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fitbitparsed_csv
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Phone Accelerometer
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Phone Activity Recognition
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Phone Applications Crashes
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Phone Applications Foreground
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Phone Applications Notifications
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Phone Battery
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Phone Bluetooth
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Phone Calls
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Phone Conversation
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Phone Data Yield
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Phone Keyboard
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Phone Light
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Phone Locations
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Phone Log
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Phone Messages
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Phone Screen
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Phone WiFI Connected
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Phone WiFI Visible
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Fitbit Calories Intraday
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Fitbit Data Yield
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Fitbit Heart Rate Summary
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RAPIDS
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<h1 id="cite-rapids-and-providers">Cite RAPIDS and providers<a class="headerlink" href="#cite-rapids-and-providers" title="Permanent link">&para;</a></h1>
<div class="admonition done">
<p class="admonition-title">RAPIDS and the community</p>
<p>RAPIDS is a community effort and as such we want to continue recognizing the contributions from other researchers. Besides citing RAPIDS, we ask you to cite any of the authors listed below if you used those sensor providers in your analysis, thank you!</p>
</div>
<h2 id="rapids">RAPIDS<a class="headerlink" href="#rapids" title="Permanent link">&para;</a></h2>
<p>If you used RAPIDS, please cite <a href="https://preprints.jmir.org/preprint/23246">this paper</a>.</p>
<div class="admonition cite">
<p class="admonition-title">RAPIDS et al. citation</p>
<p>Vega J, Li M, Aguillera K, Goel N, Joshi E, Durica KC, Kunta AR, Low CA
RAPIDS: Reproducible Analysis Pipeline for Data Streams Collected with Mobile Devices
JMIR Preprints. 18/08/2020:23246
DOI: 10.2196/preprints.23246
URL: <a href="https://preprints.jmir.org/preprint/23246">https://preprints.jmir.org/preprint/23246</a></p>
</div>
<h2 id="dbdp-all-empatica-sensors">DBDP (all Empatica sensors)<a class="headerlink" href="#dbdp-all-empatica-sensors" title="Permanent link">&para;</a></h2>
<p>If you computed features using the provider <code>[DBDP]</code> of any of the Empatica sensors (accelerometer, heart rate, temperature, EDA, BVP, IBI, tags) cite <a href="https://www.cambridge.org/core/journals/journal-of-clinical-and-translational-science/article/digital-biomarker-discovery-pipeline-an-open-source-software-platform-for-the-development-of-digital-biomarkers-using-mhealth-and-wearables-data/A6696CEF138247077B470F4800090E63">this paper</a> in addition to RAPIDS.</p>
<div class="admonition cite">
<p class="admonition-title">Bent et al. citation</p>
<p>Bent, B., Wang, K., Grzesiak, E., Jiang, C., Qi, Y., Jiang, Y., Cho, P., Zingler, K., Ogbeide, F.I., Zhao, A., Runge, R., Sim, I., Dunn, J. (2020). The Digital Biomarker Discovery Pipeline: An open source software platform for the development of digital biomarkers using mHealth and wearables data. Journal of Clinical and Translational Science, 1-28. doi:10.1017/cts.2020.511</p>
</div>
<h2 id="panda-accelerometer">Panda (accelerometer)<a class="headerlink" href="#panda-accelerometer" title="Permanent link">&para;</a></h2>
<p>If you computed accelerometer features using the provider <code>[PHONE_ACCLEROMETER][PANDA]</code> cite <a href="https://pubmed.ncbi.nlm.nih.gov/31657854/">this paper</a> in addition to RAPIDS.</p>
<div class="admonition cite">
<p class="admonition-title">Panda et al. citation</p>
<p>Panda N, Solsky I, Huang EJ, Lipsitz S, Pradarelli JC, Delisle M, Cusack JC, Gadd MA, Lubitz CC, Mullen JT, Qadan M, Smith BL, Specht M, Stephen AE, Tanabe KK, Gawande AA, Onnela JP, Haynes AB. Using Smartphones to Capture Novel Recovery Metrics After Cancer Surgery. JAMA Surg. 2020 Feb 1;155(2):123-129. doi: 10.1001/jamasurg.2019.4702. PMID: 31657854; PMCID: PMC6820047.</p>
