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<li class="md-nav__item">
<a href="/features/fitbit-data-yield/" class="md-nav__link">
Fitbit Data Yield
</a>
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Fitbit Heart Rate Summary

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Fitbit Heart Rate Summary
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</label>
<ul class="md-nav__list" data-md-scrollfix>
<li class="md-nav__item">
<a href="#v042" class="md-nav__link">
v0.4.2
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<a href="#v041" class="md-nav__link">
v0.4.1
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</label>
<ul class="md-nav__list" data-md-scrollfix>
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<a href="#v042" class="md-nav__link">
v0.4.2
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<a href="#v041" class="md-nav__link">
v0.4.1
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<h1 id="change-log">Change Log<a class="headerlink" href="#change-log" title="Permanent link">&para;</a></h1>
<h2 id="v042">v0.4.2<a class="headerlink" href="#v042" title="Permanent link">&para;</a></h2>
<ul>
<li>Update battery testing</li>
<li>Fix location processing bug when certain columns don&rsquo;t exist</li>
<li>Fix HR intraday bug when minutesonZONE features were 0 </li>
<li>Update FAQs</li>
<li>Fix HR summary bug when restinghr=0 (ignore those rows)</li>
<li>Fix ROG, location entropy and normalized entropy in Doryab location provider</li>
<li>Remove sampling frequency dependance in Doryab location provider</li>
<li>Update documentation of Doryab location provider</li>
<li>Add new <code>FITBIT_DATA_YIELD</code> <code>RAPIDS</code> provider</li>
<li>Deprecate Doryab circadian movement feature until it is fixed</li>
</ul>
<h2 id="v041">v0.4.1<a class="headerlink" href="#v041" title="Permanent link">&para;</a></h2>
<ul>
<li>Fix bug when no error message was displayed for an empty <code>[PHONE_DATA_YIELD][SENSORS]</code> when resampling location data</li>

