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Calculate Comprehensive Sleep Metrics from Activity Data

Source: R/calcTradSleep.R
calcTradSleep.Rd

Processes activity data to calculate traditional sleep metrics including sleep duration, activity index during wakefulness, brief awakenings, and detailed sleep bout characteristics. This function implements standard sleep analysis metrics commonly used in Drosophila sleep research.

A "brief awakening" is defined as a single time point of movement that is immediately preceded and followed by immobility, potentially indicating fragmented or shallow sleep.

Usage

calcTradSleep(dt_test)

Arguments

dt_test

A data.table containing activity and sleep state data, typically the output from HMMDataPrep. Must contain the following columns:

  • id: Unique identifier for each individual

  • moving: Logical indicator of movement

  • asleep: Logical indicator of sleep state

  • activity: Numeric activity count

  • phase: Factor with levels "Light" and "Dark"

  • day: Integer day number

  • genotype: Character or factor indicating genotype

  • replicate: Character or factor indicating replicate ID

Value

A named list containing seven data.table objects with sleep metrics (all time values in minutes):

brief_awakenings_data

Original data with added brief_awakenings column (logical)

sleep_summary_phase

Total sleep time per phase (Light/Dark) and day for each individual

sleep_summary_whole_day

Total sleep time per day for each individual

activity_index_phase

Mean activity during wakefulness per phase and day (total activity / time awake)

activity_index_whole_day

Mean activity during wakefulness per day

bout_summary_day

Detailed sleep bout metrics per day including:

  • latency: Time to first sleep bout (minutes from day start)

  • first_bout_length: Duration of first sleep bout

  • latency_to_longest_bout: Time to longest bout

  • length_longest_bout: Duration of longest bout

  • n_bouts: Number of sleep bouts

  • mean_bout_length: Average bout duration

  • total_bout_length: Total sleep time from bouts

bout_summary_phase

Sleep bout metrics per phase and day

Details

The function calculates metrics separately for light and dark phases based on the phase column. Sleep bouts are identified using bout_analysis from the sleepr package.

Activity index provides a measure of movement intensity during wake periods, which can indicate arousal threshold or sleep depth.

See also

HMMDataPrep for preparing input data bout_analysis for bout detection algorithm

Examples

if (FALSE) { # \dontrun{
# Assume 'processed_data' is output from HMMDataPrep()
sleep_metrics <- calcTradSleep(processed_data)

# Access individual metric tables
daily_bouts <- sleep_metrics$bout_summary_day
phase_sleep <- sleep_metrics$sleep_summary_phase

# View brief awakening data
head(sleep_metrics$brief_awakenings_data)

# Summary statistics
summary(sleep_metrics$sleep_summary_whole_day$time_spent_sleeping)
} # }