Digital phenotyping is a multidisciplinary field of science, defined by Jukka-Pekka Onnela in 2015 as the “moment-by-moment quantification of the individual-level human phenotype in situ using data from personal digital devices,” in particular smartphones. The data can be divided into two subgroups, called active data and passive data, where the former refers to data that requires active input from the users to be generated, whereas passive data, such as sensor data and phone usage patterns, are collected without requiring any active participation from the user.
Smartphones are well suited to digital phenotyping given their widespread adoption and ownership, the extent to which users engage with the devices, and richness of data that may be collected from them. Smartphone data can be used to study behavioral patterns, social interactions, physical mobility, gross motor activity, and speech production, among others. Smartphone ownership has been in steady rise globally over the past few years. For example, in the U.S., smartphone ownership among adults increased from 35% in 2011 to 64% in 2015, and in 2017 an estimated 95% of Americans own a cellphone of some kind and 77% own a smartphone.
The use of passive data collection from smartphone devices can provide granular information relevant to psychiatric and other illness phenotypes. Types of relevant passive data include GPS data to monitor spatial location, accelerometer data to record movement and gross motor activity, and call and messaging logs to document social engagement with others.
JMIR e-collection Digital Biomarkers and Digital Phenotyping
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