| Title: | Analysis of Work Loops and Other Data from Muscle Physiology Experiments |
|---|---|
| Description: | Functions for the import, transformation, and analysis of data from muscle physiology experiments. The work loop technique is used to evaluate the mechanical work and power output of muscle. Josephson (1985) <doi:10.1242/jeb.114.1.493> modernized the technique for application in comparative biomechanics. Although our initial motivation was to provide functions to analyze work loop experiment data, as we developed the package we incorporated the ability to analyze data from experiments that are often complementary to work loops. There are currently three supported experiment types: work loops, simple twitches, and tetanus trials. Data can be imported directly from .ddf files or via an object constructor function. Through either method, data can then be cleaned or transformed via methods typically used in studies of muscle physiology. Data can then be analyzed to determine the timing and magnitude of force development and relaxation (for isometric trials) or the magnitude of work, net power, and instantaneous power among other things (for work loops). Although we do not provide plotting functions, all resultant objects are designed to be friendly to visualization via either base-R plotting or 'tidyverse' functions. This package has been peer-reviewed by rOpenSci (v. 1.1.0). |
| Authors: | Vikram B. Baliga [aut, cre]  ,
Shreeram Senthivasan [aut] ,
Julia Romanowska [rev] (Julia reviewed the package for rOpenSci , see
<https://github.com/ropensci/software-review/issues/326/>),
Eric Brown [rev] (Eric reviewed the package for rOpenSci , see
<https://github.com/ropensci/software-review/issues/326/>) |
| Maintainer: | Vikram B. Baliga <[email protected]> |
| License: | GPL (>= 3) |
| Version: | 1.1.4 |
| Built: | 2025-01-13 03:33:23 UTC |
| Source: | https://github.com/ropensci/workloopR |
Compute work and power output from a work loop experiment on a per-cycle basis.
analyze_workloop(x, simplify = FALSE, GR = 1, M = -1, vel_bf = 0.05, ...)analyze_workloop(x, simplify = FALSE, GR = 1, M = -1, vel_bf = 0.05, ...)
x |
A |
simplify |
Logical. If |
GR |
Gear ratio, set to 1 by default |
M |
Velocity multiplier, set adjust the sign of velocity. This parameter should generally be either -1 (the default) or 1. |
vel_bf |
Critical frequency (scalar) for low-pass filtering of velocity
via |
... |
Additional arguments potentially passed down from
|
Please note that select_cycles() must be run on data prior to
using this function. This function relies on the input muscle_stim
object being organized by cycle number.
The muscle_stim object (x) must be a workloop,
preferably read in by one of our data import functions. Please see
documentation for as_muscle_stim() if you need to manually construct
a muscle_stim object from a non .ddf source.
The gear ratio (GR) and velocity multiplier (M) parameters can help correct
for issues related to the magnitude and sign of data collection. By default,
they are set to apply no gear ratio adjustment and to positivize velocity.
Instantaneous velocity is often noisy and the vel_bf parameter allows
for low-pass filtering of velocity data. See signal::butter() and
signal::filtfilt() for details of how filtering is achieved.
Please also be careful with units! Se Warning section below.
The function returns a list of class analyzed_workloop
that provides instantaneous velocity, a smoothed velocity, and computes work,
instantaneous power, and net power from a work loop experiment. All data are
organized by the cycle number and important metadata are stored as
Attributes.
Within the list, each entry is labeled by cycle and includes:
Time |
Time, in sec |
Position |
Length change of the muscle, corrected for gear ratio, in mm |
Force |
Force, corrected for gear ratio, in mN |
Stim |
When stimulation occurs, on a binary scale |
Cycle |
Cycle ID, as a letter |
Inst_velocity |
Instantaneous velocity, computed from |
Filt_velocity |
Instantaneous velocity, after low-pass filtering, again in meter/sec |
Inst_Power |
Instantaneous power, a product of |
Percent_of_Cycle |
The percent of that particular cycle which has elapsed |
In addition, the following information is stored in the
analyzed_workloop object's attributes:
stimulus_frequency |
Frequency at which stimulus pulses occurred |
cycle_frequency |
Frequency of oscillations (assuming sine wave trajectory) |
total_cycles |
Total number of oscillatory cycles (assuming sine wave trajectory) that the muscle experienced. |
cycle_def |
Specifies what part of the cycle is understood as the beginning and end. There are currently three options: 'lo' for L0-to-L0; 'p2p' for peak-to-peak; and 't2t' for trough-to-trough |
amplitude |
Amplitude of length change (assuming sine wave trajectory) |
phase |
Phase of the oscillatory cycle (in percent) at which stimulation occurred. Somewhat experimental, please use with caution |
position_inverted |
Logical; whether position inversion has been applied) |
units |
The units of measurement for each column in the object after running this function. See Warning |
sample_frequency |
Frequency at which samples were collected |
header |
Additional information from the header |
units_table |
Units from each Channel of the original ddf file |
protocol_table |
Protocol in tabular format; taken from the original ddf file |
stim_table |
Specific info on stimulus protocol; taken from the original ddf file |
stimulus_pulses |
Number of sequential pulses within a stimulation train |
stimulus_offset |
Timing offset at which stimulus began |
gear_ratio |
Gear ratio applied by this function |
file_id |
File name |
mtime |
Time at which file was last modified |
retained_cycles |
Which cycles were retained, as numerics |
summary |
Simple table showing work (in J) and net power (in W) for each cycle |
Most systems we have encountered record Position data in millimeters
and Force in millinewtons, and therefore this function assumes data are
recorded in those units. Through a series of internal conversions, this
function computes velocity in meters/sec, work in Joules, and power in
Watts. If your raw data do not originate in millimeters and millinewtons,
please transform your data accordingly and ignore what you see in the
attribute units.
