• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.606-611
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• 2014

The understanding of another's behavior is a fundamental cognitive ability for primates including humans. Recent neuro-physiological studies suggested that there is a direct matching algorithm from visual observation onto an individual's own motor repertories for interpreting cognitive ability. The mirror neurons are known as core regions and are handled as a functionality of intent recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper, we addressed previous works used to model the function and mechanisms of mirror neurons and proposed a computational model of a mirror neuron system which can be used in human-robot interaction environments. The major focus of the computation model is the reproduction of an individual's motor repertory with different embodiments. The model's aim is the design of a continuous process which combines sensory evidence, prior task knowledge and a goal-directed matching of action observation and execution. We also propose a biologically inspired plausible equation model.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.537-542
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• 2011

A mirror neuron is a neuron fires both when an animal acts and when the animal observes the same action performed by another. We propose a method of 3D reconstruction for occluded object motion tracking like Mirror Neuron System to fire in hidden condition. For modeling system that intention recognition through fire effect like Mirror Neuron System, we calculate depth information using stereo image from a stereo camera and reconstruct three dimension data. Movement direction of object is estimated by optical flow with three-dimensional image data created by three dimension reconstruction. For three dimension reconstruction that enables tracing occluded part, first, picture data was get by stereo camera. Result of optical flow is made be robust to noise by the kalman filter estimation algorithm. Image data is saved as history from reconstructed three dimension image through motion tracking of object. When whole or some part of object is disappeared form stereo camera by other objects, it is restored to bring image date form history of saved past image and track motion of object.

• The Journal of Korean Physical Therapy
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• v.33 no.2
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• pp.106-113
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• 2021

Purpose: This study examined the effectiveness of action observation training (AOT) and mirror therapy in improving the electroencephalograms (EEG) of stroke patients. Methods: Patients were allocated randomly to three groups: an action observation training with activity (AOTA) group (n=12), a mirror therapy with activity (MTA) group (n=11), and an AOT-only group (n=12). All groups received conventional physiotherapy in five 60-minute sessions over six weeks. The AOTA, MTA, and AOT groups practiced AOTA, MTA, and AOT, respectively, in three 30-minute sessions over six weeks. The differences between the pre- and post-treatment EEGs were assessed using a paired t-test. Comparisons between the groups were performed using one-way ANOVA. Results: The participants in the AOTA and MTA groups showed significant improvement in the EEG. AOTA improved the alpha waves of the prefrontal, temporal, and parietal lobes significantly (p<0.05). MTA improved the alpha waves of the temporal lobe significantly (p<0.05). AOT did not result in significant improvement Conclusion: AOTA and MTA improve stroke patients' EEGs. Mirror neuron activation combined with conventional stroke physiotherapy promotes motor recovery and functioning. The effect is enhanced when the actions are executed after observation. Further research into mirror neuron activation will be needed to develop methods to improve the EEGs of stroke patients.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.62-68
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• 2012

Steady-State Visually Evoked Potentials (SSVEP) are natural response signal associated with the visual stimuli with specific frequency. By using SSVEP, occipital lobe region is electrically activated as frequency form equivalent to stimuli frequency with bandwidth from 3.5Hz to 75Hz. In this paper, we propose an experimental paradigm for analyzing EEGs based on the properties of SSVEP. At first, an experiment is performed to extract frequency feature of EEGs that is measured from the image-based visual stimuli associated with specific objective with affordance and object-related affordance is measured by using mirror neuron system based on the frequency feature. And then, linear discriminant analysis (LDA) method is applied to perform the online classification of the objective pattern associated with the EEG-based affordance data. By using the SSVEP measurement experiment, we propose a Brain-Computer Interface (BCI) system for recognizing user's inherent intentions. The existing SSVEP application system, such as speller, is able to classify the EEG pattern based on grid image patterns and their variations. However, our proposed SSVEP-based BCI system performs object pattern classification based on the matters with a variety of shapes in input images and has higher generality than existing system.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.135-140
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• 2012

The mirror neuron system in the cerebrum, which are handled by visual information-based imitative learning. When we observe the observer's range of mirror neuron system, we can assume intention of performance through progress of neural activation as specific range, in include of partially hidden range. It is goal of our paper that imitative learning is applied to 3D vision-based intelligent system. We have experiment as stereo camera-based restoration about acquired 3D image our previous research Using Optical flow, unscented Kalman filter. At this point, 3D input image is sequential continuous image as including of partially hidden range. We used Hidden Markov Model to perform the intention recognition about performance as result of restoration-based hidden range. The dynamic inference function about sequential input data have compatible properties such as hand gesture recognition include of hidden range. In this paper, for proposed intention recognition, we already had a simulation about object outline and feature extraction in the previous research, we generated temporal continuous feature vector about feature extraction and when we apply to Hidden Markov Model, make a result of simulation about hand gesture classification according to intention pattern. We got the result of hand gesture classification as value of posterior probability, and proved the accuracy outstandingness through the result.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.24 no.3
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• pp.109-123
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• 2013

The discovery of the mirror neuron system (MNS) is one of the most important neuroscientific achievements in the 20th century. Some researchers had reported that MNS dysfunction was discovered in autism spectrum disorders (ASD). Finally, the 'broken mirror' theory of ASD was announced in the mid 2000's. According to this theory, ASD cannot simulate the mind and behavior of others due to MNS dysfunction; therefore, they cannot imitate the behaviors and empathized with the mind of others. However, ASD does not always show imitation problems. The researchers who have criticized the 'broken mirror' theory proposed the 'social top-down response modulation (STORM)' theory. On STORM theory, the medial prefrontal cortex or temporo-parietal junction, brain areas related with mentalising, might modulate MNS according to social context. We compared the strengths and weaknesses of each theory.

