Jinung An - Academia.edu (original) (raw)

Papers by Jinung An

Research paper thumbnail of Trained by demonstration humanoid robot controlled via a BCI system for telepresence

2018 6th International Conference on Brain-Computer Interface (BCI), 2018

Research paper thumbnail of fNIRS Neural Signal Classification of Four Finger Tasks using Ensemble Multitree Genetic Programming

Accuracy of classification and recognition in neural signal is the most important issue to evalua... more Accuracy of classification and recognition in neural signal is the most important issue to evaluate the clinical assessment or extraction of features in brain computer interface. Especially, classification of multitasks by measuring functional Near-Infrared Spectroscopy (fNIRS) is a challenging due to its low spatiotemporal resolution. To improve the classification accuracy of fNIRS neural signals for multitasks, an evolutionary computing method was proposed. Four healthy participants performed four finger tasks which are digit-active, digit-passive, thumb-active and thumb-passive. To classify the four tasks, a multitask classifier was devised by the ensemble multitree genetic programming (EMGP). The experimental results validate the performance of the proposed classifier. The comparison of the conventional and proposed classifiers at the real classification experiment shows the higher accuracy of the proposed method. Moreover, it reveals the improvement of classification accuracy w...

Research paper thumbnail of Hemispheric asymmetry in hand preference of right-handers for passive vibrotactile perception: an fNIRS study

Scientific Reports, 2020

Hemispheric asymmetry in hand preference for passive cutaneous perception compared to active hapt... more Hemispheric asymmetry in hand preference for passive cutaneous perception compared to active haptic perception is not well known. A functional near-infrared spectroscopy was used to evaluate the laterality of cortical facilitation when 31 normal right-handed participants were involved in 205 Hz passive vibrotactile cutaneous stimuli on their index fingers of preferred and less-preferred hand. Passive cutaneous perception resulted that preferred (right) hand stimulation was strongly leftward lateralized, whereas less-preferred (left) hand stimulation was less lateralized. This confirms that other manual haptic exploration studies described a higher hemispheric asymmetry in right-handers. Stronger cortical facilitation was found in the right primary somatosensory cortex (S1) and right somatosensory association area (SA) during left-hand stimulation but not right-hand stimulation. This finding suggests that the asymmetric activation in the S1 and SA for less-preferred (left) hand stimu...

Research paper thumbnail of Distinction of directional coupling in sensorimotor networks between active and passive finger movements using fNIRS

Biomedical Optics Express, 2018

Research paper thumbnail of NIRS-based experimental evaluation of driver back fatigue during long-term driving

Biotechnology & Biotechnological Equipment, 2018

Research paper thumbnail of The difference in cortical activation pattern for complex motor skills: A functional near- infrared spectroscopy study

Scientific Reports, 2019

The human brain is lateralized to dominant or non-dominant hemispheres, and controlled through la... more The human brain is lateralized to dominant or non-dominant hemispheres, and controlled through large-scale neural networks between correlated cortical regions. Recently, many neuroimaging studies have been conducted to examine the origin of brain lateralization, but this is still unclear. In this study, we examined the differences in brain activation in subjects according to dominant and non-dominant hands while using chopsticks. Fifteen healthy right-handed subjects were recruited to perform tasks which included transferring almonds using stainless steel chopsticks. Functional near-infrared spectroscopy (fNIRS) was used to acquire the hemodynamic response over the primary sensory-motor cortex (SM1), premotor area (PMC), supplementary motor area (SMA), and frontal cortex. We measured the concentrations of oxy-hemoglobin and deoxy-hemoglobin induced during the use of chopsticks with dominant and non-dominant hands. While using the dominant hand, brain activation was observed on the c...

