• Molecules and Cells
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• v.25 no.1
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• pp.1-6
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• 2008

Osteoarthritis (OA), one of the most common skeletal disorders characterized by cartilage degradation and osteophyte formation in joints, is induced by accumulated mechanical stress; however, little is known about the underlying molecular mechanism. Several experimental OA models in mice by producing instability in the knee joints have been developed to apply approaches from mouse genetics. Although proteinases like matrix metalloproteinases and aggrecanases have now been proven to be the principal initiators of OA progression, clinical trials of proteinase inhibitors have not been successful for the treatment, turning the interest of researchers to the upstream signals of proteinase induction. These signals include undegraded and fragmented matrix proteins like type II collagen or fibronection that affects chondrocytes through distinct receptors. Another signal is proinflammatory factors that are produced by chondrocytes and synovial cells; however, recent studies that used mouse OA models in knockout mice did not support that these factors have a role in the central contribution to OA development. Our mouse genetic approaches found that the induction of a transcriptional activator Runx2 in chondrocytes under mechanical stress contributes to the pathogenesis of OA through chondrocyte hypertrophy. In addition, chondrocyte apoptosis has recently been identified as being involved in OA progression. We hereby propose that these endochondral ossification signals may be important for the OA progression, suggesting that the related molecules can clinically be therapeutic targets of this disease.

• Journal of Computing Science and Engineering
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• v.7 no.2
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• pp.112-121
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• 2013

The last years have seen a rise of interest in using electroencephalography-based brain computer interfacing methodology for investigating non-medical questions, beyond the purpose of communication and control. One of these novel applications is to examine how signal quality is being processed neurally, which is of particular interest for industry, besides providing neuroscientific insights. As for most behavioral experiments in the neurosciences, the assessment of a given stimulus by a subject is required. Based on an EEG study on speech quality of phonemes, we will first discuss the information contained in the neural correlate of this judgement. Typically, this is done by analyzing the data along behavioral responses/labels. However, participants in such complex experiments often guess at the threshold of perception. This leads to labels that are only partly correct, and oftentimes random, which is a problematic scenario for using supervised learning. Therefore, we propose a novel supervised-unsupervised learning scheme, which aims to differentiate true labels from random ones in a data-driven way. We show that this approach provides a more crisp view of the brain states that experimenters are looking for, besides discovering additional brain states to which the classical analysis is blind.

• Advances in robotics research
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• v.1 no.2
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• pp.155-169
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• 2014

Study results in the last decades show that amount and quality of physical exercises, then the active participation, and now the cognitive involvement of patient in rehabilitation training are known of crux to enhance recovery outcome of motor dysfunction patients after stroke. Rehabilitation robots mainly have been developing along this direction to satisfy requirements of recovery therapy, or focusing on one or more of the above three points. Therefore, neuro-machine interaction based active rehabilitation robot has been proposed for assisting paralyzed limb performing designed tasks, which utilizes motor related EEG, UCSDI (Ultrasound Current Source Density Imaging), EMG for rehabilitation robot control and feeds back the multi-sensory interaction information such as visual, auditory, force, haptic sensation to the patient simultaneously. This neuro-controlled and perceptual rehabilitation robot will bring great benefits to post-stroke patients. In order to develop such kind of robot, some key technologies such as noninvasive precise detection of neural signal and realistic sensation feedback need to be solved. There are still some grand challenges in solving the fundamental questions to develop and optimize such kind of neuro-machine interaction based active rehabilitation robot.

• Journal of Korean Neurosurgical Society
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• v.29 no.9
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• pp.1184-1187
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• 2000

Spontaneous spinal epidural hematoma is rare disease and usually presents with a progressive neurological syndrome for which surgical decompression is usually indicated. The cause of bleeding in epidural hematoma remains unknown in most of the cases. The most frequently identified risk factor is coagulopathy or treatment with anticoagulants. Recently, authors experienced a case of spontaneous spinal epidural hematoma with intraoperative profuse bleeding at the cervicothoracic location. Laboratory examination showed no evidence of coagulopathy or hepatic disease. On neurologic examination, left hemiparesis(Grade : II) and left side sensory change were noted. On MRI scan, there was a mass of high signal intensity in T2WI and isosignal intensity in T1WI compressing the cord to left side. The patients had good surgical outcome after decompressive laminectomy and hematoma removal.

