R/PhysicalActivity-package.R

In PhysicalActivity: Process Accelerometer Data for Physical Activity Measurement

#' Process Accelerometer Data for Physical Activity Measurement
#'
#' It provides a function \code{\link{wearingMarking}} for classification of monitor
#' wear and nonwear time intervals in accelerometer data collected to assess
#' physical activity. The package also contains functions for making plot for
#' accelerometer data and obtaining the summary of various information including
#' daily monitor wear time and the mean monitor wear time during valid days.
#' 
#' The revised package version 0.2-2 improved the functions in the previous version
#' regarding speed and robustness. In addition, several functions were added: 
#' \code{\link{markDelivery}} can classify days for ActiGraph delivery by mail; 
#' \code{\link{markPAI}} can categorize physical activity intensity level based on
#' user-defined cut-points of accelerometer counts. It also supports importing ActiGraph
#' AGD files with \code{\link{readActigraph}} and \code{\link{queryActigraph}} functions.
#' The package also better supports time zones and daylight saving.
#'
#' Classify wear and nonwear time status for accelerometer data by
#' epoch-by-epoch basis by \code{\link{wearingMarking}}.
#'
#' Classify mail delivery and non-delivery day status for accelerometer data 
#' by \code{\link{markDelivery}}.
#' 
#' Three options are available for the package: \code{pa.validCut=600},
#' \code{pa.timeStamp='TimeStamp'}, and \code{pa.cts='axis1'}. When these 
#' options are specified (as in \code{\link{markDelivery}}), the other 
#' functions will automatically respect these values as defaults. For 
#' instance, the count variable in \code{data(dataSec)} is "counts".
#' Running \code{options(pa.cts='counts')} allows the user to avoid specifying the 
#' "cts" argument in \code{\link{wearingMarking}}. The options for \code{validCut} and
#' \code{timeStamp} are rarely changed.
#'
#' Shiny app called \pkg{Actigraph} can be used to visualize accelerometer data
#' and summarize the data.  Please see \url{https://github.com/couthcommander/PhysicalActivityShiny}.
#'
#' @docType package
#'
#' @author Leena Choi \email{leena.choi@@Vanderbilt.Edu},
#' Cole Beck \email{cole.beck@@vumc.org},
#' Zhouwen Liu \email{zhouwen.liu@@vumc.org},
#' Charles E. Matthews \email{Charles.Matthews2@@nih.gov}, and
#' Maciej S. Buchowski \email{maciej.buchowski@@Vanderbilt.Edu}
#'
#' Maintainer: Leena Choi \email{leena.choi@@Vanderbilt.Edu}
#'
#' @references Choi L, Liu Z, Matthews CE, Buchowski MS. 
#' Validation of accelerometer wear and nonwear time classification algorithm.
#' Med Sci Sports Exerc. 2011 Feb;43(2):357-64.
#'
#' Choi L, Ward SC, Schnelle JF, Buchowski MS. 
#' Assessment of wear/nonwear time classification algorithms for triaxial accelerometer.
#' Med Sci Sports Exerc. 2012 Oct;44(10):2009-16.
#'
#' Choi L, Chen KY, Acra SA, Buchowski MS. 
#' Distributed lag and spline modeling for predicting energy expenditure from 
#' accelerometry in youth. J Appl Physiol. 2010 Feb;108(2):314-27.
#'
#' @concept accelerometer data process
#' @concept wear and nonwear classification
#' @concept mail delivery day classification
#' @importFrom graphics abline plot text mtext
#' @importFrom stats predict pt sd qnorm qt quantile var
#' @importFrom utils getFromNamespace
#'
#' @examples
#' data(dataSec)
#'
#' mydata1m = dataCollapser(dataSec, TS = "TimeStamp", col = "counts", by = 60)
#' options(pa.cts = 'counts') # change cnt variable from "axis1" to "counts"
#' data1m = wearingMarking(dataset = mydata1m, frame = 90)
#'
#' sumVct(data1m, id="sdata1m")
#'
#' plotData(data=data1m)
#'
#' summaryData(data=data1m, validCut=600, perMinuteCts=1, markingString = "w")
"_PACKAGE"

.onLoad <- function(libname, pkgname) {
    myopts <- list(
        pa.validCut = 600,
        pa.timeStamp = "TimeStamp",
        pa.cts = "axis1"
    )
    options(myopts)
    invisible()
}