Research paper thumbnail of Motion Artifact Correction of Multi-Measured Functional Near-Infrared Spectroscopy Signals Based on Signal Reconstruction Using an Artificial Neural Network

Sensors, 2018

In this paper, a new motion artifact correction method is proposed based on multi-channel functio... more In this paper, a new motion artifact correction method is proposed based on multi-channel functional near-infrared spectroscopy (fNIRS) signals. Recently, wavelet transform and hemodynamic response function-based algorithms were proposed as methods of denoising and detrending fNIRS signals. However, these techniques cannot achieve impressive performance in the experimental environment with lots of movement such as gait and rehabilitation tasks because hemodynamic responses have features similar to those of motion artifacts. Moreover, it is difficult to correct motion artifacts in multi-measured fNIRS systems, which have multiple channels and different noise features in each channel. Thus, a new motion artifact correction method for multi-measured fNIRS is proposed in this study, which includes a decision algorithm to determine the most contaminated fNIRS channel based on entropy and a reconstruction algorithm to correct motion artifacts by using a wavelet-decomposed back-propagation...

Research paper thumbnail of Selective Detrending using Baseline Drift Detection Index for Task-dependant fNIRS Signal

Advances in Science, Technology and Engineering Systems Journal, 2017

Research paper thumbnail of A Study of an Implementable Sun Tracking Algorithm for Portable Systems

Journal of Power Electronics, 2013

Research paper thumbnail of Design and evaluation of action observation and motor imagery based BCIs using Near-Infrared Spectroscopy

Research paper thumbnail of A Tree Based Self-routing Scheme for Mobility Support in Wireless Sensor Networks

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2009

Research paper thumbnail of An Approach to Self-Assembling Swarm Robots Using Multitree Genetic Programming

The Scientific World Journal, 2013

In recent days, self-assembling swarm robots have been studied by a number of researchers due to ... more In recent days, self-assembling swarm robots have been studied by a number of researchers due to their advantages such as high efficiency, stability, and scalability. However, there are still critical issues in applying them to practical problems in the real world. The main objective of this study is to develop a novel self-assembling swarm robot algorithm that overcomes the limitations of existing approaches. To this end, multitree genetic programming is newly designed to efficiently discover a set of patterns necessary to carry out the mission of the self-assembling swarm robots. The obtained patterns are then incorporated into their corresponding robot modules. The computational experiments prove the effectiveness of the proposed approach.

Research paper thumbnail of Enhanced bandwidth of a microstrip antenna using a parasitic mushroom-like metamaterial structure for multi-robot cooperative navigation

Journal of the Korean Physical Society, 2015

Research paper thumbnail of Portable fire evacuation guide robot system

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

Research paper thumbnail of A Simple Wavelet Method for Automated Detection of Epileptic Neural Spikes in Electroencephalogram

INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences, 2010

Research paper thumbnail of Miniaturized Force-Torque Sensor Built in a Robot End-Effector for Delicate Tool-Tip Gripping Control

Elektronika ir Elektrotechnika, 2014

Research paper thumbnail of A preliminary experimental study on haptic teleoperation of mobile robot with variable force feedback gain

2010 IEEE Haptics Symposium, 2010

Research paper thumbnail of Minimizing inter-subject variability in fNIRS-based brain–computer interfaces via multiple-kernel support vector learning

Medical Engineering & Physics, 2013

Research paper thumbnail of Decision Support Algorithm for Diagnosis of ADHD Using Electroencephalograms

Journal of Medical Systems, 2011

Research paper thumbnail of Localization of Mobile Robot Based on Fusion of Artificial Landmark and RF TDOA Distance under Indoor Sensor Network

International Journal of Advanced Robotic Systems, 2011

In this paper, we propose a robust and real-time localization method for dynamic environments bas... more In this paper, we propose a robust and real-time localization method for dynamic environments based on a sensor network; the method combines landmark image information obtained from an ordinary camera and distance information obtained from sensor nodes in an indoor environment. The sensor network provides an effective method for a mobile robot to adapt to changes and guides it across a geographical network area. To enhance the performance, we used a charge-coupled device (CCD) camera and artificial landmarks for self-localization. Experimental results showed that global localization can be achieved with high robustness and accuracy using the proposed localization method.