Vikram B. Baliga and Shreeram Senthivasan
Josephson RK. 1985. Mechanical Power output from Striated Muscle during Cyclic Contraction. Journal of Experimental Biology 114: 493-512.
read_ddf,
read_analyze_wl,
select_cycles
Other data analyses:
isometric_timing(),
read_analyze_wl_dir(),
read_analyze_wl()
Other workloop functions:
fix_GR(),
get_wl_metadata(),
invert_position(),
read_analyze_wl_dir(),
read_analyze_wl(),
select_cycles(),
summarize_wl_trials(),
time_correct()
library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE) # select cycles 3 through 5 via the peak-to-peak definition wl_selected <- select_cycles(wl_dat, cycle_def = "p2p", keep_cycles = 3:5) # run the analysis function and get the full object wl_analyzed <- analyze_workloop(wl_selected, GR = 2) # print methods give a short summary print(wl_analyzed) # summary provides a bit more detail summary(wl_analyzed) # run the analysis but get the simplified version wl_analyzed_simple <- analyze_workloop(wl_selected, simplify = TRUE, GR = 2)library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE) # select cycles 3 through 5 via the peak-to-peak definition wl_selected <- select_cycles(wl_dat, cycle_def = "p2p", keep_cycles = 3:5) # run the analysis function and get the full object wl_analyzed <- analyze_workloop(wl_selected, GR = 2) # print methods give a short summary print(wl_analyzed) # summary provides a bit more detail summary(wl_analyzed) # run the analysis but get the simplified version wl_analyzed_simple <- analyze_workloop(wl_selected, simplify = TRUE, GR = 2)
For use when data are not stored in .ddf format and you would like
to create a muscle_stim object that can be used by other workloopR
functions.
as_muscle_stim(x, type, sample_frequency, ...)as_muscle_stim(x, type, sample_frequency, ...)
x |
A |
type |
Experiment type; must be one of: "workloop", "tetanus", or "twitch." |
sample_frequency |
Numeric value of the frequency at which samples were
recorded; must be in Hz. Please format as numeric, e.g. |
... |
Additional arguments that can be passed in as attributes. See Details. |
muscle_stim objects, which are required by (nearly) all
workloopR functions, are automatically created via read_ddf(). Should
you have data that are stored in a format other than .ddf, use this function
to create your own object of class muscle_stim.
The input x must be a data.frame that contains time series
of numeric data collected from an experiment. Each row must correspond to a
sample, and these columns (exact title matches) must be included:
"Time" - time, recorded in seconds
"Position" - instantaneous position of the muscle,
preferably in millimeters
"Force" - force, preferably in millinewtons
"Stim" - whether stimulation has occurred. All entries must be either 0 (no
stimulus) or 1 (stimulus occurrence).
Additional arguments can be provided via .... For all experiment
types, the following attributes are appropriate:
"units","header", "units_table",
"protocol_table", "stim_table",
"stimulus_pulses", "stimulus_offset",
"stimulus_width", "gear_ratio",
"file_id", or "mtime".
Please ensure that further attributes are appropriate to your experiment type.
For workloops, these include: "stimulus_frequency", "cycle_frequency", "total_cycles", "cycle_def", "amplitude", "phase", and "position_inverted"
For twitches or tetanic trials: "stimulus_frequency", and "stimulus_length"
An object of class workloop, twitch, or tetanus,
all of which inherit class muscle_stim. These objects behave like
data.frames in most situations but also store metadata from the ddf
as attributes.
The muscle_stim object's columns contain:
Time |
Time |
Position |
Length change of the muscle, uncorrected for gear ratio |
Force |
Force, uncorrected for gear ratio |
Stim |
When stimulation occurs, on a binary scale |
In addition, the following information is stored in the data.frame's
attributes:
sample_frequency |
Frequency at which samples were collected |
pulses |
Number of sequential pulses within a stimulation train |
total_cycles_lo |
Total number of oscillatory cycles (assuming sine wave trajectory) that the muscle experienced. Cycles are defined with respect to initial muscle length (L0-to-L0 as opposed to peak-to-peak). |
amplitude |
amplitude of length change (again, assuming sine wave trajectory) |
cycle_frequency |
Frequency of oscillations (again, assuming sine wave trajectory) |
units |
The units of measurement for each column in the
|
Shreeram Senthivasan
Other data import functions:
get_wl_metadata(),
read_analyze_wl_dir(),
read_analyze_wl(),
read_ddf_dir(),
read_ddf()
library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'))library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'))
Fix a discrepancy between the gear ratio of the motor arm used and the gear ratio recorded by software.
fix_GR(x, GR = 1)fix_GR(x, GR = 1)
x |
A |
GR |
Gear ratio, set to 1 by default |
The muscle_stim object can be of any type, including
workloop, twitch, or tetanus.