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Unrecognized output timezone "America/New_York"
</a>
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Unimplemented MAX_NO_FIELD_TYPES
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Running RAPIDS on Apple Silicon M1 Mac
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Unrecognized output timezone "America/New_York"
</a>
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Unimplemented MAX_NO_FIELD_TYPES
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Running RAPIDS on Apple Silicon M1 Mac
</a>
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@ -1550,14 +1591,29 @@ Execution halted
<details class="done" open="open"><summary>Solution</summary><p>In RAPIDS v0.1.0 we replaced <code>RMySQL</code> R package with <code>RMariaDB</code>, this error means your R virtual environment is out of date, to update it run <code>snakemake -j1 renv_restore</code></p>
</details>
<h2 id="unrecognized-output-timezone-americanew_york">Unrecognized output timezone &ldquo;America/New_York&rdquo;<a class="headerlink" href="#unrecognized-output-timezone-americanew_york" title="Permanent link">&para;</a></h2>
<details class="failure" open="open"><summary>Problem</summary></details>
<p>When running RAPIDS with R 4.0.3 on MacOS on M1, lubridate may throw an error associated with the timezone.
<details class="failure" open="open"><summary>Problem</summary><p>When running RAPIDS with R 4.0.3 on MacOS on M1, lubridate may throw an error associated with the timezone.
<div class="highlight"><pre><span></span><code>Error <span class="k">in</span> C_force_tz<span class="o">(</span>time, <span class="nv">tz</span> <span class="o">=</span> tzone, roll<span class="o">)</span>:
CCTZ: Unrecognized output timezone: <span class="s2">&quot;America/New_York&quot;</span>
Calls: get_timestamp_filter ... .parse_date_time -&gt; .strptime -&gt; force_tz -&gt; C_force_tz
</code></pre></div></p>
</details>
<details class="done" open="open"><summary>Solution</summary></details>
<p>This is because R timezone library is not set. Please add <code>Sys.setenv(“TZDIR” = file.path(R.home(), “share”, “zoneinfo”))</code> to the file active.R in renv folder to set the timezone library. For further details on how to test if <code>TZDIR</code> is properly set, please refer to <code>https://github.com/tidyverse/lubridate/issues/928#issuecomment-720059233</code>. </p>
<h2 id="unimplemented-max_no_field_types">Unimplemented MAX_NO_FIELD_TYPES<a class="headerlink" href="#unimplemented-max_no_field_types" title="Permanent link">&para;</a></h2>
<details class="failure" open="open"><summary>Problem</summary><p>You get the following error when downloading Fitbit data:
<div class="highlight"><pre><span></span><code>Error: Unimplemented MAX_NO_FIELD_TYPES
Execution halted
</code></pre></div></p>
</details>
<details class="done" open="open"><summary>Solution</summary><p>At the moment RMariaDB <a href="https://github.com/r-dbi/RMariaDB/issues/127">cannot handle</a> MySQL columns of JSON type. Change the type of your Fitbit data column to <code>longtext</code> (note that the content will not change and will still be a JSON object just interpreted as a string).</p>
</details>
<h2 id="running-rapids-on-apple-silicon-m1-mac">Running RAPIDS on Apple Silicon M1 Mac<a class="headerlink" href="#running-rapids-on-apple-silicon-m1-mac" title="Permanent link">&para;</a></h2>
<details class="failure" open="open"><summary>Problem</summary><p>You get the following error when installing pandoc or running rapids:
<div class="highlight"><pre><span></span><code>MoSHI/rapids/renv/staging/1/00LOCK-KernSmooth/00new/KernSmooth/libs/KernSmooth.so: mach-0, but wrong architecture
</code></pre></div></p>
</details>
<details class="done" open="open"><summary>Solution</summary><p>As of Feb 2020 in M1 macs, R needs to be installed via brew under Rosetta (x86 arch) due to some incompatibility with selected R libraries. To do this, run your terminal <a href="https://www.youtube.com/watch?v=nv2ylxro7rM&amp;t=138s">via Rosetta</a>, then proceed with the usual brew installation command. x86 homebrew should be installed in <code>/usr/local/bin/brew</code>, you can check which brew you are using by typing <code>which brew</code>. Then use x86 homebrew to install R and restore RAPIDS packages (<code>renv_restore</code>). </p>
</details>

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Fitbit Heart Rate Summary
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<li>Phone Screen</li>
<li>Phone WiFI Connected</li>
<li>Phone WiFI Visible</li>
<li>Fitbit Data Yield</li>
<li>Fitbit Heart Rate Summary</li>
<li>Fitbit Heart Rate Intraday</li>
<li>Fitbit Sleep Summary</li>

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<div class="md-footer-nav">
<nav class="md-footer-nav__inner md-grid" aria-label="Footer">
<a href="../phone-wifi-visible/" class="md-footer-nav__link md-footer-nav__link--prev" rel="prev">
<a href="../fitbit-data-yield/" class="md-footer-nav__link md-footer-nav__link--prev" rel="prev">
<div class="md-footer-nav__button md-icon">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20 11v2H8l5.5 5.5-1.42 1.42L4.16 12l7.92-7.92L13.5 5.5 8 11h12z"/></svg>
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@ -1258,12 +1271,12 @@
<tbody>
<tr>
<td>ratiovalidyieldedminutes</td>
<td>rows</td>
<td>-</td>
<td>The ratio between the number of valid minutes and the duration in minutes of a time segment.</td>
</tr>
<tr>
<td>ratiovalidyieldedhours</td>
<td>lux</td>
<td>-</td>
<td>The ratio between the number of valid hours and the duration in hours of a time segment. If the time segment is shorter than 1 hour this feature will always be 1.</td>
</tr>
</tbody>