Research paper thumbnail of Trained by demonstration humanoid robot controlled via a BCI system for telepresence

2018 6th International Conference on Brain-Computer Interface (BCI), 2018

Research paper thumbnail of fNIRS Neural Signal Classification of Four Finger Tasks using Ensemble Multitree Genetic Programming

Accuracy of classification and recognition in neural signal is the most important issue to evalua... more Accuracy of classification and recognition in neural signal is the most important issue to evaluate the clinical assessment or extraction of features in brain computer interface. Especially, classification of multitasks by measuring functional Near-Infrared Spectroscopy (fNIRS) is a challenging due to its low spatiotemporal resolution. To improve the classification accuracy of fNIRS neural signals for multitasks, an evolutionary computing method was proposed. Four healthy participants performed four finger tasks which are digit-active, digit-passive, thumb-active and thumb-passive. To classify the four tasks, a multitask classifier was devised by the ensemble multitree genetic programming (EMGP). The experimental results validate the performance of the proposed classifier. The comparison of the conventional and proposed classifiers at the real classification experiment shows the higher accuracy of the proposed method. Moreover, it reveals the improvement of classification accuracy w...

Research paper thumbnail of Hemispheric asymmetry in hand preference of right-handers for passive vibrotactile perception: an fNIRS study

Scientific Reports, 2020

Hemispheric asymmetry in hand preference for passive cutaneous perception compared to active hapt... more Hemispheric asymmetry in hand preference for passive cutaneous perception compared to active haptic perception is not well known. A functional near-infrared spectroscopy was used to evaluate the laterality of cortical facilitation when 31 normal right-handed participants were involved in 205 Hz passive vibrotactile cutaneous stimuli on their index fingers of preferred and less-preferred hand. Passive cutaneous perception resulted that preferred (right) hand stimulation was strongly leftward lateralized, whereas less-preferred (left) hand stimulation was less lateralized. This confirms that other manual haptic exploration studies described a higher hemispheric asymmetry in right-handers. Stronger cortical facilitation was found in the right primary somatosensory cortex (S1) and right somatosensory association area (SA) during left-hand stimulation but not right-hand stimulation. This finding suggests that the asymmetric activation in the S1 and SA for less-preferred (left) hand stimu...

Research paper thumbnail of Distinction of directional coupling in sensorimotor networks between active and passive finger movements using fNIRS

Biomedical Optics Express, 2018

Research paper thumbnail of NIRS-based experimental evaluation of driver back fatigue during long-term driving

Biotechnology & Biotechnological Equipment, 2018

Research paper thumbnail of The difference in cortical activation pattern for complex motor skills: A functional near- infrared spectroscopy study

Scientific Reports, 2019

The human brain is lateralized to dominant or non-dominant hemispheres, and controlled through la... more The human brain is lateralized to dominant or non-dominant hemispheres, and controlled through large-scale neural networks between correlated cortical regions. Recently, many neuroimaging studies have been conducted to examine the origin of brain lateralization, but this is still unclear. In this study, we examined the differences in brain activation in subjects according to dominant and non-dominant hands while using chopsticks. Fifteen healthy right-handed subjects were recruited to perform tasks which included transferring almonds using stainless steel chopsticks. Functional near-infrared spectroscopy (fNIRS) was used to acquire the hemodynamic response over the primary sensory-motor cortex (SM1), premotor area (PMC), supplementary motor area (SMA), and frontal cortex. We measured the concentrations of oxy-hemoglobin and deoxy-hemoglobin induced during the use of chopsticks with dominant and non-dominant hands. While using the dominant hand, brain activation was observed on the c...

