• Journal of Korean Neurosurgical Society
• /
• v.44 no.1
• /
• pp.36-39
• /
• 2008

Although tuberculosis of the central nervous system is well known, the incidence of intramedullary tuberculomas is low and a combination of intramedullary with intracranial tuberculomas is extremely rare. We report a case of disseminated tuberculoma involving brain and spine with miliary pulmonary tuberculosis in a 66-year-old woman initially presenting with fever, general weakness, back pain and motor weakness of both lower extremities. Despite medical therapy, she developed progressive motor weakness of both lower extremities with muscle strength 1/5 in both lower extremities. Urgent surgical intervention was followed and her muscle power and motor functions were improved gradually. The anti-tuberculous drugs were continued and the follow-up magnetic resonance imaging (MRI) of brain and spine showed that the lesions had become smaller or disappeared.

• The Journal of Pediatrics of Korean Medicine
• /
• v.23 no.3
• /
• pp.89-108
• /
• 2009

Objectives The purpose of this study is to report the clinical effects of oriental medical treatment on developmental disorder induced by traumatic brain injuries. Methods The patients were treated with herb medicine, acupunctures, moxibustions, and negative pressures, and then evaluated by manual muscle tests, gross motor function measurements, sequenced language scales for infants. Results The patient's manual muscle power, motility, cognition, speech were significantly improved after six weeks of oriental medical treatment. Conclusions This study showed that oriental medical treatments were effective on developmental disorder induced by traumatic brain injuries. However, further clinical studies were needed.

• Journal of IKEEE
• /
• v.14 no.2
• /
• pp.16-23
• /
• 2010

Since the interest of a brain science research is increased recently, various devices using brain waves have been developed in the field of brain training game, education application and brain computer interface. In this paper, we have developed a portable EEG measurement and a bluetooth based wireless transmission device measuring brain waves from the frontal lob simply and conveniently. The low brain signals about 10~100${\mu}V$ was amplified into several volts and low pass, high pass and notch filter were designed for eliminating unwanted noise and 60Hz power noise. Also, PIC24F192 microcontroller has been used to convert analog brain signal into digital signal and transmit the signal into personal computer wirelessly. The sampling rate of 1KHz and bluetooth based wireless transmission with 38,400bps were used. The LabVIEW programing was used to receive and monitor the brain signals. The power spectrum of commercial biopac MP100 and that of a developed EEG system was compared for performance verification after the simulation signals of sine waves of $1{\mu}V$, 0~200Hz was inputed and processed by FFT transformation. As a result of comparison, the developed system showed good performance because frequency response of a developed system was similar to that of a commercial biopac MP100 inside the range of 30Hz specially.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2009.02a
• /
• pp.169.1-169.1
• /
• 2009

• Proceedings of the Safety Management and Science Conference
• /
• 2011.11a
• /
• pp.583-591
• /
• 2011

A number of Brain-Computer Interface (BCI) studies have been performed to assess the cognitive status through EEG signal. However, there are a few studies trying to prevent user from unexpected safety-accident in BCI study. The EEGs were collected from 19 subjects who participated in two experiments (rest & event-related potential measurement). There was significant difference in EEG changes of both spontaneous and event-related potential. Beta power and P300 latency may be useful as a biomarker for prevention of response to safety-accident.

• Journal of the Korea Safety Management & Science
• /
• v.14 no.1
• /
• pp.1-6
• /
• 2012

A number of Brain-Computer Interface (BCI) studies have been performed to assess the cognitive status through EEG signal. However, there are a few studies trying to prevent user from unexpected safety-accident in BCI study. The EEGs were collected from 19 subjects who participated in two experiments (rest & event-related potential measurement). There was significant difference in EEG changes of both spontaneous and event-related potential. Beta power and P300 latency may be useful as a biomarker for prevention of response to safety-accident.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.170-174
• /
• 2007

