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Review
. 2021 Jan 28;13(2):422.
doi: 10.3390/nu13020422.

Harnessing SmartPhones to Personalize Nutrition in a Time of Global Pandemic

Affiliations
Review

Harnessing SmartPhones to Personalize Nutrition in a Time of Global Pandemic

Niv Zmora et al. Nutrients. .

Abstract

The soar in COVID-19 cases around the globe has forced many to adapt to social distancing and self-isolation. In order to reduce contact with healthcare facilities and other patients, the CDC has advocated the use of telemedicine, i.e., electronic information and telecommunication technology. While these changes may disrupt normal behaviors and routines and induce anxiety, resulting in decreased vigilance to healthy diet and physical activity and reluctance to seek medical attention, they may just as well be circumvented using modern technology. Indeed, as the beginning of the pandemic a plethora of alternatives to conventional physical interactions were introduced. In this Perspective, we portray the role of SmartPhone applications (apps) in monitoring healthy nutrition, from their basic functionality as food diaries required for simple decision-making and nutritional interventions, through more advanced purposes, such as multi-dimensional data-mining and development of machine learning algorithms. Finally, we will delineate the emerging field of personalized nutrition and introduce pioneering technologies and concepts yet to be incorporated in SmartPhone-based dietary surveillance.

Keywords: COVID-19; Nutrition app; nutrition; smartphone.

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Conflict of interest statement

E.E. is a paid consultant at DayTwo and BiomX.

Figures

Figure 1
Figure 1
Requirements of nutrition apps. SmartPhone apps consist of several modules: the interface should provide compelling user experience and utilize advanced technologies to facilitate comprehensive data collection, and users’ confidentiality should be maintained. Data mining should be based both on entries recorded by the app and externally derived data and should be suitable for population-based studies. Data analysis should be performed using artificial intelligence and subsequent recommendations should be produced at a personal level (Created with BioRender.com).
Figure 2
Figure 2
-Strata of nutrition apps functionality. The foundation of every nutrition SmartPhone app rests on a user interface to log meals and daily activities. Most apps provide visualization of the recorded data and information to the user. More advanced features include direct supervision and remote monitoring by medical personnel. High-level operations on collected data are population- and precision-based studies (Created with BioRender.com).

References

    1. Quer G., Radin J.M., Gadaleta M., Baca-Motes K., Ariniello L., Ramos E., Kheterpal V., Topol E.J., Steinhubl S.R. Wearable sensor data and self-reported symptoms for COVID-19 detection. Nat. Med. 2020;27:73–77. doi: 10.1038/s41591-020-1123-x. - DOI - PubMed
    1. Segal E., Zhang F., Lin X., King G., Shalem O., Shilo S., Allen W.E., Alquaddoomi F., Altae-Tran H., Anders S., et al. Building an international consortium for tracking coronavirus health status. Nat. Med. 2020;26:1161–1165. doi: 10.1038/s41591-020-0929-x. - DOI - PubMed
    1. Menni C., Valdes A.M., Freidin M.B., Sudre C.H., Nguyen L.H., Drew D.A., Ganesh S., Varsavsky T., Cardoso M.J., El-Sayed Moustafa J.S., et al. Real-time tracking of self-reported symptoms to predict potential COVID-19. Nat. Med. 2020;26:1037–1040. doi: 10.1038/s41591-020-0916-2. - DOI - PMC - PubMed
    1. Drew D.A., Nguyen L.H., Steves C.J., Menni C., Freydin M., Varsavsky T., Sudre C.H., Jorge Cardoso M., Ourselin S., Wolf J., et al. Rapid implementation of mobile technology for real-time epidemiology of COVID-19. Science. 2020;368:1362–1367. doi: 10.1126/science.abc0473. - DOI - PMC - PubMed
    1. Jia J.S., Lu X., Yuan Y., Xu G., Jia J., Christakis N.A. Population flow drives spatio-temporal distribution of COVID-19 in China. Nature. 2020;582:389–394. doi: 10.1038/s41586-020-2284-y. - DOI - PubMed

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