AI Analysis of ECG Data Reveals Potential Link Between Heart Function and Cognitive Performance

Researchers have developed an artificial intelligence model that may potentially use electrocardiogram (ECG) tests to detect premature aging and cognitive decline, according to a preliminary study to be presented at the American Stroke Association's International Stroke Conference 2025.

The study, led by Bernard Ofosuhene from UMass Chan Medical School, analyzed data from over 63,000 participants in the UK Biobank. The research utilized a deep neural network to predict biological age based on ECG data, revealing a significant correlation between heart function and cognitive performance.

By categorizing participants into three groups - normal aging, accelerated ECG-aging, and decelerated ECG-aging - researchers discovered notable differences in cognitive test performance. Participants with ECG-ages younger than their chronological age performed better on 6 of 8 cognitive tests, while those with accelerated ECG-aging performed worse.

This research represents a potential breakthrough in understanding the connection between heart health and cognitive function. Unlike traditional age measurement based on years lived, ECG-age reflects the functional status of the heart and potentially the entire organism at the tissue level.

However, the study acknowledges several limitations. The research was conducted on participants aged 43 to 85, primarily of European descent, which may limit the generalizability of the findings. Future research aims to investigate potential gender differences and explore the applicability across more diverse populations.

Fernando D. Testai, a neurology professor not involved in the study, highlighted the potential significance of this research. He suggested that ECG data collected in medical offices or through wearable devices could provide a quick, objective method for assessing cognitive ability, particularly in areas with limited access to neuropsychiatric specialists.

While the findings are preliminary and require further validation, the study opens promising avenues for early detection and intervention in age-related cognitive decline. The potential to use readily available ECG data as a predictive tool for cognitive health represents an innovative approach to understanding the complex relationship between heart and brain aging.