Yonsei University · 医学
Professor Seul Ki Han's research lab specializes in advanced signal processing, intelligent monitoring systems, and biomedical engineering applications. The lab focuses on developing data-driven methodologies for real-time condition monitoring and predictive maintenance in precision manufacturing, as well as enhancing navigation accuracy through advanced filtering techniques like Kalman filtering. Additionally, the lab explores rehabilitation technologies and human physiological responses to environmental stimuli, particularly in stroke recovery and therapeutic environments. These interdisciplinary efforts integrate sensor fusion, signal analysis, and control systems to improve health outcomes and industrial efficiency.
Figures are computed from collected data and may differ slightly.
Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver diseases worldwide, with a global prevalence of approximately 30%. However, the prevalence of NAFLD has been variously reported depending on the comorbidities. The rising prevalence of obesity in both the adult and pediatric populations is projected to consequently continue increasing NAFLD prevalence. It is a major cause of chronic liver disease worldwide, including cirrhosis and hepatocellular carcinoma (HCC). NAFLD has
A Kalman filter was developed to improve the DGPS position estimates for a parallel tracking application.Applying Kalman filtering to raw DGPS measurement data effectively removes the DGPS noise and reduces therootmeansquared (RMS) positioning error. In our study, the maximum crosstracking error (XTE) was reduced from 9.83 mto 2.76 m by Kalman filtering. The Kalman filter also reduced the rootmeansquared XTE from 0.58 m to 0.56 m. In thedirection of travel, the Kalman filter had much smaller pos
Abstract Estimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain features of commonly sensed signals can provide an early indication of tool wear and improve its prediction accuracy for prognostics and health management. This paper presents a data‐driven methodology and a complete tool chain for the inference of preci
[Purpose] The purpose of this study was to compare changes in balance ability of land exercise and underwater exercise on chronic stroke patients. [Subjects] A total of 60 patients received exercise for 40 minutes, three times a week, for 6 weeks. [Methods] Subjects from both groups performed general conventional treatment during the experimental period. In addition, all subjects engaged in extra treatment sessions. This extra treatment consisted of unstable surface exercise. The underwater exer
[Purpose] The purpose of this study was to investigate the perceived treatment times and emotional reactions under different light colors in the treatment room. [Subjects and Methods] Subjects in this study were 20 healthy young students in their 20s. Under each lighting condition (blue, red, white, and yellow) differentiated by color, each subject laid on a therapeutic bed and underwent ultrasound therapy. Subjects were instructed to press a stopwatch every 1 minute, for a total of 5 times, aft
This study addresses the passive target tracking problem using the range difference (RD) information measured by sea‐skimming anti‐ship missiles. Apart from the conventional non‐linear filtering approaches, the RD‐based passive target tracking problem is newly formulated within the framework of the recently developed non‐conservative robust Kalman filter (NCRKF). By applying NCRKF, the authors are able to cope with the performance degradation in the process of adopting linear measurement model a
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