
Smartwatches fail to measure blood glucose levels
A rigorous new evaluation reveals that wrist-worn wearables capture no real blood glucose data, exposing a major flaw in non-invasive tracking claims.
Discover the newest research about AI innovations in ⌚ Wearables.

A rigorous new evaluation reveals that wrist-worn wearables capture no real blood glucose data, exposing a major flaw in non-invasive tracking claims.

Giving consumer smart ring data to a raw language model to spot depression fails completely, unless you teach it how to think first.

By blending cardiovascular physics into machine learning, researchers have cut the data needed to track continuous blood pressure in half.
A single week of wrist-worn movement data can forecast hundreds of future health conditions years before they are diagnosed.

Pharmaceutical giants are realizing that selling a weight-loss drug is only half the battle.

A new foundation model shows that overnight pulse oximetry data contains deep physiological signatures that can predict future hypertension and next-day blood sugar levels.

A quiet regulatory truce reveals exactly how far consumer wearables can push into clinical territory without triggering a federal crackdown.

A new AI system identifies a reversible “pre-disease” window for depression, proving that treatment timing matters more than the tool itself.

A new partnership between a smart ring maker and a pharmaceutical giant reveals how drugmakers are using consumer hardware to keep patients compliant.

Smartwatches and rings are marketed as lifesaving heart monitors, but new data shows their single-lead AI systems fail the very patients who need them most.