HolmesAI Unveils AI Wearable Platform to Detect Arrhythmias & Predict Cardiac Arrest Risk at Home

The newly completed system, named CLholmes, has been designed to work with wearable technology such as smartwatches, enabling continuous heart monitoring outside hospital environments.

HolmesAI, a South Korean-based digital health AI startup, has announced the completion of CLholmes, an artificial intelligence-powered diagnostic platform that connects with wearable devices to detect multiple cardiac arrhythmias and estimate the risk of cardiac arrest within the next 24 hours using only ECG data.

The newly completed system, named CLholmes, has been designed to work with wearable technology such as smartwatches, enabling continuous heart monitoring outside hospital environments.

Sudden cardiac arrest remains one of the leading causes of unexpected death worldwide, often occurring without clear warning signs. Conventional risk assessment typically depends on hospital-based tests, intermittent ECG recordings, and clinician interpretation, which can limit early detection.

In recent years, advances in AI and wearable sensors have opened new possibilities for continuous, real-world cardiac monitoring, allowing patterns in heart rhythms to be analyzed over longer periods. CLholmes has emerged from this broader shift toward prevention-focused digital health and remote patient monitoring.

The core feature of CLholmes is its ability to predict the likelihood of cardiac arrest within 24 hours using ECG data alone, without relying on additional hospital diagnostics.

HolmesAI has positioned the platform as a tool that can support everyday health routines by continuously analyzing heart signals captured through wearable devices. The AI model behind the system was developed through joint research conducted by professors Lee Hyung-cheol and Lee Hyun-hoon of Seoul National University Hospital.

Beyond individual monitoring, HolmesAI has said it is working to develop CLholmes into a digital health service that links ECG data from wearables to patients, attending physicians, and emergency medical centres. The goal is to enable real-time alerts when the system identifies elevated cardiac arrest risk, potentially shortening response times during critical situations.

In combining wearable technology with medical AI, the startup has described the platform as a next-generation remote patient monitoring model that could help reduce deaths associated with sudden cardiac arrest.

As part of its global expansion strategy, HolmesAI opened a New York office in January to support entry into the U.S. and broader international digital healthcare markets.

“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-centred healthcare ecosystem that protects lives beyond hospital settings," a HolmesAI representative said.

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