If you have manually constructed the object via as_muscle_stim(),
the muscle_stim object should have columns as follows: Position: length change of the muscle; Force: force
An object of the same class(es) as the input (x). The function
will multiply Position by (1/GR) and multiply Force by GR,
returning an object with new values in $Position and $Force.
Other columns and attributes are welcome and will simply be passed on
unchanged into the resulting object.
Vikram B. Baliga
analyze_workloop,
read_analyze_wl,
read_analyze_wl_dir
Other data transformations:
invert_position(),
select_cycles()
Other workloop functions:
analyze_workloop(),
get_wl_metadata(),
invert_position(),
read_analyze_wl_dir(),
read_analyze_wl(),
select_cycles(),
summarize_wl_trials(),
time_correct()
Other twitch functions:
invert_position(),
isometric_timing()
Other tetanus functions:
invert_position()
library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE) # apply a gear ratio correction of 2 # this will multiply Force by 2 and divide Position by 2 wl_fixed <- fix_GR(wl_dat, GR = 2) # quick check: max(wl_fixed$Force) / max(wl_dat$Force) # 5592.578 / 2796.289 = 2 max(wl_fixed$Position) / max(wl_dat$Position) # 1.832262 / 3.664524 = 0.5library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE) # apply a gear ratio correction of 2 # this will multiply Force by 2 and divide Position by 2 wl_fixed <- fix_GR(wl_dat, GR = 2) # quick check: max(wl_fixed$Force) / max(wl_dat$Force) # 5592.578 / 2796.289 = 2 max(wl_fixed$Position) / max(wl_dat$Position) # 1.832262 / 3.664524 = 0.5
Grab metadata from files stored in the same folder (e.g. a sequence of trials in an experiment).
get_wl_metadata(file_path, pattern = "*.ddf")get_wl_metadata(file_path, pattern = "*.ddf")
file_path |
Path where files are stored. Should be in the same folder. |
pattern |
Regex pattern for identifying relevant files in the file_path. |
If several files (e.g. successive trials from one experiment) are
stored in one folder, use this function to obtain metadata in a list
format. Runs file.info() from base R to extract info from files.
This function is not truly considered to be part of the batch analysis
pipeline;
see read_analyze_wl_dir() for a similar function that not
only grabs metadata but also imports & analyzes files. Instead,
get_wl_metadata() is meant to be a handy function to investigate
metadata issues that arise if running read_analyze_wl_dir() goes awry.
Unlike read_analyze_wl_dir(), this function does not necessarily need
files to all be work loops. Any file type is welcome (as long as the Regex
pattern argument makes sense).
Either a data.frame (if a single file is supplied) or a
list of data.frames (if a list of files is supplied), with
information as supplied from file.info().
Vikram B. Baliga
Other data import functions:
as_muscle_stim(),
read_analyze_wl_dir(),
read_analyze_wl(),
read_ddf_dir(),
read_ddf()
Other workloop functions:
analyze_workloop(),
fix_GR(),
invert_position(),
read_analyze_wl_dir(),
read_analyze_wl(),
select_cycles(),
summarize_wl_trials(),
time_correct()
Other batch analyses:
read_analyze_wl_dir(),
summarize_wl_trials(),
time_correct()
library(workloopR) # get file info for files included with workloopR wl_meta <- get_wl_metadata(system.file("extdata/wl_duration_trials", package = 'workloopR'))library(workloopR) # get file info for files included with workloopR wl_meta <- get_wl_metadata(system.file("extdata/wl_duration_trials", package = 'workloopR'))
Multiply instantaneous position by -1.
invert_position(x)invert_position(x)
x |
A |
The muscle_stim object can be of any type, including
workloop, twitch, or tetanus.
If you have manually constructed the object via as_muscle_stim(),
the muscle_stim object should have a column entitled Position.
Other columns and attributes are welcome and will be passed along unchanged.
A workloop object with inverted position. The
position_inverted attribute is set to TRUE and all others are
retained.
Vikram B. Baliga
Other data transformations:
fix_GR(),
select_cycles()
Other workloop functions:
analyze_workloop(),
fix_GR(),
get_wl_metadata(),
read_analyze_wl_dir(),
read_analyze_wl(),
select_cycles(),
summarize_wl_trials(),
time_correct()
Other twitch functions:
fix_GR(),
isometric_timing()
Other tetanus functions:
fix_GR()
library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE) # invert the sign of Position wl_fixed <- invert_position(wl_dat) # quick check: max(wl_fixed$Position) / min(wl_dat$Position) # -1library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE) # invert the sign of Position wl_fixed <- invert_position(wl_dat) # quick check: max(wl_fixed$Position) / min(wl_dat$Position) # -1
Calculate timing and magnitude of force at stimulation, peak force, and various parts of the rising (force development) and relaxation (falling) phases of the twitch.
isometric_timing(x, rising = c(10, 90), relaxing = c(90, 50))isometric_timing(x, rising = c(10, 90), relaxing = c(90, 50))
x |
A |
rising |
Set points of the rising phase to be described. By default: 10% and 90%. |
relaxing |
Set points of the relaxation phase to be described. By default: 90% and 50%. |
The data.frame (x) must have time series data organized in
columns. Generally, it is preferred that you use a muscle_stim object
imported by read_ddf().