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@ -1398,10 +1411,14 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<td>It is the threshold value in km/hr which labels a row as Static or Moving.</td>
</tr>
<tr>
<td><code>[MAXIMUM_GAP_ALLOWED]</code></td>
<td><code>[MAXIMUM_ROW_GAP]</code></td>
<td>The maximum gap (in seconds) allowed between any two consecutive rows for them to be considered part of the same displacement. If this threshold is too high, it can throw speed and distance calculations off for periods when the the phone was not sensing.</td>
</tr>
<tr>
<td><code>[MAXIMUM_ROW_DURATION]</code></td>
<td>The time difference between any two consecutive rows <code>A</code> and <code>B</code> is considered as the time a participant spent in <code>A</code>. If this difference is bigger than MAXIMUM_ROW_GAP we will substitute it with <code>MAXIMUM_ROW_DURATION</code>.</td>
</tr>
<tr>
<td><code>[MINUTES_DATA_USED]</code></td>
<td>Set to <code>True</code> to include an extra column in the final location feature file containing the number of minutes used to compute the features on each time segment. Use this for quality control purposes, the more data minutes exist for a period, the more reliable its features should be. For fused location, a single minute can contain more than one coordinate pair if the participant is moving fast enough.</td>
</tr>
@ -1455,14 +1472,14 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<td>Speed variance in a time segment considering only the instances labeled as Moving.</td>
</tr>
<tr>
<td>circadianmovement</td>
<td><del class="critic">circadianmovement</del></td>
<td>-</td>
<td>"It encodes the extent to which a person&rsquo;s location patterns follow a 24-hour circadian cycle." <a href="../../citation#doryab-locations">Doryab et al.</a>.</td>
<td>Not suggested for use at the moment, see Observations below. "It encodes the extent to which a person&rsquo;s location patterns follow a 24-hour circadian cycle." <a href="../../citation#doryab-locations">Doryab et al.</a>.</td>
</tr>
<tr>
<td>numberofsignificantplaces</td>
<td>places</td>
<td>Number of significant locations visited. It is calculated using the DBSCAN clustering algorithm which takes in EPS and MIN_SAMPLES as parameters to identify clusters. Each cluster is a significant place.</td>
<td>Number of significant locations visited. It is calculated using the DBSCAN/OPTICS clustering algorithm which takes in EPS and MIN_SAMPLES as parameters to identify clusters. Each cluster is a significant place.</td>
</tr>
<tr>
<td>numberlocationtransitions</td>
@ -1492,12 +1509,12 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<tr>
<td>movingtostaticratio</td>
<td>-</td>
<td>Ratio between stationary time and total location sensed time. A lat/long coordinate pair is labelled as stationary if it’s speed (distance/time) to the next coordinate pair is less than 1km/hr. A higher value represents a more stationary routine. These times are computed by multiplying the number of rows by <code>[SAMPLING_FREQUENCY]</code></td>
<td>Ratio between stationary time and total location sensed time. A lat/long coordinate pair is labelled as stationary if it’s speed (distance/time) to the next coordinate pair is less than 1km/hr. A higher value represents a more stationary routine. These times are computed using timeInSeconds feature.</td>
</tr>
<tr>
<td>outlierstimepercent</td>
<td>-</td>
<td>Ratio between the time spent in non-significant clusters divided by the time spent in all clusters (total location sensed time). A higher value represents more time spent in non-significant clusters. These times are computed by multiplying the number of rows by <code>[SAMPLING_FREQUENCY]</code></td>
<td>Ratio between the time spent in non-significant clusters divided by the time spent in all clusters (total location sensed time). A higher value represents more time spent in non-significant clusters. These times are computed using timeInSeconds feature.</td>
</tr>
<tr>
<td>maxlengthstayatclusters</td>
@ -1535,10 +1552,12 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<p class="admonition-title">Assumptions/Observations</p>
<p><strong>Significant Locations Identified</strong>
Significant locations are determined using DBSCAN clustering on locations that a patient visit over the course of the period of data collection.</p>
<p><strong>The Circadian Calculation</strong>
For a detailed description of how this is calculated, see <a href="../../citation#doryab-locations">Canzian et al</a>.</p>
<p><strong>Circadian Movement Calculation</strong>
Note Feb 3 2021. It seems the implementation of this feature is not correct, we suggest not to use this feature until a fix is in place. For a detailed description of how this should be calculated, see <a href="https://pubmed.ncbi.nlm.nih.gov/28344895/">Saeb et al</a>.</p>
<p><strong>Fine Tuning Clustering Parameters</strong>
Based on an experiment where we collected fused location data for 7 days with a mean accuracy of 86 &amp; SD of 350.874635, we determined that <code>EPS/MAX_EPS</code>=100 produced closer clustering results to reality. Higher values (&gt;100) missed out some significant places like a short grocery visit while lower values (&lt;100) picked up traffic lights and stop signs while driving as significant locations. We recommend you set <code>EPS</code> based on the accuracy of your location data (the more accurate your data is, the lower you should be able to set EPS).</p>
<p><strong>Duration Calculation</strong>
To calculate the time duration component for our features, we compute the difference between the timestamps of consecutive rows to take into account sampling rate variability. If this time difference is larger than a threshold (300 seconds by default) we replace it with a maximum duration (60 seconds by default, i.e. we assume a participant spent at least 60 seconds in their last known location)</p>
</div>

