acc (version 1.0.2)

rtb: rtb

Description

Summarizes accelerometer data by real time bouts

Usage

rtb(data, type, tri, spuriousDef, nonwearDef, 
                boutsizeSed, toleranceSed,  
                mvpa, boutsizeMVPA, toleranceMVPA)

Arguments

type

Whether to return bouts information for sedentary or MVPA. Choose either 'sedentary' or 'MVPA'

data

Data which consists of two columns [TimeStamp,counts]

tri

Whether the data is from a tri-axial accelerometer. Default is tri='FALSE'.

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 an

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 observatio

boutsizeSed

Bout size used in summarizing sedentary minutes per day. Default is boutsizeSed=10.

toleranceSed

Whether to allow some observations outside the cut point for sedentary activity within the bout. Default is toleranceSed='FALSE'.

mvpa

Cut point for moderate-vigorous physical activity (MVPA). Options are 'Freedson'(mvpa = 1952), 'Swartz'(mvpa = 574), 'Copland' (mvpaCP = 1041), 'Hall' (mvpa = 809), or user can specify a numeric value instead (e.g. 1952). Default is mvpa='Freedson'.

boutsizeMVPA

Bout size used in summarizing MVPA minutes per day. Default is boutsizeMVPA = 10.

toleranceMVPA

Whether to allow up to two observations outside the cut point for MVPA within the bout. Default is toleranceMVPA='TRUE'.

Value

• Two columns are returned, consisting of: TimeStamp Time stamp of date and time Minutes Minutes of either sedentary activity or MVPA for the observed bout

Examples

##
## Simulate a dataset for two days, for an individual with low MVPA level.
##
mvpaLowData <- simAcc(minutes=(60*24*2),mvpaLevel='low')
summarySed <- rtb(data=mvpaLowData,type='sedentary')
summarySed
summaryMVPA <- rtb(data=mvpaLowData,type='mvpa')
summaryMVPA


##
## Simulate a dataset for two days, for an individual with high MVPA level.
##
mvpaHighData <- simAcc(minutes=(60*24*2),mvpaLevel='high')
summarySed <- rtb(data=mvpaHighData,type='sedentary')
summarySed
summaryMVPA <- rtb(data=mvpaHighData,type='mvpa')
summaryMVPA