The rising and relaxing arguments allow for the user to supply
numeric vectors of any length. By default, these arguments are
rising = c(10, 90) and relaxing = c(90, 50). Numbers in each
of these correspond to percent values and capture time and force at that
percent of the corresponding curve. These values can be replaced by those
that the user specifies and do not necessarily need to have length = 2. But
please note that 0 and 100 should not be used, e.g.
rising = seq(10, 90, 5) works, but rising = seq(0, 100, 5)
does not.
A data.frame with the following metrics as columns:
file_ID |
File ID |
time_stim |
Time between beginning of data collection and when stimulation occurs |
force_stim |
Magnitude of force at the onset of stimulation |
time_peak |
Absolute time of peak force, i.e. time between beginning of data collection and when peak force occurs |
force_peak |
Magnitude of peak force |
time_rising_X |
Time between beginning of data collection and X% of force development |
force_rising_X |
Magnitude of force at X% of force development |
time_relaxing_X |
Time between beginning of data collection and X% of force relaxation |
force_relaxing_X |
Magnitude of force at X% of relaxation |
Vikram B. Baliga
Ahn AN, and Full RJ. 2002. A motor and a brake: two leg extensor muscles acting at the same joint manage energy differently in a running insect. Journal of Experimental Biology 205, 379-389.
Other data analyses:
analyze_workloop(),
read_analyze_wl_dir(),
read_analyze_wl()
Other twitch functions:
fix_GR(),
invert_position()
library(workloopR) # import the twitch.ddf file included in workloopR twitch_dat <-read_ddf(system.file("extdata", "twitch.ddf", package = 'workloopR')) # run isometric_timing() to get info on twitch kinetics # we'll use different set points than the defaults analyze_twitch <- isometric_timing(twitch_dat, rising = c(25, 50, 75), relaxing = c(75, 50, 25) ) # see the results analyze_twitchlibrary(workloopR) # import the twitch.ddf file included in workloopR twitch_dat <-read_ddf(system.file("extdata", "twitch.ddf", package = 'workloopR')) # run isometric_timing() to get info on twitch kinetics # we'll use different set points than the defaults analyze_twitch <- isometric_timing(twitch_dat, rising = c(25, 50, 75), relaxing = c(75, 50, 25) ) # see the results analyze_twitch
read_analyze_wl() is an all-in-one function to read in a work loop
file, select cycles, and compute work and power output.
read_analyze_wl(file_name, ...)read_analyze_wl(file_name, ...)
file_name |
A .ddf file that contains data from a single workloop experiment |
... |
Additional arguments to be passed to |
Please be careful with units! See Warnings below. This function
combines read_ddf() with select_cycles() and then ultimately
analyze_workloop() into one handy function.
As detailed in these three functions, possible arguments include: cycle_def - used to specify which part of the cycle is understood as
the beginning and end. There are currently three options: 'lo' for L0-to-L0;
'p2p' for peak-to-peak; and 't2t' for trough-to-trough bworth_order - Filter order for low-pass filtering of Position
via signal::butter prior to finding peak lengths. Default: 2. bworth_freq - Critical frequency (scalar) for low-pass filtering of
Position via signal::butter prior to finding peak lengths.
Default: 0.05. keep_cycles - Which cycles should be retained. Default: 4:6. GR - Gear ratio. Default: 1. M - Velocity multiplier used to positivize velocity; should be either
-1 or 1. Default: -1. vel_bf - Critical frequency (scalar) for low-pass filtering of
velocity via signal::butter. Default: 0.05.
The gear ratio (GR) and velocity multiplier (M) parameters can help correct
for issues related to the magnitude and sign of data collection. By
default, they are set to apply no gear ratio adjustment and to positivize
velocity. Instantaneous velocity is often noisy and the vel_bf
parameter allows for low-pass filtering of velocity data. See
signal::butter() and signal::filtfilt() for details of how
filtering is achieved.
The function returns a list of class analyzed_workloop
that provides instantaneous velocity, a smoothed velocity, and computes work,
instantaneous power, and net power from a work loop experiment. All data are
organized by the cycle number and important metadata are stored as
Attributes.
