<(From Left) Professor Hyunjoo Jenny Lee, Dr.Sang-Mok Lee, Ph.D candidate Xiaojia Liang> Conventional wearable ultrasound sensors have been limited by low power output and poor structural stability, making them unsuitable for high-resolution imaging or therapeutic applications. A KAIST research team has now overcome these challenges by developing a flexible ultrasound sensor with statically adjustable curvature. This breakthrough opens new possibilities for wearable medical devices that
2025-11-12<Professor Hyunjoon Park, M.S candidate Eun-ju Kang, Prospective M.S candidate Jae-seong Kim, undergraduate student Min-su Kim> A team led by Professor Hyunjoon Park from the Department of Industrial Design won the ‘Best of the Best’ award at the 2025 Red Dot Design Awards, one of the world's top three design awards, for their 'Angel Robotics WSF1 VISION Concept.' The design for the next-generation wearable robot for people with paraplegia successfully implements functional
2025-08-09A KAIST research team led by Professor Keon Jae Lee has proposed an innovative theoretical framework and research strategies for AI-based wearable blood pressure sensors, paving the way for continuous and non-invasive cardiovascular monitoring. Hypertension is a leading chronic disease affecting over a billion people worldwide and is a major risk factor for severe cardiovascular conditions such as myocardial infarction, stroke, and heart failure. Traditional blood pressure measurement relies o
2025-03-04- Professor Seunghyup Yoo’s research team of the School of Electrical Engineering developed an ultralow-power carbon dioxide (CO2) sensor using a flexible and thin organic photodiode, and succeeded in real-time breathing monitoring by attaching it to a commercial mask - Wearable devices with features such as low power, high stability, and flexibility can be utilized for early diagnosis of various diseases such as chronic obstructive pulmonary disease and sleep apnea < Photo 1. Fro
2025-02-13- A international joint research team of KAIST and the University of Michigan developed a digital biomarker for predicting symptoms of depression based on data collected by smartwatches - It has the potential to be used as a medical technology to replace the economically burdensome fMRI measurement test - It is expected to expand the scope of digital health data analysis The CORONA virus pandemic also brought about a pandemic of mental illness. Approximately one billion people worldwide suf
2025-01-20