The most personal analysis should happen on hardware you control. This work details an on-device architecture that interprets sensitive biosignals locally, keeping raw health data private by default.
Continuous health data is among the most sensitive information a person generates. We designed the system so that sensitive processing never has to leave the device.
We implemented an on-device pipeline for filtering, feature extraction, and inference, transmitting only minimized, consented summaries.
On-device processing preserved analytical quality while sharply reducing the volume of personal data ever transmitted or stored remotely.
A privacy-first architecture reduces risk for patients and builds the trust that continuous monitoring depends on.
Privacy and capability can coexist. Local processing is a practical default for sensitive continuous health monitoring.