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. 2018 Dec;33(12):2046-2047.
doi: 10.1007/s11606-018-4610-8.

Using Smartphone Crowdsourcing to Redefine Normal and Febrile Temperatures in Adults: Results from the Feverprints Study

Jonathan S Hausmann  1   2 , Ron Berna  3   4 , Nitin Gujral  4 , Soleh Ayubi  4   5 , Jared Hawkins  4 , John S Brownstein  4 , Fatma Dedeoglu  6
Affiliations

Using Smartphone Crowdsourcing to Redefine Normal and Febrile Temperatures in Adults: Results from the Feverprints Study

Jonathan S Hausmann et al. J Gen Intern Med. 2018 Dec.
No abstract available

Keywords: ResearchKit; crowdsourcing; fever; smartphone; temperatures.

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Conflict of interest statement

The authors declare that they do not have a conflict of interest.

Figures

Fig. 1
Fig. 1
(a) Average daily temperature and (b) number of temperature recordings at each hour. To assess temperature trends throughout the day, each entry was treated individually. To adjust for varying number of measurements per user, recordings were grouped into 15-min intervals, and each user’s average temperature over that interval was treated as a single data point. These adjusted temperature points were then plotted vs. recording time, and a smoothing cubic spline was applied to average over different users’ recordings. Cubic spline interpolation was performed to generate curves sampled at regular intervals. Kindly indicate the panel labels/figure indicators in the artwork.I have uploaded a graph with labeled section A and B.
See this image and copyright information in PMC

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