• Journal of Sensor Science and Technology
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• v.12 no.3
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• pp.121-127
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• 2003

In this study, we carried out a study for implementation of the pre-amplifier and the digital signal processing part for the potable EEG biofeedback system. As we consider characteristics of the EEG signal, we designed the pre-amplifier to obtain the EEG signal to be reduced noise signal. Because the EEG signal include EOG, EMG, ECG signals etc, it is difficult to analyze of the EEG signal. Therefore, we developed DSP board and operation program which was embed the LMS adaptive filter algorithm and operate with the pre-amplifier in the real time. The simulation signal and pure EEG signal is used in the experiment. As the result, we confirmed good efficiency of developed system and possibility of application to the portable EEG biofeedback system.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1650-1656
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• 2004

In this paper, a multi-adaptive filter is proposed for removing EOG and the 60 Hz power supply noise from EEG measured in the frontal lobe and the feedback output control method is implemented for biofeedback. The multi-adaptive filter has been implemented on the TMS320C6711 DSP system and the feedback output control algorithm has been realized by calculating the ratio of alpha wave on the TMS320C31 DSP system with real time performance. Through the experiment using the implemented multi-adaptive filter and feedback output controller, we demonstrate that the proposed adaptive filter effectively removes EOG and the 60 Hz power supply noise from the measured EEG in the frontal lobe and the feedback algorithm controls the level of stimulation by the ratio of the alpha wave.

• Journal of Biomedical Engineering Research
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• v.25 no.3
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• pp.227-233
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• 2004

In this paper, it is proposed that the four channel electrode arrangement at a frontal lobe and the noise reduction method using a JADE for the EEG biofeedback system. The proposed electrode arrangement is based on the retina-cornea dipole model. Using JADE and signals which are acquired by the proposed arrangement, four independent components are separated. To estimate a pure EEG component among four components, it is measured that a ratio of alpha wave to the whole signal and then the component that has a maximum value is considered as a pure EEG which the noise is eliminated. As a result of experiments, the proposed methods are effective in reduction of noises during acquisition of the EEG.

• Journal of Biomedical Engineering Research
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• v.23 no.2
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• pp.155-163
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• 2002

Attention Deficit Hyperactivity Disorder(ADHD) is a childhood syndrome characterized by short attention span. impulsiveness, and hyperactivity, which often leadㄴ to learning disabilities and various behavioral problems. For the treatment of ADHD, medication and cognitive-behavior therapy is applied in recent yearn Although psycho-stimulant medication has been widely used for many rears. current findings suggest that, as the sole treatment for ADHD, it is an inadequate form of intervention in that parents don't want their child to use drug and the effects are limited to the period in which the drugs are physiologically active. On the other hand, EEG biofeedback treatment studies for ADHD have reported promising results not only in significant reductions in hyperactive, inattentive, and disruptive behaviors, but also improvements in academic performance and IQ scores. However it is too boring for children to finish the whole treatment. The recent increase in computer usage in medicine and rehabilitation has changed the way health care is delivered. Virtual Reality technology provides specific stimuli that can be used in removing distractions and providing environments that get the subjects'attention and increasing their ability to concentrate. VR technology can hold a patient's attention for a longer period of time than other methods can, because VR is immersive, interactive and imaginal. Based on these aspects, we developed Attention Enhancement System (AES) using VR technology, EEG biofeedback, and cognitive training method for enhancing attention and made a clinical trial to people who have attention difficulty and behavioral problems.

• The Journal of the Korea Contents Association
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• v.5 no.1
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• pp.19-26
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• 2005

This paper introduces a new design method of realizing the machine control interface by using bio-signals(EEG/EOG). This method can be further expanded to be applied to the computer system responding to EEG or EOG signals and the general bio-feedback system. For this reason, we made the remotely controlled toy system controlled by the EEG spectrums, their combination indexes, and EOG parameters. And the headset that has bio-signal processing modules built-in offers convenience for users, and this make much more advanced system than any other existing BCI and BMI system.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.461-470
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• 2007

Human can learn how to shape their brain electrical activity in a desired direction through continuous feedback of the electroencephalogram (EEG), and this technique is known as Neurofeedback (or EEG biofeedback), which has been used since the late 1960s in clinical applications. In this study, a portable wireless EEG (named wEEG) has been designed and implemented, which consists of a mobile station (a wireless two-channel EEG acquisition device) and a base station (a bridge between mobile station and computer). Moreover, a SensoriMotor Rhythm (SMR) training system was also implemented with the wEEG for enhancing attention with virtual environment. Experiment results based on 16 volunteers' (8 females and 8 males, average age is $27{\pm}4$) were reported in this paper. The results show that the SMR ratio of 87.5% subjects increased about 0.7% in training status than that in the stable status. With the proposed system, many training protocol scan be designed easily and can be done at home in our daily life conveniently. Additionally, the proposed system will be useful for disabled and aged people.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.91-96
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• 2000

