JMIR Publications

ABSTRACT

As digital phenotyping, the capture of active and passive data from consumer devices like smartphones, becomes more common the need to properly process the data and derive replicable features from it has become paramount. Cortex is an open-source data processing pipeline for digital phenotyping data, optimized for use with the mindLAMP apps which is used by nearly 100 research teams across the world. Cortex is designed to help teams 1) assess digital phenotyping data quality in real time, 2) derive replicable clinical features from the data, 3) and enable easy to share data visualizations. Cortex offers many options to work with digital phenotyping data, although some common approaches are likely of value to all teams using it. This paper highlights the reasoning, code, and example steps necessary to fully work with digital phenotyping data in an streamlined manner. Covering how to work with the data, assess its quality, derives features, and visualize findings, this paper is designed to offer the reader the knowledge and skills to apply towards analyzing any digital phenotyping dataset. Towards highlighting clinical applications, this paper also provides three easy to implement examples of Cortex use in real world settings. Through understanding how to work with digital phenotyping data and providing ready to deploy code with Cortex, the paper aims to show the new field of digital phenotyping can be both accessible to all yet still rigorous in methodology.