CircaCP

CircaCP-package

Tools to import actigraphy files, screen/clean wear, detect sleep,
and compute cosinor + nonparametric circadian metrics.

internal

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

Sleep and Circadian Metrics Estimation from Actigraphy Data

Jonathon Jacobs

CircaCP-package function

<pre><code>
df &lt;- import_acti_file(file, date_col="Date", time_col="Time", activity_cols="Activity")
scr &lt;- screen_wear(df, min_days=5, max_zero_run=200)
if (scr$status == "ok") {
 newdf &lt;- sleep_detection(scr$clean_df, thr=0.4, dist="ZAG")
 metrics &lt;- extract_sleep_metrics_df(newdf)
}
</code></pre>

Quick start

<ul>
<li><code>import_acti_file()</code> — import with header stripping</li>
<li><code>screen_wear()</code> — decimate + longest-wear screening</li>
<li><code>sleep_cos()</code> — fit cosinor model + circadian windowing</li>
<li><code>sleep_detection()</code> — cosinor + threshold labeling</li>
<li><code>extract_nonparametric_metrics()</code> — RA/IS/IV/L5/M10</li>
<li><code>extract_sleep_metrics()</code> — tidy per-episode metrics</li>
</ul>

Key functions

Maintainer: Shanshan Chen <a href="/link/schen3%40vcu.edu?package=CircaCP&version=0.1.2" data-mini-rdoc="CircaCP::schen3@vcu.edu">schen3@vcu.edu</a>
Other contributors:<ul>
<li>Jonathon Jacobs [contributor]</li>
</ul>

Author

CircaCP: Actigraphy Import, Screening, and Circadian Metrics — CircaCP-package

<pre><code>
df &lt;- import_acti_file(file, date_col="Date", time_col="Time", activity_cols="Activity")
scr &lt;- screen_wear(df, min_days=5, max_zero_run=200)
if (scr$status == "ok") {
 newdf &lt;- sleep_detection(scr$clean_df, thr=0.4, dist="ZAG")
 metrics &lt;- extract_sleep_metrics_df(newdf)
}
</code></pre>

<ul>
<li><code>import_acti_file()</code> — import with header stripping</li>
<li><code>screen_wear()</code> — decimate + longest-wear screening</li>
<li><code>sleep_cos()</code> — fit cosinor model + circadian windowing</li>
<li><code>sleep_detection()</code> — cosinor + threshold labeling</li>
<li><code>extract_nonparametric_metrics()</code> — RA/IS/IV/L5/M10</li>
<li><code>extract_sleep_metrics()</code> — tidy per-episode metrics</li>
</ul>

Maintainer: Shanshan Chen <a href='mailto:schen3@vcu.edu'>schen3@vcu.edu</a>
Other contributors:<ul>
<li>Jonathon Jacobs [contributor]</li>
</ul>

CircaCP-package: CircaCP: Actigraphy Import, Screening, and Circadian Metrics

Description

Arguments

Quick start

Key functions

Author