AI model could use heart rhythm data to detect premature aging and cognitive decline

Electrocardiogram tests – which measure the heart's electrical activity – could someday be paired with an artificial intelligence model to detect premature aging and cognitive decline, new research suggests.

The study found people with accelerated ECG age had lower cognitive test scores than those experiencing normal aging. Preliminary findings will be presented Wednesday at the American Stroke Association's International Stroke Conference in Los Angeles. The findings are considered preliminary until full results are published in a peer-reviewed journal.

"Unlike chronological age, which is based on years lived, ECG age reflects the functional status of the heart and potentially the entire organism at the tissue level, providing insights into aging and health status," lead study author Bernard Ofosuhene said in a news release. He is a clinical research coordinator in the department of medicine at the UMass Chan Medical School in Worcester, Massachusetts.

Every time the heart beats, it emits an electrical impulse, or wave. An ECG, also known as an EKG, translates these impulses into wavy lines on paper, allowing doctors to spot heart problems. For this study, researchers designed an AI model to predict a person's biological age using their ECG data. Biological age reflects how a person's cells and tissues may be deteriorating.

Prior studies have shown that ECG age can help predict heart disease and death. But little was known about its relationship to cognitive impairment. The researchers note that since ECGs are widely used in heart and stroke diagnoses, the new tool could help flag people at risk for cognitive...