Description Usage Arguments Details Value References Examples
Classifies wear time vs. non-wear time based on a vector of accelerometer count values.
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counts |
Integer vector with accelerometer count values. |
window |
Integer value specifying minimum length of a non-wear period. |
tol |
Integer value specifying tolerance for non-wear algorithm, i.e. number of seconds/minutes with non-zero counts allowed during a non-wear interval. |
tol_upper |
Integer value specifying maximum count value for a second/minute with non-zero counts during a non-wear interval. |
nci |
Logical value for whether to use algorithm from NCI's SAS programs. See Details. |
days_distinct |
Logical value for whether to treat each day of data as
distinct, as opposed to analyzing the entire monitoring period as one
continuous segment. For minute-to-minute counts, strongly recommend setting
to |
units_day |
Integer value specifying how many data point are in a day. Typically either 1440 or 86400 depending on whether count values are minute-to-minute or second-to-second. |
If nci = FALSE
, the algorithm uses a moving window to go through
every possible interval of length window
in counts
. Any
interval in which no more than tol
counts are non-zero, and those
are still < tol.upper
, is classified as non-wear time.
If nci = TRUE
, non-wear time is classified according to the algorithm
used in the NCI's SAS programs. Briefly, this algorithm defines a non-wear
period as an interval of length window
that starts with a count value
of 0, does not contain any periods with (tol + 1)
consecutive
non-zero count values, and does not contain any counts > tol.upper
.
If these criteria are met, the non-wear period continues until there are
(tol + 1)
consecutive non-zero count values or a single count value >
tol.upper
.
Integer vector with 1's for valid wear time and 0's for non-wear time.
National Cancer Institute. Risk factor monitoring and methods: SAS programs for analyzing NHANES 2003-2004 accelerometer data. Available at: http://riskfactor.cancer.gov/tools/nhanes_pam. Accessed Aug. 19, 2018.
Acknowledgment: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-0940903.
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