Within the list, each entry is labeled by cycle and includes:
Time |
Time, in sec |
Position |
Length change of the muscle, corrected for gear ratio, in mm |
Force |
Force, corrected for gear ratio, in mN |
Stim |
When stimulation occurs, on a binary scale |
Cycle |
Cycle ID, as a letter |
Inst_velocity |
Instantaneous velocity, computed from |
Filt_velocity |
Instantaneous velocity, after low-pass filtering, again in meter/sec |
Inst_Power |
Instantaneous power, a product of |
Percent_of_Cycle |
The percent of that particular cycle which has elapsed |
In addition, the following information is stored in the
analyzed_workloop object's attributes:
stimulus_frequency |
Frequency at which stimulus pulses occurred |
cycle_frequency |
Frequency of oscillations (assuming sine wave trajectory) |
total_cycles |
Total number of oscillatory cycles (assuming sine wave trajectory) that the muscle experienced. |
cycle_def |
Specifies what part of the cycle is understood as the beginning and end. There are currently three options: 'lo' for L0-to-L0; 'p2p' for peak-to-peak; and 't2t' for trough-to-trough |
amplitude |
Amplitude of length change (assuming sine wave trajectory) |
phase |
Phase of the oscillatory cycle (in percent) at which stimulation occurred. Somewhat experimental, please use with caution |
position_inverted |
Logical; whether position inversion has been applied) |
units |
The units of measurement for each column in the object after running this function. See Warning |
sample_frequency |
Frequency at which samples were collected |
header |
Additional information from the header |
units_table |
Units from each Channel of the original ddf file |
protocol_table |
Protocol in tabular format; taken from the original ddf file |
stim_table |
Specific info on stimulus protocol; taken from the original ddf file |
stimulus_pulses |
Number of sequential pulses within a stimulation train |
stimulus_offset |
Timing offset at which stimulus began |
gear_ratio |
Gear ratio applied by this function |
file_id |
File name |
mtime |
Time at which file was last modified |
retained_cycles |
Which cycles were retained, as numerics |
summary |
Simple table showing work (in J) and net power (in W) for each cycle |
Most systems we have encountered record Position data in millimeters
and Force in millinewtons, and therefore this function assumes data are
recorded in those units. Through a series of internal conversions, this
function computes velocity in meters/sec, work in Joules, and power in
Watts. If your raw data do not originate in millimeters and millinewtons,
please transform your data accordingly and ignore what you see in the
attribute units.
Vikram B. Baliga
Josephson RK. 1985. Mechanical Power output from Striated Muscle during Cyclic Contraction. Journal of Experimental Biology 114: 493-512.
read_ddf,
select_cycles
analyze_workloop
Other data analyses:
analyze_workloop(),
isometric_timing(),
read_analyze_wl_dir()
Other data import functions:
as_muscle_stim(),
get_wl_metadata(),
read_analyze_wl_dir(),
read_ddf_dir(),
read_ddf()
Other workloop functions:
analyze_workloop(),
fix_GR(),
get_wl_metadata(),
invert_position(),
read_analyze_wl_dir(),
select_cycles(),
summarize_wl_trials(),
time_correct()
library(workloopR) # import the workloop.ddf file included in workloopR and analyze with # a gear ratio correction of 2 and cycle definition of peak-to-peak wl_dat <- read_analyze_wl(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE, GR = 2, cycle_def = "p2p")library(workloopR) # import the workloop.ddf file included in workloopR and analyze with # a gear ratio correction of 2 and cycle definition of peak-to-peak wl_dat <- read_analyze_wl(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE, GR = 2, cycle_def = "p2p")
All-in-one function to import multiple workloop .ddf files from a directory, sort them by mtime, analyze them, and store the resulting objects in an ordered list.
read_analyze_wl_dir(file_path, pattern = "*.ddf", sort_by = "mtime", ...)read_analyze_wl_dir(file_path, pattern = "*.ddf", sort_by = "mtime", ...)
file_path |
Directory in which files are located |
pattern |
Regular expression used to specify files of interest. Defaults to all .ddf files within file_path |
sort_by |
Metadata by which files should be sorted to be in the correct
run order. Defaults to |
... |
Additional arguments to be passed to |
Work loop data files will be imported and then arranged in the order
in which they were run (assuming run order is reflected in mtime).
Chiefly used in conjunction with summarize_wl_trials() and
time_correct() if time correction is desired.
A list containing analyzed_workloop objects, one for each file that is
imported and subsequently analyzed. The list is sorted according to the
sort_by parameter, which by default uses the time of last modification
of each file's contents (mtime).
Most systems we have encountered record Position data in millimeters
and Force in millinewtons, and therefore this function assumes data are
recorded in those units. Through a series of internal conversions, this
function computes velocity in meters/sec, work in Joules, and power in
Watts. If your raw data do not originate in millimeters and millinewtons,
please transform your data accordingly and ignore what you see in the
attribute units.
Shreeram Senthivasan
Josephson RK. 1985. Mechanical Power output from Striated Muscle during Cyclic Contraction. Journal of Experimental Biology 114: 493-512.
read_analyze_wl,
get_wl_metadata,
summarize_wl_trials,
time_correct
Other data analyses:
analyze_workloop(),
isometric_timing(),
read_analyze_wl()
Other data import functions:
as_muscle_stim(),
get_wl_metadata(),
read_analyze_wl(),
read_ddf_dir(),
read_ddf()
Other workloop functions:
analyze_workloop(),
fix_GR(),
get_wl_metadata(),
invert_position(),
read_analyze_wl(),
select_cycles(),
summarize_wl_trials(),
time_correct()
Other batch analyses:
get_wl_metadata(),
summarize_wl_trials(),
time_correct()
library(workloopR) # batch read and analyze files included with workloopR analyzed_wls <- read_analyze_wl_dir(system.file("extdata/wl_duration_trials", package = 'workloopR'), phase_from_peak = TRUE, cycle_def = "p2p", keep_cycles = 2:4)library(workloopR) # batch read and analyze files included with workloopR analyzed_wls <- read_analyze_wl_dir(system.file("extdata/wl_duration_trials", package = 'workloopR'), phase_from_peak = TRUE, cycle_def = "p2p", keep_cycles = 2:4)
read_ddf reads in workloop, twitch, or tetanus experiment data from
.ddf files.