Research paper thumbnail of Motion Artifact Correction of Multi-Measured Functional Near-Infrared Spectroscopy Signals Based on Signal Reconstruction Using an Artificial Neural Network

Sensors, 2018

In this paper, a new motion artifact correction method is proposed based on multi-channel functio... more In this paper, a new motion artifact correction method is proposed based on multi-channel functional near-infrared spectroscopy (fNIRS) signals. Recently, wavelet transform and hemodynamic response function-based algorithms were proposed as methods of denoising and detrending fNIRS signals. However, these techniques cannot achieve impressive performance in the experimental environment with lots of movement such as gait and rehabilitation tasks because hemodynamic responses have features similar to those of motion artifacts. Moreover, it is difficult to correct motion artifacts in multi-measured fNIRS systems, which have multiple channels and different noise features in each channel. Thus, a new motion artifact correction method for multi-measured fNIRS is proposed in this study, which includes a decision algorithm to determine the most contaminated fNIRS channel based on entropy and a reconstruction algorithm to correct motion artifacts by using a wavelet-decomposed back-propagation...

Research paper thumbnail of Selective Detrending using Baseline Drift Detection Index for Task-dependant fNIRS Signal

Advances in Science, Technology and Engineering Systems Journal, 2017

Research paper thumbnail of A Study of an Implementable Sun Tracking Algorithm for Portable Systems

Journal of Power Electronics, 2013

Research paper thumbnail of Design and evaluation of action observation and motor imagery based BCIs using Near-Infrared Spectroscopy

Research paper thumbnail of A Tree Based Self-routing Scheme for Mobility Support in Wireless Sensor Networks

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2009

Research paper thumbnail of An Approach to Self-Assembling Swarm Robots Using Multitree Genetic Programming

The Scientific World Journal, 2013

In recent days, self-assembling swarm robots have been studied by a number of researchers due to ... more In recent days, self-assembling swarm robots have been studied by a number of researchers due to their advantages such as high efficiency, stability, and scalability. However, there are still critical issues in applying them to practical problems in the real world. The main objective of this study is to develop a novel self-assembling swarm robot algorithm that overcomes the limitations of existing approaches. To this end, multitree genetic programming is newly designed to efficiently discover a set of patterns necessary to carry out the mission of the self-assembling swarm robots. The obtained patterns are then incorporated into their corresponding robot modules. The computational experiments prove the effectiveness of the proposed approach.

Research paper thumbnail of Enhanced bandwidth of a microstrip antenna using a parasitic mushroom-like metamaterial structure for multi-robot cooperative navigation

Journal of the Korean Physical Society, 2015

Research paper thumbnail of Portable fire evacuation guide robot system

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

Research paper thumbnail of A Simple Wavelet Method for Automated Detection of Epileptic Neural Spikes in Electroencephalogram

INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences, 2010

Research paper thumbnail of Miniaturized Force-Torque Sensor Built in a Robot End-Effector for Delicate Tool-Tip Gripping Control

Elektronika ir Elektrotechnika, 2014

Research paper thumbnail of A preliminary experimental study on haptic teleoperation of mobile robot with variable force feedback gain

2010 IEEE Haptics Symposium, 2010

Research paper thumbnail of Minimizing inter-subject variability in fNIRS-based brain–computer interfaces via multiple-kernel support vector learning

Medical Engineering & Physics, 2013

Research paper thumbnail of Decision Support Algorithm for Diagnosis of ADHD Using Electroencephalograms

Journal of Medical Systems, 2011

Research paper thumbnail of Localization of Mobile Robot Based on Fusion of Artificial Landmark and RF TDOA Distance under Indoor Sensor Network

International Journal of Advanced Robotic Systems, 2011

In this paper, we propose a robust and real-time localization method for dynamic environments bas... more In this paper, we propose a robust and real-time localization method for dynamic environments based on a sensor network; the method combines landmark image information obtained from an ordinary camera and distance information obtained from sensor nodes in an indoor environment. The sensor network provides an effective method for a mobile robot to adapt to changes and guides it across a geographical network area. To enhance the performance, we used a charge-coupled device (CCD) camera and artificial landmarks for self-localization. Experimental results showed that global localization can be achieved with high robustness and accuracy using the proposed localization method.