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Fitbit Data Yield
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Fitbit Heart Rate Summary

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Fitbit Data Yield
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</a>
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Fitbit Heart Rate Summary
@ -1076,6 +1089,13 @@
</label>
<ul class="md-nav__list" data-md-scrollfix>
<li class="md-nav__item">
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v0.4.2
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</li>
<li class="md-nav__item">
<a href="#v041" class="md-nav__link">
v0.4.1
@ -1216,6 +1236,13 @@
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<ul class="md-nav__list" data-md-scrollfix>
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<a href="#v042" class="md-nav__link">
v0.4.2
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<a href="#v041" class="md-nav__link">
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@ -1325,6 +1352,19 @@
<h1 id="change-log">Change Log<a class="headerlink" href="#change-log" title="Permanent link">&para;</a></h1>
<h2 id="v042">v0.4.2<a class="headerlink" href="#v042" title="Permanent link">&para;</a></h2>
<ul>
<li>Update battery testing</li>
<li>Fix location processing bug when certain columns don&rsquo;t exist</li>
<li>Fix HR intraday bug when minutesonZONE features were 0 </li>
<li>Update FAQs</li>
<li>Fix HR summary bug when restinghr=0 (ignore those rows)</li>
<li>Fix ROG, location entropy and normalized entropy in Doryab location provider</li>
<li>Remove sampling frequency dependance in Doryab location provider</li>
<li>Update documentation of Doryab location provider</li>
<li>Add new <code>FITBIT_DATA_YIELD</code> <code>RAPIDS</code> provider</li>
<li>Deprecate Doryab circadian movement feature until it is fixed</li>
</ul>
<h2 id="v041">v0.4.1<a class="headerlink" href="#v041" title="Permanent link">&para;</a></h2>
<ul>
<li>Fix bug when no error message was displayed for an empty <code>[PHONE_DATA_YIELD][SENSORS]</code> when resampling location data</li>