read_ddf( file_name, file_id = NA, rename_cols = list(c(2, 3), c("Position", "Force")), skip_cols = 4:11, phase_from_peak = FALSE, ... )read_ddf( file_name, file_id = NA, rename_cols = list(c(2, 3), c("Position", "Force")), skip_cols = 4:11, phase_from_peak = FALSE, ... )
file_name |
A .ddf file that contains data from a single workloop, twitch, or tetanus experiment |
file_id |
A string identifying the experiment. The file name is used by default. |
rename_cols |
List consisting of a vector of indices of columns to rename and a vector of new column names. See Details. |
skip_cols |
Numeric vector of column indices to skip. See Details. |
phase_from_peak |
Logical, indicating whether percent phase of stimulation should be recorded relative to peak length or relative to L0 (default) |
... |
Additional arguments passed to/from other functions that work
with |
Read in a .ddf file that contains data from an experiment. If
position and force do not correspond to columns 2 and 3 (respectively),
replace "2" and "3" within rename_cols accordingly. Similarly,
skip_cols = 4:11 should be adjusted if more than 11 columns are
present and/or columns 4:11 contain important data.
Please note that there is no correction for gear ratio or further
manipulation of data. See fix_GR to adjust gear ratio. Gear ratio can
also be adjusted prior to analyses within the analyze_workloop()
function, the data import all-in-one function read_analyze_wl(), or
the batch analysis all-in-one read_analyze_wl_dir().
Please also note that organization of data within the .ddf file is assumed to
conform to that used by Aurora Scientific's Dynamic Muscle Control and
Analysis Software. YMMV if using a .ddf file from another source. The
as_muscle_stim() function can be used to generate muscle_stim
objects if data are imported via another function. Please feel free to
contact us with any issues or requests.
An object of class workloop, twitch, or tetanus,
all of which inherit class muscle_stim. These objects behave like
data.frames in most situations but also store metadata from the ddf
as attributes.
The muscle_stim object's columns contain:
Time |
Time |
Position |
Length change of the muscle, uncorrected for gear ratio |
Force |
Force, uncorrected for gear ratio |
Stim |
When stimulation occurs, on a binary scale |
In addition, the following information is stored in the data.frame's
attributes:
sample_frequency |
Frequency at which samples were collected |
pulses |
Number of sequential pulses within a stimulation train |
total_cycles_lo |
Total number of oscillatory cycles (assuming sine wave trajectory) that the muscle experienced. Cycles are defined with respect to initial muscle length (L0-to-L0 as opposed to peak-to-peak). |
amplitude |
amplitude of length change (again, assuming sine wave trajectory) |
cycle_frequency |
Frequency of oscillations (again, assuming sine wave trajectory) |
units |
The units of measurement for each column in the
|
Vikram B. Baliga and Shreeram Senthivasan
Other data import functions:
as_muscle_stim(),
get_wl_metadata(),
read_analyze_wl_dir(),
read_analyze_wl(),
read_ddf_dir()
library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE)library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE)
Uses read_ddf() to read in workloop, twitch, or tetanus experiment
data from multiple .ddf files.
read_ddf_dir(file_path, pattern = "*.ddf", sort_by = "mtime", ...)read_ddf_dir(file_path, pattern = "*.ddf", sort_by = "mtime", ...)
file_path |
Path where files are stored. Should be in the same folder. |
pattern |
Regex pattern for identifying relevant files in the file_path. |
sort_by |
Metadata by which files should be sorted to be in the correct
run order. Defaults to |
... |
Additional arguments to be passed to |
Read in a .ddf file that contains data from an experiment. If
position and force do not correspond to columns 2 and 3 (respectively),
replace "2" and "3" within rename_cols accordingly. Similarly,
skip_cols = 4:11 should be adjusted if more than 11 columns are
present and/or columns 4:11 contain important data.
Please note that there is no correction for gear ratio or further
manipulation of data. See fix_GR to adjust gear ratio. Gear ratio can
also be adjusted prior to analyses within the analyze_workloop()
function, the data import all-in-one function read_analyze_wl(), or
the batch analysis all-in-one read_analyze_wl_dir().
Please also note that organization of data within the .ddf file is assumed to
conform to that used by Aurora Scientific's Dynamic Muscle Control and
Analysis Software. YMMV if using a .ddf file from another source. The
as_muscle_stim() function can be used to generate muscle_stim
objects if data are imported via another function. Please feel free to
contact us with any issues or requests.
A list of objects of class workloop, twitch, or
tetanus, all of which inherit class muscle_stim. These objects
behave like data.frames in most situations but also store metadata
from the ddf as attributes.
