Curated News
By: NewsRamp Editorial Staff
November 09, 2026
AI Smartwatch ECG Analysis May Detect Hidden Heart Condition
TLDR
- Medical AI Co.'s model detected LVSD from Apple and Samsung smartwatch ECGs, but brand inconsistencies affected 9% of cases.
- The AI analyzed 30-second single-lead smartwatch ECGs; requiring 2 of 3 consecutive positive days halved false positives but missed two LVSD cases.
- AI analysis of smartwatch ECGs may help flag hidden heart dysfunction, enabling earlier screening and better outcomes for asymptomatic people.
- In a study of 2,211 adults, an AI model identified reduced heart pumping from smartwatch ECGs, though results varied by brand and recording day.
Impact - Why it Matters
Left ventricular systolic dysfunction often goes unnoticed until it causes serious heart failure, so a noninvasive way to flag it earlier could be transformative. Smartwatches are already worn by millions, and this research suggests that with AI analysis, they might one day serve as a first-line screening tool to prompt confirmatory echocardiograms. However, the brand-dependent variability and trade-offs in repeat testing mean consumers should not yet rely on their smartwatch for diagnosis. The findings underscore the need for larger studies to standardize AI algorithms and testing protocols, but they also highlight the growing potential of wearable technology to bridge gaps in preventive cardiology.
Summary
An artificial intelligence (AI) model that analyzes ECG recordings from smartwatches may help identify people with left ventricular systolic dysfunction (LVSD), a hidden and dangerous heart condition, according to preliminary research presented at the American Heart Association’s Scientific Sessions 2026. The study, led by Hak Seung Lee, M.D., FAHA, chief medical officer of Medical AI Co., Ltd., which developed the AI model, and a cardiologist at the Digital Healthcare Institute, Sejong Medical Research Institute in Incheon, South Korea, involved 2,211 adults who had ECGs recorded on both an Apple Watch and a Samsung Galaxy Watch during the same clinic visit. The AI model distinguished people with and without LVSD about equally well on both watches. However, when the same AI-score cutoff was applied to both, 200 participants (9%) were classified as positive on one watch and negative on the other.
In a second group of 146 adults who recorded ECGs at home on their own smartwatches, requiring positive results on at least 2 of 3 consecutive days halved false-positive results (from 18 to 9 among 70 people without LVSD) in the 108 who recorded for at least 5 days, but missed two more people with LVSD compared to a single-positive-day rule. Among all 146 home-recording participants, 81% of those with consistently positive results had LVSD confirmed by echocardiography, versus about 6% of those with consistently negative results. “A single smartwatch ECG is a snapshot, and repeated recordings can give different results,” Lee said. “Requiring repeated positive results reduced false positives in our study, yet it also missed some additional cases that should have been positive. Larger studies are needed to determine how best to use these results to guide further evaluation.”
The findings suggest that smartwatch ECGs analyzed with AI may help identify people who need additional heart screening such as an echocardiogram, but more research is needed before smartwatch ECG readings can replace traditional screening exams. The study has limitations, including being conducted at one hospital in South Korea and including patients referred for echocardiography, so the results may not apply to the general population. The research was featured in a release link and is considered preliminary until published in a peer-reviewed journal.
Source Statement
This curated news summary relied on content distributed by NewMediaWire. Read the original source here, AI Smartwatch ECG Analysis May Detect Hidden Heart Condition