• Journal of the Korean Society of Physical Medicine
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• v.5 no.3
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• pp.395-404
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• 2010

Purpose : The object of this study was to examine the effect of motor learning on brain activation depending on the method of motor learning. Methods : The brain activation was measured in 9 men by fMRI. The subjects were divided into the following groups depending on the method of motor learning: actually practice (AP, n=3) group, action observation (AO, n=3) group and motor imagery (MI, n=3) group. In order to examine the effect of motor learning depending on the method of motor learning, the brain activation data were measured during learning. For the investigation of brain activation, fMRI was conducted. Results : The results of brain activation measured before and during learning were as follows; (1) During learning, the AP group showed the activation in the following areas: primary motor area located in precentral gyrus, somatosensory area located in postcentral gyrus, supplemental motor area and prefrontal association area located in precentral gyrus, middle frontal gyrus and superior frontal gyrus, speech area located in superior temporal gyrus and middle temporal gyrus, Broca's area located in inferior parietal lobe and somatosensory association area of precuneus; (2) During learning, the AD groups showed the activation in the following areas: primary motor area located in precentral gyrus, prefrontal association area located in middle frontal gyrus and superior frontal gyrus, speech area and supplemental motor area located in superior temporal gyrus and middle temporal gyrus, Broca's area located in inferior parietal lobe, somatosensory area and primary motor area located in precentral gyrus of right cerebrum and left cerebrum, and somatosensory association area located in precuneus; and (3) During learning, the MI group showed activation in the following areas: speech area located in superior temporal gyrus, supplemental area, and somatosensory association area located in precuneus. Conclusion : Given the results above, in this study, the action observation was suggested as an alternative to motor learning through actual practice in serial reaction time task of motor learning. It showed the similar results to the actual practice in brain activation which were obtained using activation of mirror neuron. This result suggests that the brain activation occurred by the activation of mirror neuron, which was observed during action observation. The mirror neurons are located in primary motor area, somatosensory area, premotor area, supplemental motor area and somatosensory association area. In sum, when we plan a training program through physiotherapy to increase the effect during reeducation of movement, the action observation as well as best resting is necessary in increasing the effect of motor learning with the patients who cannot be engaged in actual practice.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.583-588
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• 2024

With the emergence of Brain-Computer Interface (BCI) technology, analyzing mirror neurons has become more feasible. However, evaluating the accuracy of BCI systems that rely on human thoughts poses challenges due to their qualitative nature. To harness the potential of BCI, we propose a new approach to measure accuracy based on the characteristics of mirror neurons in the human brain that are influenced by speech speed, depending on the ultimate goal of movement. In Chapter 2 of this paper, we introduce mirror neurons and provide an explanation of human posture estimation for mirror neurons. In Chapter 3, we present a powerful pose estimation method suitable for real-time dynamic environments using the technique of human posture estimation. Furthermore, we propose a method to analyze the accuracy of BCI using this robotic environment.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.357-358
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• 2023

본 연구는 실제 행동과 운동 심상으로 팔과 다리 동작 인식을 위한 BCI 패러다임을 제안하고 유도성 분석을 한다. 이 페러다임은 각 팔과 양다리의 특정 움직임을 인식하기 위해 ERP를 기반 페러다임을 구성한다. BCI 페러다임은 왼팔, 오른팔, 양다리를 움직이는 영상 자극을 주며 이를 기반으로 왼팔, 오른팔, 양다리 움직임에 대한 인식을 한다. 거울뉴런은 실제 행동과 실제 행동을 보았을때와 운동심상을 통한 자극을 받았을 때 같은 뉴런이 활성화된다는 성질을 가지고 있다. 이러한 성질을 이용하여 운동심상만과 실제 행동을 동시에 학습할 경우를 유도성 분석을 진행한다. 또한 유도성 특징 분석을 통해 나타난 결과를 바탕으로 BCI 패러다임을 제안한다.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.6
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• pp.658-663
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• 2015

In the previous work, we have proposed an integrate-and-fire neuron circuit and synaptic device based on the floating body MOSFET [1-3]. Integrate-and-Fire(I&F) neuron circuit emulates the biological neuron characteristics such as integration, threshold triggering, output generation, refractory period using floating body MOSFET. The synaptic device has short-term and long-term memory in a single silicon device. In this paper, we connect the neuron circuit and the synaptic device using current mirror circuit for summation of post synaptic pulses. We emulate spike-timing-dependent-plasticity (STDP) characteristics of the synapse using feedback voltage without controller or clock. Using memory device in the logic circuit, we can emulate biological synapse and neuron with a small number of devices.