Although research efforts for brain waves have prospered in medicine and engineering, acupuncture still has a long way to go regarding researches on brain waves analysis. Thus this study set out to analyze brain waves stimulated by indirect mugwort moxibustion, which was part of acupuncture techniques, and to investigate their correlations with the automatic nervous system. For the experiments, stimulation was given to Jungwan, Shingwol and Gwanwon, which were some of the spots on the body suitable for acupuncture, through indirect mugwort moxibustion. The subjects' brain waves were measured before the stimulation, during the stimulation, and one hour and two hours after the stimulation. The measurements were analyzed with Matlab 7.0 for FFT and frequency power spectrum. Then the ${\alpha}$, ${\beta}$, ${\delta}$, and ${\theta}$ waves were analyzed and examined for changes to the percentage of each frequency and to the amplitude of vibration according to the stages of stimulation. The EEG data of the entire brain were translated into FFT to analyze the percentage of the ${\alpha}$, ${\beta}$, ${\delta}$, and ${\theta}$ waves. As a result, the ${\alpha}$ waves recorded a double increase after the stimulation. The power spectrum analysis results of the entire brain decreased the ${\alpha}$ and ${\beta}$ waves dropping in the energy level, which suggested that the parasympathetic nerves were activated. When the results of the study were compared with those of the previous study, it's confirmed that indirect moxibustion stimulation could cause changes to the automatic nervous system and bring stability to those who were nervous or under stress due to the proportionate increase of the ${\alpha}$ waves.

• Science of Emotion and Sensibility
• /
• v.19 no.4
• /
• pp.119-126
• /
• 2016

In this study, we investigated the effects of mouth breathing on brain activity through electroencephalogram (EEG). EEG was performed on 12 healthy volunteers of age ranging from 21 to 27 years (male: female = 6:6, non-smoker). Brain waves on resting state (Rest_N/Rest_M) and auditory-language stimuli state (Eng_N/Eng_M) were recorded during mouth and nose breathing. Four different regions (R1~R4) were classified based on the brain functionality. And each channel (e.g., Pf1 and Pf2) and frequency (${\alpha}$, ${\beta}$, ${\gamma}$, and ${\theta}$) were analyzed using their absolute power ratios of fast Fourier transform (FFT). The results showed that there was no significant difference between Rest_N and Rest_M. Eng_N had significantly higher brain activity than Rest_N; on the other hand, there was no significant difference between Rest_M and Eng_M. These results demonstrate that mouth-breathing on resting state does not induce any significant effects on brain activity and/or functionality, even though it causes subtle temporary inconvenience. In addition to the uncomfort, the brain activity can be adversely influenced by mouth-breathing, which could lower the cognitive skills under certain circumstances.

• Journal of Korean Academy of Nursing
• /
• v.36 no.4
• /
• pp.621-629
• /
• 2006

Purpose. The purpose of this study was to identify the clinical variables that predict functional and cognitive recovery at 1- and 6-month in both severe and moderate/mild traumatic brain injury patients. Methods. The subjects of this study were 82 traumatically brain-injured patients who were admitted to a Neurological Intensive Care Unit at a university hospital. Potential prognostic factors included were age, motor and pupillary response, systolic blood pressure, heart rate, and the presence of intracranial hematoma at admission. Results. The significant predictors of functional disability in severe traumatic brain injury subjects were, age, systolic blood pressure, the presence of intracranial hematoma, motor response, and heart rate at admission. In moderate/mild traumatic brain injury patients, motor response, abnormal pupil reflex, and heart rate at admission were identified as significant predictors of functional disability. On the other hand, the significant predictors of cognitive ability for severe traumatic brain injury patients were motor response and the presence of intracranial hematoma at admission, whereas those for moderate/mild patients were motor response, pupil reflex, systolic blood pressure at admission, and age. Conclusions. The results of the present study indicate that the significant predictors of TBI differ according to TBI severity on admission, outcome type, and outcome measurement time. This can be meaningful to critical care nurses for a better understanding on the prediction of brain injury patients. On the other hand, the model used in the present study appeared to produce relatively low explicabilities for functional and cognitive recovery although a direct comparison of our results with those of others is difficult due to differences in outcome definition and validation methods. This implies that other clinical variables should be added to the model used in the present study to increase its predicting power for determining functional and cognitive outcomes.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.3
• /
• pp.254-259
• /
• 2015

In this paper, The wireless robot control system was proposed using Brain-computer interface(BCI) systems based on the steady-state visual evoked potential(SSVEP). Cross Power Spectral Density(CPSD) was used for analysis of electroencephalogram(EEG) and extraction of feature data. And Linear Discriminant Analysis(LDA) and Support Vector Machine(SVM) was used for patterns classification. We obtained the average classification rates of about 70% of each subject. Robot control was implemented using the results of classification of EEG and commanded using bluetooth communication for robot moving.