An artificial intelligence (AI) algorithm paired with the single-lead electrocardiogram (ECG) sensors on a smartwatch accurately diagnosed structural heart diseases, a study to be presented at the 2025 American Heart Association scientific sessions (7–10 November, New Orleans, USA) has demonstrated.
Researchers said this is the first prospective study to show that an AI algorithm can detect multiple structural heart diseases based on measures taken from a single-lead ECG sensor on the back and digital crown of a smartwatch.
“Millions of people wear smartwatches, and they are currently mainly used to detect heart rhythm problems such as atrial fibrillation. Structural heart diseases, on the other hand, are usually found with an echocardiogram, an advanced ultrasound imaging test of the heart that requires special equipment and isn’t widely available for routine screening,” said study author Arya Aminorroaya (Yale School of Medicine, New Haven, USA). “In our study, we explored whether the same smartwatches people wear every day could also help find these hidden structural heart diseases earlier, before they progress to serious complications or cardiac events.”
Researchers developed the AI algorithm using more than 266,000 12-lead ECG recordings from more than 110,000 adults. Based on this library of data, they developed an algorithm to identify structural heart disease from a single-lead ECG that can be obtained using smartwatch sensors. For this purpose, researchers isolated only one of the 12 leads of the ECG, which resembles the single-lead ECG on smartwatches. They also accounted for random interference in ECG signalling or “noise” that could arise during the recording of a single-lead ECG using real-world smartwatches.
The AI model was externally validated using data from people seeking care at community hospitals, as well as data from a population-based study from Brazil. Then, they prospectively recruited 600 participants who underwent 30-second, single-lead ECGs using a smartwatch to gauge the algorithm’s accuracy in a real-world setting.
The analysis found using single-lead ECGs obtained from hospital equipment, the AI model was very effective at distinguishing people with and without structural heart disease, scoring 92% on a standard performance scale (where 100% is perfect).
Among the 600 participants with the single-lead ECGs obtained from a smartwatch, the AI model maintained high performance at 88% for detecting structural heart disease. Additionally, the AI algorithm accurately identified most people with heart disease (86% sensitivity) and was accurate in ruling out heart disease (99% negative predictive value).
Researchers used a database of 266,054 ECGs from 110,006 patients who received testing and treatment at Yale New Haven Hospital between 2015 and 2023 to develop the AI-ECG algorithm. The algorithm was matched to ultrasound scans to see whether they had structural heart disease or not.
The AI model was then validated in 44,591 adults seeking care at four community hospitals and 3,014 participants from the population-based ELSA-Brasil study. The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) gathers important information about how chronic diseases develop and progress, focusing mainly on cardiovascular diseases and diabetes.
During the real-world prospective study, 600 patients wore the same type of smartwatch with a single-lead ECG sensor for 30 seconds on the same day they were getting a heart ultrasound. The median age of the participants was 62 years, and about half were women, 44% were non-Hispanic white, 15% non-Hispanic Black, 7% Hispanic, 1% Asian and 33% others. About 5% were found to have structural heart disease on the heart ultrasound.
Study limitations include a small number of patients with the actual disease in the prospective study and the number of false positive results.
“We plan to evaluate the AI tool in broader settings and explore how it could be integrated into community-based heart disease screening programmes to assess its potential impact on improving preventive care,” Aminorroaya said.
