Nothing
M30
: the count value (in counts/epoch duration) at and above which the most active 30 minutes are accumulated over the day.compute_peak_step_acc()
) to compute peak step accumulation only when there is the minimum number of minutes required to perform computation. It returns NA otherwise.compute_mx()
) to compute MX metrics only when there is the minimum amount of time required to perform the targetted computation. It returns NA otherwise.compute_accumulation_metrics()
function.dplyr::left_join()
function following the release of dplyr package v1.1.0.recap_by_day()
function now returns a list, not a dataframe.tbl_agd
.create_fig_res_by_day()
now allows to visualise all metrics by day (activity volume, step accumulation, intensity distribution).intersex
and prefer not to say
categories to provide a more inclusive classification of sex. As it seems there is no scientific study about what should be the calculation of resting and activity energy expenditures for intersex people, the values provided for Basal metabolic rate (BMR) and METs are the averages of two values: the value that would be computed for a male, and the value that would be computed for a female. For people reporting prefer not to say
, computations for females are used by default.undefined
or chooses the prefer not to say
option, then an equation for females is used. If the patient falls into the intersex
category, then the average of the results for a male and for a female of the considered age is used (WARNING: At the time of writing this guide, there is no scientific data to justify any calculation for intersex people).".undefined
or chooses the prefer not to say
option, then equations including sex information, when selected, are used as if the patient were a female; when the intersex
category is used, an average of the METs related respectively to a male and to a female is used with the equations using sex information; of note, at the time of writing this guide, there is no scientific data to justify any calculation for intersex people);".compute_bmr()
and compute_mets()
functions now use the dplyr::case_when()
function to determine the appropriate value of BMR and METs, respectively.prepare_dataset()
function imports data using the read_agd()
function (instead of the PhysicalActivity::readActigraph()
function). This modification now allows to import data from the GT3X device (previously only data from GT3X+ and newer devices could be used). This was not possible before because the structure of the .agd file obtained with a GT3X device is not accepted by the PhysicalActivity::readActigraph()
function. size
arguments of the internal geom_line()
, geom_segment()
and geom_rect()
functions by linewidth
arguments in relation to the v3.4.0 {ggplot2}
update.as.character()
by format()
in the mark_wear_time()
function so that there is no more error when checking for R dev versions.verify_fa = FALSE
to icon()
functions in the UI to remove an error message that appeared when running the app.mark_intensity()
function: the intensity category numbers associated to the Nonwear, SED, LPA, and MVPA categories (that are present only in the exported marked whole dataset when using the app) were not as expected because they were obtained by converting a factor vector to a numeric vector. Now the conversion is done from a character vector to a numeric vector, which keeps the numerical order as expected. This error had no impact on the results, nor on the figures provided by the package/app. The exported marked dataset has now the corrected intensity category numbers, that is: 0 for Nonwear, 1 for SED, 2 for LPA, and 3 for MVPA.NEWS.md
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