Chain simple surveys into longer runs to build complex studies. Use R to generate pretty feedback and complex designs.
This package performs model-free reinforcement learning in R.
DOSE: A customizable watchOS app framework for Experience Sampling Method (ESM) and Ecological Momentary Assessment (EMA) studies on Apple Watch — featuring randomized survey scheduling, HealthKit integration, and seamless Firebase data syncing.
Boundary-triggered check-ins for ActivityWatch (return from AFK, context switch, long block). Adopted from Jeremiah-England/aw-watcher-ask-away with full history and attribution.
Neurophenomenology as personal instrumentation built to study the gap between experience and its recollection, simultaneously producing a local health data archive — a framework for time-aligned first-person sampling and continuous physiological recording.
Experience sampling to better aim agents, analysed in Dust. Pings you at random moments, asks what you are doing, and hands the log to an agent that ranks what is actually worth automating.
Reproducible provenance audit of the LifeSnaps Fitbit dataset: tests whether device-record dates can stand in for study-exposure windows, and rebuilds observation windows from scheduled survey prompts.
iOS Shortcuts pipeline for thrice-daily EMA data collection
Metricwire — independent third-party profile of a public API surface, by API Evangelist. Metricwire is a real-world data collection platform for ecological momentary assessment (EMA), experience sampling (ESM), and digital-health research. It helps organizations measure real-world experiences to inform treatments, service offerings, and policies.
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