Samsung will soon use its wearable technology to enable early detection and monitoring of left ventricular systolic dysfunction (LVSD), a serious cardiovascular condition responsible for approximately half of all heart failures and is more fatal than some cancers.

Similarly, the South Korean firm is advancing brain-computer interface (BCI) technologies by overcoming the limitations of bulky devices to unlock potential in mental health management and productivity.

LVSD stands out as one of the most fatal cardiovascular diseases, with a five-year survival rate of only 50% following diagnosis. As a result, early detection of LVSD is critical, as timely diagnosis along with medication and lifestyle adjustments, can significantly reduce hospitalisation and lower the risk of death.

Samsung has overcome this limitation with AI algorithms that were developed with Medical AI (www.medicalai.com), a Korean medical device company specialising in AI-based ECG technology. These algorithms were developed based on Medical AI’s in-house algorithm for the 12-lead ECG analysis, which is already deployed across more than 100 major hospitals in Korea and used for 120,000 patients monthly, bringing clinically proven, real-word reliability that led to securing regulatory approval from South Korea’s Ministry of Food & Drug Safety (MFDS) as the first smart watch to gain LVSD detection capabilities.

This technology not only enables early screening for asymptomatic individuals but also aims to reduce the surging healthcare costs associated with heart failure by promoting early diagnosis and timely treatment. Furthermore, this product aligns with global healthcare priorities, including personalised patient care, proactive health management, lowering healthcare burdens, and advancing the application of AI in medicine.

Much like the work with Medical AI on LVSD detection, Samsung (www.samsung.com) recently partnered with Hanyang University’s Department of Biomedical Engineering to develop an around-the-ear electroencephalogram (EEG) prototype device, advancing BCI technology with better wearability and precision.

Engineered to overcome limitations of traditional EEG systems, the ear-EEG offers a sleek, ergonomic design that allows seamless brainwave monitoring outside laboratory settings. Designed to capture high-quality signals with electrodes around the ear, the research prototype delivers strong real-world application potential.

It accurately detected the onset of drowsiness in real time, showcasing its potential to enhance learning efficiency and support focus in education and beyond.

Using AI to analyse brainwaves, the device identified participants’ personal video preferences with 92.86% accuracy, pointing to potential applications in neuromarketing and entertainment.

This research was recently featured in the IEEE Sensors Journal (ieeexplore.ieee.org/abstract/document/11123617).

“This study is a prime example of academia-industry collaboration being recognised internationally for its scholarly significance,” said Chang-Hwan Im of Hanyang University (www.hanyang.ac.kr). “The technology we developed is not limited to education and marketing but has the potential to expand into diverse fields such as entertainment and mental health management.”