extract_sleep_metrics

From minute-level data with sleep/wake labels (<code>label.sw</code> 1 = sleep, 0 = wake),
extracts sleep/wake onsets, episode durations, circular SDs of onset times,
Sleep Regularity Index (SRI), cosinor parameters, day/night variance ratio,
and nonparametric metrics (RA, IS, IV, L5, M10). Returns one row per episode
with scalar metrics repeated per row (tidy format).

A generic sleep–wake cycle detection algorithm for analyzing unlabeled actigraphy data.
The algorithm has been validated against event markers using data from the Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study,
and its methodological details are described in Chen and Sun (2024) <doi:10.1098/rsos.231468>.
The package provides functions to estimate sleep metrics (e.g., sleep and wake onset times) and circadian rhythm metrics
(e.g., mesor, phasor, interdaily stability, intradaily variability), as well as tools for screening actigraphy quality,
fitting cosinor models, and performing parametric change point detection.
The workflow can also be used to segment long actigraphy sequences into regularized structures for physical activity research.

Shanshan Chen

CircaCP

Sleep and Circadian Metrics Estimation from Actigraphy Data

Jonathon Jacobs

extract_sleep_metrics function

<dl><dt>df</dt>
<dd><code>data.frame</code> with columns <code>id</code>, <code>Date</code>, <code>Time</code>, <code>Activity</code>, <code>label.sw</code>.</dd>
<dt>min_sleep_episode_min</dt>
<dd>Minimum duration (minutes) to treat as a main sleep episode.</dd></dl>

Arguments

Extract metrics related to sleep and circadian rhythm after using CircaCP algorithm — extract_sleep_metrics

<dl>

<dt>df</dt>
<dd><code>data.frame</code> with columns <code>id</code>, <code>Date</code>, <code>Time</code>, <code>Activity</code>, <code>label.sw</code>.</dd>


<dt>min_sleep_episode_min</dt>
<dd>Minimum duration (minutes) to treat as a main sleep episode.</dd>

</dl>

extract_sleep_metrics: Extract metrics related to sleep and circadian rhythm after using CircaCP algorithm

Description

Usage

Value

Arguments

See Also