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Fitbit Heart Rate Summary
@ -1153,6 +1166,20 @@
Unrecognized output timezone "America/New_York"
</a>
</li>
<li class="md-nav__item">
<a href="#unimplemented-max_no_field_types" class="md-nav__link">
Unimplemented MAX_NO_FIELD_TYPES
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Running RAPIDS on Apple Silicon M1 Mac
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@ -1333,6 +1360,20 @@
Unrecognized output timezone "America/New_York"
</a>
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Unimplemented MAX_NO_FIELD_TYPES
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Running RAPIDS on Apple Silicon M1 Mac
</a>
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@ -1550,14 +1591,29 @@ Execution halted
<details class="done" open="open"><summary>Solution</summary><p>In RAPIDS v0.1.0 we replaced <code>RMySQL</code> R package with <code>RMariaDB</code>, this error means your R virtual environment is out of date, to update it run <code>snakemake -j1 renv_restore</code></p>
</details>
<h2 id="unrecognized-output-timezone-americanew_york">Unrecognized output timezone &ldquo;America/New_York&rdquo;<a class="headerlink" href="#unrecognized-output-timezone-americanew_york" title="Permanent link">&para;</a></h2>
<details class="failure" open="open"><summary>Problem</summary></details>
<p>When running RAPIDS with R 4.0.3 on MacOS on M1, lubridate may throw an error associated with the timezone.
<details class="failure" open="open"><summary>Problem</summary><p>When running RAPIDS with R 4.0.3 on MacOS on M1, lubridate may throw an error associated with the timezone.
<div class="highlight"><pre><span></span><code>Error <span class="k">in</span> C_force_tz<span class="o">(</span>time, <span class="nv">tz</span> <span class="o">=</span> tzone, roll<span class="o">)</span>:
CCTZ: Unrecognized output timezone: <span class="s2">&quot;America/New_York&quot;</span>
Calls: get_timestamp_filter ... .parse_date_time -&gt; .strptime -&gt; force_tz -&gt; C_force_tz
</code></pre></div></p>
</details>
<details class="done" open="open"><summary>Solution</summary></details>
<p>This is because R timezone library is not set. Please add <code>Sys.setenv(“TZDIR” = file.path(R.home(), “share”, “zoneinfo”))</code> to the file active.R in renv folder to set the timezone library. For further details on how to test if <code>TZDIR</code> is properly set, please refer to <code>https://github.com/tidyverse/lubridate/issues/928#issuecomment-720059233</code>. </p>
<h2 id="unimplemented-max_no_field_types">Unimplemented MAX_NO_FIELD_TYPES<a class="headerlink" href="#unimplemented-max_no_field_types" title="Permanent link">&para;</a></h2>
<details class="failure" open="open"><summary>Problem</summary><p>You get the following error when downloading Fitbit data:
<div class="highlight"><pre><span></span><code>Error: Unimplemented MAX_NO_FIELD_TYPES
Execution halted
</code></pre></div></p>
</details>
<details class="done" open="open"><summary>Solution</summary><p>At the moment RMariaDB <a href="https://github.com/r-dbi/RMariaDB/issues/127">cannot handle</a> MySQL columns of JSON type. Change the type of your Fitbit data column to <code>longtext</code> (note that the content will not change and will still be a JSON object just interpreted as a string).</p>
</details>
<h2 id="running-rapids-on-apple-silicon-m1-mac">Running RAPIDS on Apple Silicon M1 Mac<a class="headerlink" href="#running-rapids-on-apple-silicon-m1-mac" title="Permanent link">&para;</a></h2>
<details class="failure" open="open"><summary>Problem</summary><p>You get the following error when installing pandoc or running rapids:
<div class="highlight"><pre><span></span><code>MoSHI/rapids/renv/staging/1/00LOCK-KernSmooth/00new/KernSmooth/libs/KernSmooth.so: mach-0, but wrong architecture
</code></pre></div></p>
</details>
<details class="done" open="open"><summary>Solution</summary><p>As of Feb 2020 in M1 macs, R needs to be installed via brew under Rosetta (x86 arch) due to some incompatibility with selected R libraries. To do this, run your terminal <a href="https://www.youtube.com/watch?v=nv2ylxro7rM&amp;t=138s">via Rosetta</a>, then proceed with the usual brew installation command. x86 homebrew should be installed in <code>/usr/local/bin/brew</code>, you can check which brew you are using by typing <code>which brew</code>. Then use x86 homebrew to install R and restore RAPIDS packages (<code>renv_restore</code>). </p>
</details>

