South Korean healthtech startup Deepmedi wants to make everyday health monitoring as simple as looking into a camera. The company has developed an AI-powered, non-contact biosignal measurement platform that tracks blood pressure, heart rate, stress levels, and fatigue through a smartphone, laptop, or kiosk-no wearables, sensors, or hospital visits required.

Unlike many camera-based wellness apps, Deepmedi's system is rooted in real biosignal data rather than surface-level estimations. Its core technology, remote photoplethysmography (rPPG), uses AI image processing to extract micro-changes in facial blood flow and translate them into clinical-grade metrics. According to the company, the algorithm reaches 97% accuracy with measurement times as fast as 15 seconds. Beyond simple readings, Deepmedi's platform also includes an enterprise dashboard that visualizes stress trends, fatigue alerts, and heart-rate variability insights, positioning the company not just as a measurement tool but as a data intelligence layer for health operations.

Importantly, Deepmedi's technology has already been validated at the regulatory level in South Korea, receiving Class II medical device certification from the Ministry of Food and Drug Safety (KMFDS). It is the only camera-based health monitoring technology in Korea to hold this status, strengthening its credibility as it enters global markets.

Under its CareUp brand, Deepmedi is applying this tech to real-world use cases, especially in industrial health and safety. Construction, logistics, and manufacturing sites are using CareUp kiosks and mobile tools to run pre-shift stress screenings, fatigue checks, and heat-stroke risk detection, based entirely on camera readings. For companies managing thousands of workers, the value is immediate: no wearables to distribute, no compliance burden, and scalable monitoring driven by live data streams rather than sporadic manual checks.

Deepmedi's dataset is another differentiator. The company has collected over 8,000 subjects and 7.6 million matched video–biosignal pairs, enabling its models to learn from diverse real-world conditions. Its research on AI-based blood pressure estimation and HRV-driven stress analysis has been presented at leading global conferences, drawing growing international attention.

That traction is translating into global pilots. In Japan, Deepmedi is running SDK integrations and PoC deployments for heat-stroke prediction in outdoor worksites. In the United States, the company is collaborating with Emory University to refine its algorithms with multi-ethnic datasets-key to ensuring fairness and robustness. Partnerships in the Middle East and Southeast Asia are focused on workforce health analytics and productivity management.

“We aim to build a global digital health platform where people can monitor their health anytime, anywhere,” said Kwang-Jin Lee, CEO of Deepmedi. With its data-driven approach, expanding pilots, and enterprise-grade dashboard, Deepmedi is positioning itself as a foundational layer for the next generation of camera-based health intelligence.

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