Using Rsleep and SleepCycles Packages To Detect Sleep Cycles
Source:vignettes/Using_rsleep_and_SleepCycles_packages_to_detect_sleep_cycles.Rmd
Using_rsleep_and_SleepCycles_packages_to_detect_sleep_cycles.RmdThe SleepCycles package [1] has been specifically developed to identify sleep cycles [2] and their corresponding NREM and REM components (known as (N)REM periods) from data that has been categorized based on AASM criteria for sleep staging [3].
In the other hand, the rsleep package reads and analyze sleep data in various formats.
This vignettte describes how to combine SleepCycles and
rsleep packages to identify sleep cycles in sleep data and
leverage this material in sleep data analysis pipelines.
Hypnogram
Sleep cycles can be identified from hypnograms. 15012016HD.csv
contains a hypnogram scored by a sleep expert using Noxturnal
software published by ResMed. The rsleep package provides the
read_events_noxturnal() function to read hypnograms in this
format.
library(rsleep)
if(!file.exists("15012016HD.csv")){
download.file(
url = "https://rsleep.org/data/15012016HD.csv",
destfile = "15012016HD.csv")}
events <- rsleep::read_events_noxturnal("15012016HD.csv")
unlink("15012016HD.csv")
events = hypnogram(events)
rsleep::plot_hypnogram(events)
Formatting
Tne SleepCycles package only reads directories and files
in specific format. Hypnograms must be converted in the appropriate
arrangement before being written on disk in an explicit folder:
events.vmrk = data.frame(Description = as.character(events$event))
events.vmrk$Description[events.vmrk$Description == "AWA"] = 0
events.vmrk$Description[events.vmrk$Description == "N1"] = 1
events.vmrk$Description[events.vmrk$Description == "N2"] = 2
events.vmrk$Description[events.vmrk$Description == "N3"] = 3
events.vmrk$Description[events.vmrk$Description == "REM"] = 5
events.vmrk$Description = as.integer(events.vmrk$Description)
events.vmrk$Type = "SleepStage"
events.vmrk = events.vmrk[,c(2,1)]
newdir <- file.path(tempdir(),"SleepCycles")
dir.create(newdir, showWarnings = FALSE)
write.table(
events.vmrk,
file = paste(newdir, "events.txt", sep = "/"),
row.names=FALSE,
col.names = TRUE,
quote = FALSE,
sep = ",")Detection
The SleepCycles() function can now read the created
directory and detect sleep cycles in the saved hypnograms. The original
version of the function interactively asks the file format to the user
and writes the result to a file in the same directory. The forked
version boupetch/SleepCycles modifies this behaviour to
take the format as parameters and return directly the results as a
dataframe, making the pipeline easier to automate.
devtools::install_github("boupetch/SleepCycles")
#> Skipping install of 'SleepCycles' from a github remote, the SHA1 (4fd13643) has not changed since last install.
#> Use `force = TRUE` to force installation
cycles = SleepCycles::SleepCycles(
p = newdir,
filetype = "txt",
plot = FALSE)
#> [1] 1
unlink(newdir, recursive=TRUE)
head(cycles)
#> Type SleepCycle SleepStages N_REM percentile
#> 1 SleepStage NA 0 NA NA
#> 2 SleepStage NA 0 NA NA
#> 3 SleepStage NA 0 NA NA
#> 4 SleepStage NA 0 NA NA
#> 5 SleepStage NA 0 NA NA
#> 6 SleepStage NA 0 NA NAIndicators
Binding the resulting dataframe to the original hypnogram
events and performing aggregations provides valuable sleep
macrostructure indicators:
hypnogram.full = cbind(events, cycles)
# Number of cycles
max(hypnogram.full$SleepCycle, na.rm = TRUE)
#> [1] 7
# Duration of each cycle
hypnogram.agg = aggregate(
event ~ SleepCycle,
data = hypnogram.full,
FUN = length)
hypnogram.agg$minutes = hypnogram.agg$event/2
hypnogram.agg
#> SleepCycle event minutes
#> 1 1 301 150.5
#> 2 2 186 93.0
#> 3 3 152 76.0
#> 4 4 202 101.0
#> 5 5 175 87.5
#> 6 6 161 80.5
#> 7 7 172 86.0
# Composition of each cycle
cycles.comp = aggregate(
SleepStages ~ SleepCycle + event,
data = hypnogram.full,
FUN = length)
cycles.comp = reshape(
data = cycles.comp,
direction = "wide",
timevar = "event",
idvar = "SleepCycle")
cycles.comp
#> SleepCycle SleepStages.N3 SleepStages.N2 SleepStages.N1 SleepStages.REM
#> 1 1 98 60 9 71
#> 2 2 108 56 NA 21
#> 3 4 6 114 NA 81
#> 4 5 5 73 NA 96
#> 5 6 39 62 NA 54
#> 8 3 NA 91 NA 60
#> 12 7 NA 77 NA 93
#> SleepStages.AWA
#> 1 63
#> 2 1
#> 3 1
#> 4 1
#> 5 6
#> 8 1
#> 12 2