</div>
<h2 id="stachl-applications-foreground">Stachl (applications foreground)<a class="headerlink" href="#stachl-applications-foreground" title="Permanent link">&para;</a></h2>
<p>If you computed applications foreground features using the app category (genre) catalogue in <code>[PHONE_APPLICATIONS_FOREGROUND][RAPIDS]</code> cite <a href="https://www.pnas.org/content/117/30/17680">this paper</a> in addition to RAPIDS.</p>
<div class="admonition cite">
<p class="admonition-title">Stachl et al. citation</p>
<p>Clemens Stachl, Quay Au, Ramona Schoedel, Samuel D. Gosling, Gabriella M. Harari, Daniel Buschek, Sarah Theres Völkel, Tobias Schuwerk, Michelle Oldemeier, Theresa Ullmann, Heinrich Hussmann, Bernd Bischl, Markus Bühner. Proceedings of the National Academy of Sciences Jul 2020, 117 (30) 17680-17687; DOI: 10.1073/pnas.1920484117 </p>
</div>
<h2 id="doryab-bluetooth">Doryab (bluetooth)<a class="headerlink" href="#doryab-bluetooth" title="Permanent link">&para;</a></h2>
<p>If you computed bluetooth features using the provider <code>[PHONE_BLUETOOTH][DORYAB]</code> cite <a href="https://arxiv.org/abs/1812.10394">this paper</a> in addition to RAPIDS.</p>
<div class="admonition cite">
<p class="admonition-title">Doryab et al. citation</p>
<p>Doryab, A., Chikarsel, P., Liu, X., &amp; Dey, A. K. (2019). Extraction of Behavioral Features from Smartphone and Wearable Data. ArXiv:1812.10394 [Cs, Stat]. <a href="http://arxiv.org/abs/1812.10394">http://arxiv.org/abs/1812.10394</a></p>
</div>
<h2 id="barnett-locations">Barnett (locations)<a class="headerlink" href="#barnett-locations" title="Permanent link">&para;</a></h2>
<p>If you computed locations features using the provider <code>[PHONE_LOCATIONS][BARNETT]</code> cite <a href="https://doi.org/10.1093/biostatistics/kxy059">this paper</a> and <a href="https://doi.org/10.1145/2750858.2805845">this paper</a> in addition to RAPIDS.</p>
<div class="admonition cite">
<p class="admonition-title">Barnett et al. citation</p>
<p>Ian Barnett, Jukka-Pekka Onnela, Inferring mobility measures from GPS traces with missing data, Biostatistics, Volume 21, Issue 2, April 2020, Pages e98–e112, <a href="https://doi.org/10.1093/biostatistics/kxy059">https://doi.org/10.1093/biostatistics/kxy059</a></p>
</div>
<div class="admonition cite">
<p class="admonition-title">Canzian et al. citation</p>
<p>Luca Canzian and Mirco Musolesi. 2015. Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp &lsquo;15). Association for Computing Machinery, New York, NY, USA, 1293–1304. DOI:<a href="https://doi.org/10.1145/2750858.2805845">https://doi.org/10.1145/2750858.2805845</a></p>
</div>
<h2 id="doryab-locations">Doryab (locations)<a class="headerlink" href="#doryab-locations" title="Permanent link">&para;</a></h2>
<p>If you computed locations features using the provider <code>[PHONE_LOCATIONS][DORYAB]</code> cite <a href="https://arxiv.org/abs/1812.10394">this paper</a> and <a href="https://doi.org/10.1145/2750858.2805845">this paper</a> in addition to RAPIDS. In addition, if you used the <code>SUN_LI_VEGA_STRATEGY</code> strategy, cite <a href="https://www.jmir.org/2020/9/e19992/">this paper</a> as well.</p>
<div class="admonition cite">
<p class="admonition-title">Doryab et al. citation</p>
<p>Doryab, A., Chikarsel, P., Liu, X., &amp; Dey, A. K. (2019). Extraction of Behavioral Features from Smartphone and Wearable Data. ArXiv:1812.10394 [Cs, Stat]. <a href="http://arxiv.org/abs/1812.10394">http://arxiv.org/abs/1812.10394</a></p>
</div>
<div class="admonition cite">
<p class="admonition-title">Canzian et al. citation</p>
<p>Luca Canzian and Mirco Musolesi. 2015. Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp &lsquo;15). Association for Computing Machinery, New York, NY, USA, 1293–1304. DOI:<a href="https://doi.org/10.1145/2750858.2805845">https://doi.org/10.1145/2750858.2805845</a></p>
</div>
<div class="admonition cite">
<p class="admonition-title">Sun et al. citation</p>
<p>Sun S, Folarin AA, Ranjan Y, Rashid Z, Conde P, Stewart C, Cummins N, Matcham F, Dalla Costa G, Simblett S, Leocani L, Lamers F, Sørensen PS, Buron M, Zabalza A, Guerrero Pérez AI, Penninx BW, Siddi S, Haro JM, Myin-Germeys I, Rintala A, Wykes T, Narayan VA, Comi G, Hotopf M, Dobson RJ, RADAR-CNS Consortium. Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19. J Med Internet Res 2020;22(9):e19992</p>
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