accBatch {acc}

Summarizes multiple accelerometer datafiles

Description

Summarizes multiple accelerometer datafiles in a batch mode. Summary can be provided for multiple types of physical activities, by day.

Usage

accBatch(path, tri, axis, spuriousDef, nonwearDef, minWear,
    patype, pacut, epoch, boutsize, tolerance)

Arguments

path

Path to accelerometer data files read in by function readCounts or readCountsBath. Files in this path can have both uni-axial and tri-axial data. If at least one tri-axial data is present in the path, please specify tri='TRUE' and axis. This information will be used to summarize tri-axial data.

tri

Is there at least one dataset from a tri-axial accelerometer in the folder? Default is tri=‘TRUE’. If tri=‘TRUE’ then option ‘axis’ should be specified. Default axis is axis='vm'.

axis

If the data is from a tri-axial device, this option is applied. Options are ‘x’,‘y’,‘z’,‘sum’, or ‘vm’. Options ‘x’, ‘y’, or ‘z’ can be spefied to summarize data using only data from a single axis. If the option 'vm' is used, the square root of the squared sum of counts from three axes (i.e. \sqrt{{x}^{2}+{y}^{2}+{z}^{2}}) are used for the summary. If the option 'sum' is used, sum of the counts from three axes are used.

spuriousDef

Definition of spurious observation. Defined as minutes of consecutive zeros. For example, if spuriousDef = 20, this means that an observation point will be determined as a spurious observation if there are consequtive counts of at least 20 zeros before and after the single non-zero observation. Default is spuriousDef = 20.

nonwearDef

Definition of non-wear time. Defined as minutes of consecutive zeros. For example, if nonwearDef=60, this means that a period will be defined as non-wear time if there are at least 60 consecutive zeros. Default is nonwearDef=60. To consider all observations as wear time specify nonwearDef=‘Inf’

minWear

Minimum wear time definition. Defined as minutes of wear time. or example, if minWear = 600, this means that a day will be considered valid only if the wear time is at least 600 minutes. Default is minWear = 600. To return summary for all dates in the data, set minWear = 0.

patype

Types of physical activity for summary. For example, to summarize sedentary and moderate-vigorous physical activities, user specifies patype=c(‘Sedentary’,‘MVPA’). This labels the summary accordingly.

pacut

Cut points to be used for the physical activity type. For example, if the user specified patype=c(‘Sedentary’,‘MVPA’), pacut can be specified as pacut=c(c(0,99),c(1952,Inf)). The options requires to have a lower and a upper limit for each activity type (i.e. c(0,99) for sedentary activity). The specified interval includes its lower and upper endpoints (it is a closed inerval).

boutsize

Boutsize to summarize a physical activity. If multiple patype is specified, boutsize should be for each one (e.g., if patype=c(‘Sedentary’,‘MVPA’) then one can use boutsize=c(10,10)).

epoch

Epoch size. Default is '1 min'. Other epoch size can be specified using this option (e.g., '1 sec')

tolerance

Whether two observations outside the physical activity should be permitted in summarizing a physical activity. If multiple patype is specified, tolerance should be for each one (e.g., if patype=c(‘Sedentary’,‘MVPA’) then one can use tolerance=c(‘FALSE’,‘TRUE’)).

Value

A folder ‘summaryfiles’ is created within the specified path. In the folder, summary files are saved by the same filenames as in the accelerometer data for valid days which consists of columns [Date, SedentaryMinutes, wearTime, numberOfBoutsSed, mvpaMinutes, numberOfBoutsMVPA]

Author(s)

Jaejoon Song <[e-mail]>

References

Choi, L., Liu, Z., Matthews, C.E. and Buchowski, M.S. (2011). Validation of Accelerometer Wear and Nonwear Time Classification Algorithm. Med Sci Sports Exerc, 43(2):357-64.

Hall, K. S., Howe, C. A., Rana, S. R., Martin, C. L., and Morey, M. C. (2013). METs and Accelerometry of Walking in Older Adults: Standard versus Measured Energy Cost. Medicine and Science in Sports and Medicine, 45(3). 574-82.

Freedson, P., Melanson, E., and Sirard, J. (1998). Calibration of the Computer Sciences and Applications, Inc. accelerometer. Medicine and Science in Sports and Exercercise, 30(5):777-81.

Swartz, A. M., Strath, S. J., Bassett, D. R. Jr., O'Brien, W. L., King, G. A., and Ainsworth, B. E. (2000). Estimation of energy expenditure using CSA accelerometers at hip and wrist sites. Medicine and Science in Sports and Exercercise, 32: S450-456.

Copeland, J. L., and Esliger, D. W. (2009). Accelerometer assessment of physical activity in active, healthy older adults. J Aging Phys Act, 17: 17-30.

Examples

##
## Example
##
## Not run: 
mypath <- "C:/Accelerometry files/readfiles"
accBatch(path=mypath, tri='TRUE', axis='vm',
                     spuriousDef=20, nonwearDef=60, minWear=600, 
                     patype=c('Sedentary','MVPA'),pacut=c(c(0,99),c(1952,Inf)), 
                     boutsize=c(10,10), tolerance=c('FALSE','TRUE'))

## End(Not run)