Using wearables to enable cardiovascular-kidney-metabolic (CKM) risk profiling for personalized coaching

Heart disease, kidney conditions, and metabolic disorders like type 2 diabetes aren't isolated, they form an interconnected web known as cardiovascular-kidney-metabolic (CKM) syndrome. CKM progression often begins silently years before symptoms appear, shaped by everyday habits like movement, sleep, and cardiovascular activity. Catching these subtle shifts early offers the best chance to reverse the trend. Yet while smartwatches easily track what we did yesterday, moving from passive tracking to meaningful action is much harder: How do my daily habits affect my CKM right now? And if I sleep 30 minutes longer or add a brisk walk to my routine, how much will my health improve over the next three months?

Age is often seen as playing a part in answering these questions, but chronological age alone isn’t enough because two people born in the same year can have vastly different physiological health. While researchers have developed “biological clocks” from blood tests or wearable sensors to estimate whether someone's body is aging faster or slower than their calendar age, most existing clocks aren't built for everyday coaching. Many are trained simply to estimate the birth year, latching onto traits you can't easily change, or act as black boxes that can't show how modifying a specific habit will shift your future health.

In “Personalized health coaching via coachable health age and counterfactual wearable trajectories” and our companion study, “Cardiovascular-Kidney-Metabolic Health Age Using Wearables and Blood Biomarkers”, we introduce an investigational framework designed to close the loop between tracking a person’s health and actively improving it. The framework provides the following:

A health age metric you can actually move

We validated this model across three independent cohorts:

Playing out "what-if" futures with a sensor world model

We paired SensorWM with a feasibility-constrained optimizer and a language model coaching agent to do three things: