Nothing
## ----setup, echo = FALSE------------------------------------------------------
knitr::opts_chunk$set(
echo = TRUE, warning = FALSE, message = FALSE, collapse = TRUE,
comment = "#>", out.width = "75%", fig.asp = 1 / 1.6, fig.width = 5
)
pckg <- c("actigraph.sleepr", "dplyr", "lubridate", "ggplot2")
inst <- suppressMessages(lapply(pckg, library, character.only = TRUE))
theme_set(theme_light())
## -----------------------------------------------------------------------------
file_10s <- system.file("extdata", "ActiSleepPlus-RawData-Day01.agd",
package = "actigraph.sleepr"
)
agdb_60s <- read_agd(file_10s) %>%
collapse_epochs(60) %>%
mutate(date = lubridate::as_date(timestamp)) %>%
select(date, timestamp, starts_with("axis")) %>%
group_by(date)
agdb_60s
## -----------------------------------------------------------------------------
periods_nonwear <- agdb_60s %>% apply_troiano(min_period_len = 45)
periods_nonwear
## -----------------------------------------------------------------------------
tail(attributes(periods_nonwear), 8)
## -----------------------------------------------------------------------------
periods_nonwear %>% filter(length >= 60)
## -----------------------------------------------------------------------------
# Find the periods during which the device was worn
periods_wear <- complement_periods(
periods_nonwear, agdb_60s,
period_start, period_end
)
periods_wear
# Label each epoch with the period_id of the wear period it falls in
# or with NA if the epoch falls outside a wear period
agdb_wear <- combine_epochs_periods(
agdb_60s, periods_wear,
period_start, period_end
)
agdb_wear
# Once we add the wear/nonwear information, it is straightforward to
# compute summary statistics or join with external minute-by-minute data
agdb_wear %>%
group_by(period_id, .add = TRUE) %>%
summarise(
time_worn = n(),
ave_counts = mean(axis1),
.groups = "drop_last"
)
## -----------------------------------------------------------------------------
periods_nonwear <- agdb_60s %>% apply_choi(
min_period_len = 45,
min_window_len = 10
)
periods_nonwear
## -----------------------------------------------------------------------------
tail(attributes(periods_nonwear), 5)
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