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<li>Phone Screen</li>
<li>Phone WiFI Connected</li>
<li>Phone WiFI Visible</li>
<li>Fitbit Data Yield</li>
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<div class="md-footer-nav">
<nav class="md-footer-nav__inner md-grid" aria-label="Footer">
<a href="../phone-wifi-visible/" class="md-footer-nav__link md-footer-nav__link--prev" rel="prev">
<a href="../fitbit-data-yield/" class="md-footer-nav__link md-footer-nav__link--prev" rel="prev">
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20 11v2H8l5.5 5.5-1.42 1.42L4.16 12l7.92-7.92L13.5 5.5 8 11h12z"/></svg>
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<tbody>
<tr>
<td>ratiovalidyieldedminutes</td>
<td>rows</td>
<td>-</td>
<td>The ratio between the number of valid minutes and the duration in minutes of a time segment.</td>
</tr>
<tr>
<td>ratiovalidyieldedhours</td>
<td>lux</td>
<td>-</td>
<td>The ratio between the number of valid hours and the duration in hours of a time segment. If the time segment is shorter than 1 hour this feature will always be 1.</td>
</tr>
</tbody>

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<td>It is the threshold value in km/hr which labels a row as Static or Moving.</td>
</tr>
<tr>
<td><code>[MAXIMUM_GAP_ALLOWED]</code></td>
<td><code>[MAXIMUM_ROW_GAP]</code></td>
<td>The maximum gap (in seconds) allowed between any two consecutive rows for them to be considered part of the same displacement. If this threshold is too high, it can throw speed and distance calculations off for periods when the the phone was not sensing.</td>
</tr>
<tr>
<td><code>[MAXIMUM_ROW_DURATION]</code></td>
<td>The time difference between any two consecutive rows <code>A</code> and <code>B</code> is considered as the time a participant spent in <code>A</code>. If this difference is bigger than MAXIMUM_ROW_GAP we will substitute it with <code>MAXIMUM_ROW_DURATION</code>.</td>
</tr>
<tr>
<td><code>[MINUTES_DATA_USED]</code></td>
<td>Set to <code>True</code> to include an extra column in the final location feature file containing the number of minutes used to compute the features on each time segment. Use this for quality control purposes, the more data minutes exist for a period, the more reliable its features should be. For fused location, a single minute can contain more than one coordinate pair if the participant is moving fast enough.</td>
</tr>
@ -1455,14 +1472,14 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<td>Speed variance in a time segment considering only the instances labeled as Moving.</td>
</tr>
<tr>
<td>circadianmovement</td>
<td><del class="critic">circadianmovement</del></td>
<td>-</td>
<td>"It encodes the extent to which a person&rsquo;s location patterns follow a 24-hour circadian cycle." <a href="../../citation#doryab-locations">Doryab et al.</a>.</td>
<td>Not suggested for use at the moment, see Observations below. "It encodes the extent to which a person&rsquo;s location patterns follow a 24-hour circadian cycle." <a href="../../citation#doryab-locations">Doryab et al.</a>.</td>
</tr>
<tr>
<td>numberofsignificantplaces</td>
<td>places</td>
<td>Number of significant locations visited. It is calculated using the DBSCAN clustering algorithm which takes in EPS and MIN_SAMPLES as parameters to identify clusters. Each cluster is a significant place.</td>
<td>Number of significant locations visited. It is calculated using the DBSCAN/OPTICS clustering algorithm which takes in EPS and MIN_SAMPLES as parameters to identify clusters. Each cluster is a significant place.</td>
</tr>
<tr>
<td>numberlocationtransitions</td>
@ -1492,12 +1509,12 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<tr>
<td>movingtostaticratio</td>
<td>-</td>
<td>Ratio between stationary time and total location sensed time. A lat/long coordinate pair is labelled as stationary if it’s speed (distance/time) to the next coordinate pair is less than 1km/hr. A higher value represents a more stationary routine. These times are computed by multiplying the number of rows by <code>[SAMPLING_FREQUENCY]</code></td>
<td>Ratio between stationary time and total location sensed time. A lat/long coordinate pair is labelled as stationary if it’s speed (distance/time) to the next coordinate pair is less than 1km/hr. A higher value represents a more stationary routine. These times are computed using timeInSeconds feature.</td>
</tr>
<tr>
<td>outlierstimepercent</td>
<td>-</td>
<td>Ratio between the time spent in non-significant clusters divided by the time spent in all clusters (total location sensed time). A higher value represents more time spent in non-significant clusters. These times are computed by multiplying the number of rows by <code>[SAMPLING_FREQUENCY]</code></td>
