option to plot for force, peak/mean pressure and area for complete measurement. Useful for checking data

Usage

whole_pressure_curve(
  pressure_data,
  variable,
  side,
  threshold = 10,
  plot = FALSE
)

Arguments

pressure_data

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

variable

String. "peak_pressure", "force", or "area"

side

For insole data only

threshold

Numeric. Threshold value for sensor to be considered active. Currently only applies to insole data

plot

Logical. If TRUE also plots data as line curve

Value

Numeric vector containing variable values

Examples

emed_data <- system.file("extdata", "emed_test.lst", package = "pressuRe")
pressure_data <- load_emed(emed_data)
whole_pressure_curve(pressure_data, variable = "peak_pressure", plot = FALSE)
whole_pressure_curve(pressure_data, variable = "area", plot = FALSE)
whole_pressure_curve(pressure_data, variable = "force", plot = FALSE)