An at-home diagnostic platform that can verify 21 types of cardiac arrhythmia and predict cardiac arrest risks within 24 hours has been developed based on artificial intelligence, according to HolmesAI, a digital health care AI company.
The company announced Friday that it has finalized the development of its wearable-integrated medical AI solution, CLholmes. It aims to predict the likelihood of cardiac arrest within 24 hours using only electrocardiogram data, without the need to rely on hospital diagnostics, and to allow continuous monitoring and preventive health care routine in everyday life.
The technology was developed through joint research by professors Lee Hyung-cheol and Lee Hyun-hoon of Seoul National University Hospital.
HolmesAI said it is developing CLholmes into a digital health service that can connect ECG data generated by wearable devices such as smartwatches to patients, attending physicians and emergency medical centers to detect and provide immediate alerts in cases of cardiac arrest risks.
In combining wearable technology with medical AI, CLholmes said it represents a next-generation remote patient monitoring model, which is expected to contribute to the prevention of deaths caused by sudden cardiac arrest. CLholmes was awarded the Innovation Award at CES 2025.
In line with the completion of the CLholmes AI development, HolmesAI opened a New York office in the United States in January, as part of its expansion into the global digital health care market.
"Through the establishment of our New York office, we aim to introduce our wearable-based digital health and medical AI convergence model to the global market and accelerate the development of a prevention-centered healthcare ecosystem that protects lives beyond hospital settings," a HolmesAI representative said.
HolmesAI was co-founded by Lee Kwang-hyun, who is also the chief strategy officer. Lee completed his bachelor's and master's degrees in data science at New York University. (khnews@heralcorp.com)
khnews@heraldcorp.com