• Journal of Korean Neurosurgical Society
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• v.49 no.3
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• pp.178-181
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• 2011

Congenital anomalies in arches of the atlas are rare, and are usually discovered incidentally. However, a very rare subgroup of patients with unique radiographic features is predisposed to transient quadriparesis after minor cervical or head trauma, A 46-year-old male presented with a 2-month history of tremor and hyperesthesia of the lower extremities after experiencing a minor head trauma. He said that he had been quadriplegic for about 2 weeks after that trauma. Radiographs of his cervical spine revealed bilateral bony defects of the lateral aspects of the posterior arch of C1 and a midline cleft within the anterior arch of the atlas. A magnetic resonance imaging revealed an increased cord signal at the C2 level on the T2-weighted sagittal image. A posterior, suboccipital midline approach for excision of the remnant posterior tubercle was performed. The patient showed significant improvement of his motor and sensory functions. Since major neurologic deficits can be produced by a minor trauma, it is crucial to recognize this anomaly.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.865-871
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• 2012

In this study, ambulatory electrocardiogram(ECG) signal and the rhythms of heart beats are visualized in terms of R-R intervals and Heart Rate Variability(HRV) in the environment of an android plaform. With this aim, Graphical User Interface(GUI) is implemented by executing multi-thread Java programming modules including ECG, heart-beats, tachogram and visualization unit. ECG signals are acquired in an android device by receiving the data from ambulatory ECG sensory system. Finite Impulse Response(FIR) filters are implemented to eliminate the baseline wandering noises contained in the ambulatory signals and DC-offset level in R-R interval data. With simulating the normal or stress emotional state of a subject, we can find the fact that HRV can be successfully estimated and visualized in an android smart phone platform.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.8
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• pp.965-970
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• 2011

We develop a diagnostic system to monitor failures in an engine-assembly line. Existing techniques such as sensory analysis, time domain analysis, frequency analysis, and statistical analysis have limitations in the diagnosis of engine-assembly failure when there are abnormal vibration waveforms (crashing and damping signals) during the assembly. We use a wavelet technique to deal with crashing and damping signals. We also implement a new technique for developing diagnostic rules from sensor data, and we demonstrate its validity.

• Journal of KIISE
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• v.44 no.7
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• pp.726-732
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• 2017

In practical distributed sensing and prediction applications over wireless sensor networks (WSN), environmental sensing activities are highly dynamic because of noisy sensory information from moving source signals. The recent distributed online convex optimization frameworks have been developed as promising approaches for solving approximately stochastic learning problems over network of sensors in a distributed manner. Negligence of mobility consequence in the original distributed saddle point algorithm (DSPA) could strongly affect the convergence rate and stability of learning results. In this paper, we propose an integrated sliding windows mechanism in order to stabilize predictions and achieve better convergence rates in cooperative detection of a moving source signal scenario.

• The Korean Journal of Pain
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• v.22 no.1
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• pp.92-95
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• 2009

Transverse myelitis is a focal inflammatory disorder of the spinal cord characterized by motor, sensory, and autonomic dysfunction. A 41-year-old man with transverse myelitis and no pre-existing neurologic disease presented with hypesthesia, numbness, weakness in the both lower extremities, back pain, decreased libido, constipation, and dysuria. A MRI test showed intramedullary high signal intensity between T4 and T8 on a T2-weighted image. After high-dose intravenous methylprednisolone and oral prednisolone therapy, he showed facial swelling and acneiform eruption. Therefore, we injected 40 mg methylprednisolone via an epidural route. A 7-dose serial treatment improved most symptoms. A follow up MRI showed radiological improvement. We report a case of transverse myelitis treated by epidural steroids.

• Journal of Sensor Science and Technology
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• v.24 no.1
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• pp.29-34
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• 2015

This study aimed to evaluate the characterization of a metal oxide semiconductor and electrochemical gas sensor array for measuring wastewater odor. The sensitivity of all gas sensors observed in sampling method by stripping was 6.7 to 20.6 times higher than that by no stripping, except sensor D (electrochemical gas sensor). The average reduction ratio of sensor signal as a function of initial dilution rate of wastewater was in the order of food plant > food waste reutilization facility > plating plant. The sensitivity of gas sensors was dependent on both the type of wastewater and the dilution rate. The sensor signals observed by the gas sensor array were correlated with the dilution factor (OU) calculated by the air dilution sensory test with several wastewater ($r^2=0.920{\sim}0.997$), except the sensor signals of sensor D measured in the plating plant wastewater. It seems likely that the gas sensor array plays a role in the evaluation of odor in wastewater and is useful tool for on-site odor monitoring in the wastewater facilities.