<td>Ratio between the time spent in non-significant clusters divided by the time spent in all clusters (total location sensed time). A higher value represents more time spent in non-significant clusters. These times are computed using timeInSeconds feature.</td>
</tr>
<tr>
<td>maxlengthstayatclusters</td>
@ -1535,10 +1552,12 @@ For a detailed description of how this is calculated, see <a href="../../citatio
<p class="admonition-title">Assumptions/Observations</p>
<p><strong>Significant Locations Identified</strong>
Significant locations are determined using DBSCAN clustering on locations that a patient visit over the course of the period of data collection.</p>
<p><strong>The Circadian Calculation</strong>
For a detailed description of how this is calculated, see <a href="../../citation#doryab-locations">Canzian et al</a>.</p>
<p><strong>Circadian Movement Calculation</strong>
Note Feb 3 2021. It seems the implementation of this feature is not correct, we suggest not to use this feature until a fix is in place. For a detailed description of how this should be calculated, see <a href="https://pubmed.ncbi.nlm.nih.gov/28344895/">Saeb et al</a>.</p>
<p><strong>Fine Tuning Clustering Parameters</strong>
Based on an experiment where we collected fused location data for 7 days with a mean accuracy of 86 &amp; SD of 350.874635, we determined that <code>EPS/MAX_EPS</code>=100 produced closer clustering results to reality. Higher values (&gt;100) missed out some significant places like a short grocery visit while lower values (&lt;100) picked up traffic lights and stop signs while driving as significant locations. We recommend you set <code>EPS</code> based on the accuracy of your location data (the more accurate your data is, the lower you should be able to set EPS).</p>
<p><strong>Duration Calculation</strong>
To calculate the time duration component for our features, we compute the difference between the timestamps of consecutive rows to take into account sampling rate variability. If this time difference is larger than a threshold (300 seconds by default) we replace it with a maximum duration (60 seconds by default, i.e. we assume a participant spent at least 60 seconds in their last known location)</p>
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</a>
<a href="../fitbit-heartrate-summary/" class="md-footer-nav__link md-footer-nav__link--next" rel="next">
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<lastmod>2021-01-27</lastmod>
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<changefreq>daily</changefreq>
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<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
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<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
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<lastmod>2021-02-03</lastmod>
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<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
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<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
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<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
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<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
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<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-01-27</lastmod>
<lastmod>2021-02-03</lastmod>
<changefreq>daily</changefreq>
</url><url>
<loc>None</loc>
<lastmod>2021-02-03</lastmod>
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13
latest/team/index.html
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@ -711,6 +711,19 @@
<li class="md-nav__item">
<a href="../features/fitbit-data-yield/" class="md-nav__link">
Fitbit Data Yield
</a>
</li>
<li class="md-nav__item">
<a href="../features/fitbit-heartrate-summary/" class="md-nav__link">
Fitbit Heart Rate Summary

13
latest/visualizations/data-quality-visualizations/index.html
View File

@ -711,6 +711,19 @@
<li class="md-nav__item">
<a href="../../features/fitbit-data-yield/" class="md-nav__link">
Fitbit Data Yield
</a>
</li>
<li class="md-nav__item">
<a href="../../features/fitbit-heartrate-summary/" class="md-nav__link">
Fitbit Heart Rate Summary

13
latest/visualizations/feature-visualizations/index.html
View File

@ -711,6 +711,19 @@
<li class="md-nav__item">
<a href="../../features/fitbit-data-yield/" class="md-nav__link">
Fitbit Data Yield
</a>
</li>
<li class="md-nav__item">
<a href="../../features/fitbit-heartrate-summary/" class="md-nav__link">
Fitbit Heart Rate Summary

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