open architecture for mobile health activity classification graphing mobility data over time a small set of common principles/practices by which these modules are described and interface to one another
enabling reuse, integration, and innovation getting further together faster…
does caﬀeine aﬀect my sleep? N-‐of-‐1 study design caﬀeine no caﬀeine caﬀeine sleep sleep no caﬀeine caﬀeine no caﬀeine
scaling (n = 1) n Outcome Variables • a caﬀeine deﬁnition module • a sleep deﬁnition module, with APIs for getting sleep data from various monitors • new variables that take advantage of mobile (e.g., reality mining) Scripting study protocols • e.g., modules for setting up an n-‐of-‐1 study
n Σ scaling (n=1) Make the ﬁndings comparable for aggregation • libraries of standard measures (e.g., PHQ-‐9, PROMIS) • indexing of variables and results and to standard vocabularies
n Σ scaling (n=1) Need to describe context to combine apples with apples • who is “n”: demographics, important clinical features • study approach: ad hoc, n-‐of-‐1, etc. • activity context: walking? running? • social context: … • technical context: device, operating system, app, version, sampling rate… • etc.