Wearable Data Quality: How to Filter Noise Before the Insight

Quality Gates

1. Sensor Status – Check battery, firmware, and wear position.
2. Context Blend – Import events (alcohol, jet lag) automatically from calendar/notes.
3. Outlier Removal – Rolling median + IQR filter for HRV, resting pulse, temperature.

Manual Overrides

• Mark nights with poor fit directly in the app.
• Add subjective energy score (1–10) to evaluate deviations.

Sync with Biomarkers

Wearable KPI	Biomarker	Decision
HRV declining	hsCRP rising	Start inflammation protocol
Sleep deficit	Cortisol high	Adjust evening routine

Conclusion

Wearable data only becomes valuable when you treat it like lab values: with checks, context, and a clear use case.