Apple Health XML export: contents and analysis boundaries
A practical map of Apple Health XML exports, from records and metadata to provenance, missing data, privacy, and defensible analysis.
VitalAgent research blog
Apple Health data, wearable algorithms, and evidence—explained.
Practical, source-visible field notes for people building with or interpreting personal health data. We separate measurements, estimates, and conclusions—and name what the evidence cannot establish.
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Four ways to ask better questions of health data.
Each article includes its evidence basis, review date, primary or authoritative sources, and the limits that should remain visible.
Apple Health data and MCP: a privacy-aware architecture
A practical architecture for exposing minimized Apple Health summaries to an MCP-compatible tool while preserving consent and boundaries.
Wearable algorithms: from sensor signal to insight
A transparent five-layer model for wearable algorithms: sensors, signal quality, features, personal baselines or models, and uncertainty.
How to read wearable sleep-validation studies
A practical framework for reading wearable sleep studies: comparator, population, sensitivity, specificity, agreement, and limits.
Editorial standard
Source first. Boundaries visible. Human reviewed.
Primary evidenceApple documentation and peer-reviewed research are linked directly.
No synthetic certaintyMissing data, study limits, and engineering interpretation stay labeled.
Draft before publishDaily research drafts require source and claims review before they reach this index.