Each muscle_stim object's columns contain:
Time |
Time |
Position |
Length change of the muscle, uncorrected for gear ratio |
Force |
Force, uncorrected for gear ratio |
Stim |
When stimulation occurs, on a binary scale |
In addition, the following information is stored in each data.frame's
attributes:
sample_frequency |
Frequency at which samples were collected |
pulses |
Number of sequential pulses within a stimulation train |
total_cycles_lo |
Total number of oscillatory cycles (assuming sine wave trajectory) that the muscle experienced. Cycles are defined with respect to initial muscle length (L0-to-L0 as opposed to peak-to-peak). |
amplitude |
amplitude of length change (again, assuming sine wave trajectory) |
cycle_frequency |
Frequency of oscillations (again, assuming sine wave trajectory) |
units |
The units of measurement for each column in the
|
Vikram B. Baliga and Shreeram Senthivasan
Other data import functions:
as_muscle_stim(),
get_wl_metadata(),
read_analyze_wl_dir(),
read_analyze_wl(),
read_ddf()
library(workloopR) # import a set of twitch .ddf files included in workloopR workloop_dat <-read_ddf_dir(system.file("extdata/wl_duration_trials", package = 'workloopR'))library(workloopR) # import a set of twitch .ddf files included in workloopR workloop_dat <-read_ddf_dir(system.file("extdata/wl_duration_trials", package = 'workloopR'))
Retain data from a work loop experiment based on position cycle
select_cycles( x, cycle_def, keep_cycles = 4:6, bworth_order = 2, bworth_freq = 0.05, ... )select_cycles( x, cycle_def, keep_cycles = 4:6, bworth_order = 2, bworth_freq = 0.05, ... )
x |
A |
cycle_def |
A string specifying how cycles should be defined; one of: "lo", "p2p", or "t2t". See Details more info |
keep_cycles |
The indices of the cycles to keep. Include 0 to keep data identified as being outside complete cycles |
bworth_order |
Filter order for low-pass filtering of |
bworth_freq |
Critical frequency (scalar) for low-pass filtering of
|
... |
Additional arguments passed to/from other functions that make use
of |
select_cycles() subsets data from a workloop trial by
position cycle. The cycle_def argument is used to specify which part
of the cycle is understood as the beginning and end. There are currently
three options:
'lo' for L0-to-L0;
'p2p' for peak-to-peak; and
't2t' for trough-to-trough
Peaks are identified using pracma::findpeaks(). L0 points on the
rising edge are found by finding the midpoints between troughs and the
following peak. However the first and last extrema and L0 points may be
misidentified by this method. Please plot your Position cycles to
ensure the edge cases are identified correctly.
The keep_cycles argument is used to determine which cycles (as
defined by cycle_def should be retained in the final dataset. Zero
is the index assigned to all data points that are determined to be outside
a complete cycle.
The muscle_stim object (x) must be a workloop,
preferably read in by one of our data import functions. Please see
documentation for as_muscle_stim() if you need to manually construct
a muscle_stim object from another source.
A workloop object with rows subsetted by the chosen position
cycles. A Cycle column is appended to denote which cycle each time
point is associated with. Finally, all attributes from the input
workloop object are retained and one new attribute is added to
record which cycles from the original data were retained.
Vikram B. Baliga and Shreeram Senthivasan
analyze_workloop,
read_analyze_wl,
read_analyze_wl_dir
Other data transformations:
fix_GR(),
invert_position()
Other workloop functions:
analyze_workloop(),
fix_GR(),
get_wl_metadata(),
invert_position(),
read_analyze_wl_dir(),
read_analyze_wl(),
summarize_wl_trials(),
time_correct()
library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE) # select cycles 3 through 5 via the peak-to-peak definition wl_selected <- select_cycles(wl_dat, cycle_def = "p2p", keep_cycles = 3:5) # are the cycles of (approximately) the same length? summary(as.factor(wl_selected$Cycle))library(workloopR) # import the workloop.ddf file included in workloopR wl_dat <-read_ddf(system.file("extdata", "workloop.ddf", package = 'workloopR'), phase_from_peak = TRUE) # select cycles 3 through 5 via the peak-to-peak definition wl_selected <- select_cycles(wl_dat, cycle_def = "p2p", keep_cycles = 3:5) # are the cycles of (approximately) the same length? summary(as.factor(wl_selected$Cycle))
Summarize important info from work loop files stored in the same folder
(e.g. a sequence of trials in an experiment) including experimental
parameters, run order, and mtime.
summarize_wl_trials(wl_list)summarize_wl_trials(wl_list)
wl_list |
List of |
If several files (e.g. successive trials from one experiment) are
stored in one folder, use this function to obtain summary stats and
metadata and other parameters. This function requires a list of
analyze_workloop objects, which can be readily obtained by first
running read_analyze_wl_dir() on a specified directory.
A data.frame of information about the collection of workloop files.
