PassiveDx Aims to Detect Health Anomalies Passively Using Everyday Device Data

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PassiveDx is a proposed AI health system designed to monitor personal health without requiring active user participation. Rather than diagnosing known diseases, it builds a behavioral and physiological baseline for each individual — tracking signals like typing dynamics, sleep rhythm, gait, and heart-rate variability — then flags meaningful deviations over time. The system draws on existing research into digital biomarkers, including smartphone keystroke dynamics and Wi-Fi Channel State Information for contactless respiratory sensing. Developers have structured it as a seven-layer architecture in which privacy is the foundational layer, giving users granular control over which sensors are active and what data leaves their device. The goal is not to replace clinical diagnosis but to surface early warning signals before symptoms become clinically apparent, feeding relevant patterns into healthcare workflows for review.

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