Digital phenotyping is a multidisciplinary field of

science Science is a systematic endeavor that Scientific method, builds and organizes knowledge in the form of Testability, testable explanations and predictions about the universe. Science may be as old as the human species, and some of the earli ...

, first defined in a May 2016 paper in ''JMIR Mental Health'' authored by John Torous, Mathew V Kiang, Jeanette Lorme, and Jukka-Pekka Onnela as the “moment-by-moment quantification of the individual-level human phenotype ''

in situ ''In situ'' (; often not italicized in English) is a Latin phrase that translates literally to "on site" or "in position." It can mean "locally", "on site", "on the premises", or "in place" to describe where an event takes place and is used in ...

'' using

data In the pursuit of knowledge, data (; ) is a collection of discrete Value_(semiotics), values that convey information, describing quantity, qualitative property, quality, fact, statistics, other basic units of meaning, or simply sequences of sy ...

from personal digital devices." 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 for 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, aging, frailty, and other illness phenotypes. Types of relevant passive data include

GPS The Global Positioning System (GPS), originally Navstar GPS, is a satellite-based radionavigation system owned by the United States government and operated by the United States Space Force. It is one of the global navigation satellite sy ...

data to monitor spatial location,

accelerometer An accelerometer is a tool that measures proper acceleration. Proper acceleration is the acceleration (the rate of change of velocity) of a body in its own instantaneous rest frame; this is different from coordinate acceleration, which is acc ...

data to record movement and gross motor activity, and call and messaging logs to document

social engagement Social engagement (also social involvement, social participation) refers to one's degree of participation in a community or society. Definitions Prohaska, Anderson and Binstock (2012) noted that the term social engagement is commonly used to r ...

with others. Passively collected data may also support clinical differentiation between diagnostic groups and monitoring mental health symptoms. The related term '

digital phenotype Digital usually refers to something using discrete digits, often binary digits. Technology and computing Hardware *Digital electronics, electronic circuits which operate using digital signals **Digital camera, which captures and stores digital i ...

,' was introduced in Nature Biotechnology by

Sachin H. Jain Sachin H. Jain (born 1980) is an American physician who held leadership positions in the Center for Medicare and Medicaid Services (CMS) and the Office of the National Coordinator for Health Information Technology (ONC). From 2015 to 2020, he se ...

and

John Brownstein John Brownstein is a Canadian epidemiologist and Professor of Medicine at the Harvard Medical School as well as the Chief Innovation Officer at Boston Children’s Hospital. His research focuses on development of computational methods in epidem ...

in 2015.

Research Platforms and Commercialization

One of the first implementations of digital phenotyping on smart phones was th
Funf Open Sensing Framework
developed at the MIT Media Lab and launched on October 5, 2011. Members of the Funf team interested in profiling and predicting human behavior formed a commercial venture called Behavio in 2012. In April 2013, it was announced that the Behavio team had joined Google. The Funf platform has inspired other mobile phone sensor logging platforms for psychology and behavior applications, such as the Purple Robot platform, developed by the CBITS (Center for Behavioral Intervention Technologies) at Northwestern University in 2012, which has since expanded and remains an active GITHUB project. Among the academic research community, there are now many digital phenotyping platforms. Popular open-source digital phenotyping platforms include Beiwe which was developed in the Onnela lab at Harvard School of Public Health in 2013. Others includ
AWAREEARSmindLAMPRADAR-CNS
among others and there is currently no metric to determine which is most popular. In terms of commercialization, in 2017, former head of the National Institutes of Mental Health, Tom Insel, joined Rick Klausner and Paul Dagum to form the founding team o
MindStrong Health
which uses digital phenotyping methods combined with machine learning to develop new paradigms for mental health assessment and development of new digital biomarkers for mental health. As of 2021 the company's website does not mention digital phenotyping.

References

{{reflist Academic discipline interactions Bioinformatics

Research Platforms and Commercialization

See also

Further reading

References