Improving performance in motor imagery BCI-based control applications via virtually embodied feedback

JW Choi, S Huh, S Jo - Computers in Biology and Medicine, 2020 - Elsevier
Objective Brain-computer interfaces (BCIs) based on motor imagery (MI) are commonly used
for control applications. However, these applications require strong and discriminant neural …

Observing actions through immersive virtual reality enhances motor imagery training

JW Choi, BH Kim, S Huh, S Jo - IEEE Transactions on Neural …, 2020 - ieeexplore.ieee.org
Visual information plays an essential role in enhancing neural activity during mental practices.
Previous research has shown that using different visual scenarios during mental practices …

Maximization and restoration: Action segmentation through dilation passing and temporal reconstruction

J Park, D Kim, S Huh, S Jo - Pattern Recognition, 2022 - Elsevier
Action segmentation aims to split videos into segments of different actions. Recent work
focuses on dealing with long-range dependencies of long, untrimmed videos, but still suffers …

Surface-functionalized SERS platform for deep learning-assisted diagnosis of Alzheimer's disease

M Kim, S Huh, HJ Park, SH Cho, MY Lee, S Jo… - Biosensors and …, 2024 - Elsevier
Early diagnosis of Alzheimer's disease is crucial to stall the deterioration of brain function, but
conventional diagnostic methods require complicated analytical procedures or inflict acute …

Asynchronous motor imagery BCI and LiDAR-based shared control system for intuitive wheelchair navigation

JW Choi, J Park, S Huh, S Jo - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Mapping drivers’ thoughts directly to mobility system control would make driving more intuitive
as if the mobility system is an extension of their own body. Such a system would allow …

Improved explanatory efficacy on human affect and workload through interactive process in artificial intelligence

BH Kim, S Koh, S Huh, S Jo, S Choi - IEEE Access, 2020 - ieeexplore.ieee.org
Despite recent advances in the field of explainable artificial intelligence systems, a concrete
quantitative measure for evaluating the usability of such systems is nonexistent. Ensuring …

An eog/eeg-based hybrid brain-computer interface for chess

JW Choi, E Rho, S Huh, S Jo - 2018 IEEE international …, 2018 - ieeexplore.ieee.org
Most user interfaces require motion; the motor-impaired therefore do not have many options
to choose from. Electroencephalography (EEG) and the analysis of eye movement are two …

Development of a Prediction Model for Daily PM2.5 in Republic of Korea by Using an Artificial Neutral Network

JW Huh, JS Youn, PM Park, KJ Jeon, S Park - Applied Sciences, 2023 - mdpi.com
This study aims to develop PM 2.5 prediction models using air pollutant data (PM 10 , NO 2 ,
SO 2 , O 3 , CO, and PM 2.5 ) and meteorological data (temperature, humidity, wind speed, …

Daily PM2.5 Estimation using Multiple Linear Regression and Artificial Neural Networks Before 2015

JW Huh, SJ Park - Journal of Industrial Technology, 2024 - koreascience.kr
Since 2015, the PM 2.5 measurement data has been publicly available nationwide in South
Korea, but its use is restricted to after 2015, unlike other air pollutants. To overcome this …

HybGrasp: A Hybrid Learning-to-Adapt Architecture for Efficient Robot Grasping

J Mun, KT Giang, Y Lee, N Oh, S Huh… - IEEE Robotics and …, 2023 - ieeexplore.ieee.org
Despite the prevalence of robotic manipulation tasks in various real-world applications of
different requirements and needs, there has been a lack of focus on enhancing the adaptability …