Wearables can catch illness before symptoms appear

Snyder, director of the Center for Genomics and Personalized Medicine at Stanford University, argues for a fundamental shift: from detecting disease to continuously monitoring health. Wearable devices are his primary tool. In an interview published by Lifespan.io, he describes how his team used consumer devices to detect infections before people felt ill. In his own case, that was Lyme disease. The researchers spotted a drop in his blood oxygen levels before symptoms appeared.

Your personal baseline is the benchmark

The core principle is the individual baseline. Wearables measure continuously, including when you are healthy. The system therefore knows what your resting heart rate, heart rate variability (the variation in time between consecutive heartbeats), and oxygen saturation normally look like. A deviation from your personal norm is an early warning signal, even if your values still fall within population averages.

Snyder’s team demonstrated this for COVID-19 in collaboration with Fitbit. In people with longer presymptomatic periods, algorithmic analysis of heart rate and related signals could detect infection before symptoms began. For influenza the window is shorter, but early detection was still possible.

Ageotypes and the future of longevity measurement

Beyond infection detection, Snyder studies individual aging patterns. He introduced the concept of ageotypes: personal aging profiles describing in which organ systems a person ages fastest. He is also developing intrinsic capacity as a quantitative health measure for use in longevity research and drug trials. Whether these measures are already clinically actionable is still under investigation.

His broader message is straightforward: current healthcare reacts to illness. Prevention requires systems that measure continuously, flag deviations early, and intervene before damage accumulates.

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