A full-stack analytical application designed to correlate physiological signals with spatial environments. The system ingests raw Garmin activity exports and processes heart rate, walking pace, cadence, and GPS data through a Python-based transformation pipeline. Multi-sensor time-series streams are synchronized and normalized into a composite geospatial dataset, binding physiological signals directly to spatial coordinates.

To ensure spatial integrity, GPS data was harmonized to the WGS84 coordinate reference system. Location points were spatially resampled to mitigate signal noise and drift, then reconstructed into continuous walking paths by sequencing timestamps and recursively interpolating intermediate positions. This enabled smooth, motion-based visualizations of biometric response along movement trajectories.

The frontend application built with React, Vite, Deck.gl, and Recharts allows users to interactively explore these spatial-physiological relationships. Stakeholders can visualize biometric fluctuations along paths, filter metrics dynamically, and assess how environmental layout conditions may influence human response. The application is deployed via Vercel for internal use and demonstrations.