Columns include:
File_ID |
Name of the file |
Cycle_Frequency |
Frequency of Position change |
Amplitude |
amplitude of Position change |
Phase |
Phase of the oscillatory cycle (in percent) at which stimulation occurred. Somewhat experimental, please use with caution |
Stimulus_Pulses |
Number of stimulation pulses |
mtime |
Time at which file's contents were last changed ( |
Mean_Work |
Mean work output from the selected cycles |
Mean_Power |
Net power output from the selected cycles |
Vikram B. Baliga and Shreeram Senthivasan
Josephson RK. 1985. Mechanical Power output from Striated Muscle during Cyclic Contraction. Journal of Experimental Biology 114: 493-512.
read_analyze_wl_dir,
get_wl_metadata,
time_correct
Other workloop functions:
analyze_workloop(),
fix_GR(),
get_wl_metadata(),
invert_position(),
read_analyze_wl_dir(),
read_analyze_wl(),
select_cycles(),
time_correct()
Other batch analyses:
get_wl_metadata(),
read_analyze_wl_dir(),
time_correct()
library(workloopR) # batch read and analyze files included with workloopR analyzed_wls <- read_analyze_wl_dir(system.file("extdata/wl_duration_trials", package = 'workloopR'), phase_from_peak = TRUE, cycle_def = "p2p", keep_cycles = 2:4 ) # now summarize summarized_wls <- summarize_wl_trials(analyzed_wls)library(workloopR) # batch read and analyze files included with workloopR analyzed_wls <- read_analyze_wl_dir(system.file("extdata/wl_duration_trials", package = 'workloopR'), phase_from_peak = TRUE, cycle_def = "p2p", keep_cycles = 2:4 ) # now summarize summarized_wls <- summarize_wl_trials(analyzed_wls)
Correct for potential degradation of muscle over time.
time_correct(x)time_correct(x)
x |
A |
This function assumes that across a batch of successive trials, the stimulation parameters for the first and final trials are identical. If not, DO NOT USE. Decline in power output is therefore assumed to be a linear function of time. Accordingly, the difference between the final and first trial's (absolute) power output is used to 'correct' trials that occur in between, with explicit consideration of run order and time elapsed (via mtime). A similar correction procedure is applied to work.
A data.frame that additionally contains:
Time_Corrected_Work |
Time corrected work output, transformed from
|
Time_Corrected_Power |
Time corrected net power output, transformed
from |
And new attributes:
power_difference |
Difference in mass-specific net power output between the final and first trials. |
time_difference |
Difference in mtime between the final and first trials. |
time_correction_rate |
Overall rate; |
Vikram B. Baliga and Shreeram Senthivasan
Other workloop functions:
analyze_workloop(),
fix_GR(),
get_wl_metadata(),
invert_position(),
read_analyze_wl_dir(),
read_analyze_wl(),
select_cycles(),
summarize_wl_trials()
Other batch analyses:
get_wl_metadata(),
read_analyze_wl_dir(),
summarize_wl_trials()
library(workloopR) # batch read and analyze files included with workloopR analyzed_wls <- read_analyze_wl_dir(system.file("extdata/wl_duration_trials", package = 'workloopR'), phase_from_peak = TRUE, cycle_def = "p2p", keep_cycles = 2:4) # now summarize summarized_wls <- summarize_wl_trials(analyzed_wls) # mtimes within the package are not accurate, so we'll supply # our own vector of mtimes summarized_wls$mtime <- read.csv( system.file( "extdata/wl_duration_trials/ddfmtimes.csv", package="workloopR"))$mtime # now time correct timecor_wls <- time_correct(summarized_wls) timecor_wlslibrary(workloopR) # batch read and analyze files included with workloopR analyzed_wls <- read_analyze_wl_dir(system.file("extdata/wl_duration_trials", package = 'workloopR'), phase_from_peak = TRUE, cycle_def = "p2p", keep_cycles = 2:4) # now summarize summarized_wls <- summarize_wl_trials(analyzed_wls) # mtimes within the package are not accurate, so we'll supply # our own vector of mtimes summarized_wls$mtime <- read.csv( system.file( "extdata/wl_duration_trials/ddfmtimes.csv", package="workloopR"))$mtime # now time correct timecor_wls <- time_correct(summarized_wls) timecor_wls
Mostly meant for internal use in our analysis functions, but made available
for other use cases. Accordingly, it does not strictly rely on objects of
class muscle_stim.
trapezoidal_integration(x, f)trapezoidal_integration(x, f)
x |
a variable, e.g. vector of positions |
f |
integrand, e.g. vector of forces |
In the functions analyze_workloop(), read_analyze_wl()
, and read_analyze_wl_dir(), work is calculated as the difference
between the integral of the upper curve and the integral of the lower curve
of a work loop.
A numerical value indicating the value of the integral.
Vikram B. Baliga
Atkinson, Kendall E. (1989), An Introduction to Numerical Analysis (2nd ed.), New York: John Wiley & Sons
analyze_workloop,
read_analyze_wl,
read_analyze_wl_dir
# create a circle centered at (x = 10, y = 20) with radius 2 t <- seq(0, 2 * pi, length = 1000) coords <- t(rbind(10 + sin(t) * 2, 20 + cos(t) * 2)) # use the function to get the area trapezoidal_integration(coords[, 1], coords[, 2]) # does it match (pi * r^2)? 3.14159265358 * (2^2) # very close# create a circle centered at (x = 10, y = 20) with radius 2 t <- seq(0, 2 * pi, length = 1000) coords <- t(rbind(10 + sin(t) * 2, 20 + cos(t) * 2)) # use the function to get the area trapezoidal_integration(coords[, 1], coords[, 2]) # does it match (pi * r^2)? 3.14159265358 * (2^2) # very close