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Cite RAPIDS and providers

RAPIDS and the community

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!

RAPIDS

If you used RAPIDS, please cite this paper.

RAPIDS et al. citation

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: https://preprints.jmir.org/preprint/23246

DBDP (all Empatica sensors)

If you computed features using the provider [DBDP] of any of the Empatica sensors (accelerometer, heart rate, temperature, EDA, BVP, IBI, tags) cite this paper in addition to RAPIDS.

Bent et al. citation

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

Panda (accelerometer)

If you computed accelerometer features using the provider [PHONE_ACCLEROMETER][PANDA] cite this paper in addition to RAPIDS.

Panda et al. citation

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.

Stachl (applications foreground)

If you computed applications foreground features using the app category (genre) catalogue in [PHONE_APPLICATIONS_FOREGROUND][RAPIDS] cite this paper in addition to RAPIDS.

Stachl et al. citation

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

Doryab (bluetooth)

If you computed bluetooth features using the provider [PHONE_BLUETOOTH][DORYAB] cite this paper in addition to RAPIDS.

Doryab et al. citation

Doryab, A., Chikarsel, P., Liu, X., & Dey, A. K. (2019). Extraction of Behavioral Features from Smartphone and Wearable Data. ArXiv:1812.10394 [Cs, Stat]. http://arxiv.org/abs/1812.10394

Barnett (locations)

If you computed locations features using the provider [PHONE_LOCATIONS][BARNETT] cite this paper and this paper in addition to RAPIDS.

Barnett et al. citation

Ian Barnett, Jukka-Pekka Onnela, Inferring mobility measures from GPS traces with missing data, Biostatistics, Volume 21, Issue 2, April 2020, Pages e98–e112, https://doi.org/10.1093/biostatistics/kxy059

Canzian et al. citation

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 ‘15). Association for Computing Machinery, New York, NY, USA, 1293–1304. DOI:https://doi.org/10.1145/2750858.2805845

Doryab (locations)

If you computed locations features using the provider [PHONE_LOCATIONS][DORYAB] cite this paper and this paper in addition to RAPIDS. In addition, if you used the SUN_LI_VEGA_STRATEGY strategy, cite this paper as well.

Doryab et al. citation

Doryab, A., Chikarsel, P., Liu, X., & Dey, A. K. (2019). Extraction of Behavioral Features from Smartphone and Wearable Data. ArXiv:1812.10394 [Cs, Stat]. http://arxiv.org/abs/1812.10394

Canzian et al. citation

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 ‘15). Association for Computing Machinery, New York, NY, USA, 1293–1304. DOI:https://doi.org/10.1145/2750858.2805845

Sun et al. citation

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

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