본 연구는 이러한 뇌파 바이오피드백 원리를 적용하여 뇌파를 유도하고 유도된 상태에 대한 피드백을 제공함으로써 사용자 스스로 자신의 뇌파 상태를 조절하도록 하는 장치로 개발된 Q0jump 시스템의 효과성을 밝히고자 하였다. 연구 방법에 있어서 뇌파 측정 장비와 Q-jump를 동시에 측정함으로써 Q-jump 시스템의 타당성을 검증하였으며, 또한 뇌파유도 프로그램을 사용하여 그 효과성을 입증하려 했다. 그 결과 Q-jump 시스템과 뇌파 측정장비에서 얻어진 결과가 유의한 상관을 가짐을 보았다. 상대적 출현량에 있어서 뇌파 유도프로그램을 사용했을 때, 전두엽 부분에서 slow alpha 는 유의한 증가를, fast beta는 유의한 감소를 나타냈다. 후속 연구에 있어서는 통제집단을 이용한 보다 면밀한 검증 연구가 필요하다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1715-1717
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• 2015

최근 의학 및 게임 분야에서 뉴로 피드백에 관한 연구들이 활발하다. 뉴로 피드백이란 뇌의 전기적 활동을 뜻하는EEG(Electroencephalogram)을 대상으로 하는 바이오피드백(biofeedback) 시스템의 일종이다. 좌 우뇌의 불균형은 불안과 우울 등의 정서적 장애를 초래한다. 본 논문에서는 좌, 우뇌 활성도를 대칭적으로 향상시켜 뇌기능의 최적화를 위한 시스템을 제안하며 뇌파를 분석하여 정서 상태 파악 후 규칙적 훈련을 통한 우울, 불안 등의 정서적 문제를 개선하는 뉴로 피드백 시스템 개발에 대한 결과를 보고한다. 실험을 통한 시스템의 검증으로 3주간 진행한 훈련 결과를 비교하였으며 그 증가율을 살펴보았다. 1주차와 3주차의 데이터를 비교해본 결과 평균적으로 26.18%의 증가율을 보였고 좌, 우뇌의 활성도의 대칭이 향상된 것을 알 수 있었다.

• Science of Emotion and Sensibility
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• v.5 no.2
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• pp.29-34
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• 2002

Our previous studies investigated that narrow field of view (FOV : 50˚) and slow navigation speed decreased the frequency of occurrence and severity of cybersickness during immersion in the virtual reality (VR). It would cause a significant reduction of cybersickness if it were provided cybersickness alleviating virtual environment (CAVE) using biofeedback method whenever subject underwent physiological agitation. For verifying the hypothesis, we constructed a real-time cybersickness detection and feedback system with artificial neural network whose inputs are electrophysiological parameters of blood pulse volume, skin conductance, eye blink, skin temperature, heart period, and EEG. The system temporary provided narrow FOV and decreased speed of navigation as feedback outputs whenever physiological measures signal the occurrence of cybersickness. We examined the frequency and severity of cybersickness from simulator sickness questionnaires and self-report in 36 subjects. All subjects experienced VR two times in CAVE and non-CAVE condition at one-month intervals. The frequency and severity of cybersickness were significantly reduced in CAVE than non-CAVE condition. Virtual environment of narrow FOV and slow navigation provided by electrophysiological features based artificial neural network caused a significant reduction of cybersickness symptoms. These results showed that efficiency of a cybersickness detection system we developed was relatively high and subjects expressed more comfortable in the virtual navigation environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.609-614
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• 2014

Cerebellar ataxia is a steadily progressive neurodegenerative disease associated with loss of motor control, leaving patients unable to walk, talk, or perform activities of daily living. Direct motor instruction in cerebella ataxia patients has limited effectiveness, presumably because an inappropriate closed-loop cerebellar response to the inevitable observed error confounds motor learning mechanisms. Recent studies have validated the age-old technique of employing motor imagery training (mental rehearsal of a movement) to boost motor performance in athletes, much as a champion downhill skier visualizes the course prior to embarking on a run. Could the use of EEG based BCI provide advanced biofeedback to improve motor imagery and provide a "backdoor" to improving motor performance in ataxia patients? In order to determine the feasibility of using EEG-based BCI control in this population, we compare the ability to modulate mu-band power (8-12 Hz) by performing a cued motor imagery task in an ataxia patient and healthy control.