• Journal of radiological science and technology
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• v.42 no.2
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• pp.113-117
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• 2019

The purpose of this study was to investigate the FA value which can produce the best T2-weighted images by measuring the signal intensity and noise according to the FA value change in the brain image and the abdominal image of the mouse using micro-MRI. Brain imaging and abdominal imaging of BALB / C mice weighing 20g were performed using 4.7T (Bruker BioSpin MRI GmbH) micro-MRI equipment, Turbo RARE-T2 (spin echo-T2) images were scanned at TR 3500 msec and TE 36 msec. The changes of the FA values were $60^{\circ}$, $80^{\circ}$, $100^{\circ}$, $120^{\circ}$, $140^{\circ}$, $160^{\circ}$ and $180^{\circ}$. We measured signal intensity according to FA values of ventricle and thalamus in brain imaging, The signal intensity of kidney and muscle around the kidney was measured in abdominal images. To obtain SNR and CNR, we measured the background signals of two different parts, not the tissue. In the brain (thalamus) image, the signal intensity of FA $100^{\circ}$ was 7,433 and SNR (6.49) was the highest. In the abdominal (kidney) image, the signal intensity was highest at 16,523 when FA was $120^{\circ}$, and the highest SNR was 8.54 when FA was $140^{\circ}$. The CNR value of the brain image was 1.38 at FA $60^{\circ}$ and gradually increased to 8.29 at FA $180^{\circ}$. The CNR value of the muscle adjacent to the kidney gradually increased from 2.36 when the FA value was $60^{\circ}$ and the highest value was 4,57 at the FA value $180^{\circ}$.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.1 no.1
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• pp.13-19
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• 2007

In this study, diagnostic algorithm was suggested to diagnose quantitatively the degree of the stress urinary incontinence. The bio-signal measurement system was developed to measure the contraction pressure of the pelvic floor muscle and diagnostic parameters were drawn out by analyzing the contraction pressure data. Statistical evaluations were done to classify the diagnositc parameters by order that relationship is high. The diagnostic algorithm that was able to diagnose degree of the urinary incontinence as quantitatively was realized from the high relationship parameters.

• Journal of Digestive Cancer Reports
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• v.5 no.2
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• pp.97-104
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• 2017

Background: Cachexia is a multi-factorial syndrome presenting with chronic illness, decreases in body weight, and loss of adipose tissue and skeletal muscle, mostly in patients with advanced cancer and chronic wasting disease. Even after years of intensive researches, there remains no convincing therapy to prevent cancer cachexia. Methods: In this in vivo study, we have established C26 adenocarcinoma-induced cancer cachexia model in mice to explore the underlying core changes in cytokine, signal transduction, and muscle wasting. The ultimate aim of establishing animal model is to find optimal therapeutics to mitigate cancer cachexia. Results: We have administered C26 adenocarcinoma cells onto BALB/c mice and observed 4 weeks to assess the progression of cancer cachexia. Significant loss of weight accompanied with loss of appetite was noted. As C26 adenocarcinoma xenograft progressed, mortality was started from 3 weeks, accompanied with significant sarcopenia and decreased mice movement. Surges in TNF-α and IL-6 were noted with the commencement of cancer cachexia. Conclusion: Using C26 adenocarcinoma cancer cachexia model, we can screen the optimal therapeutics to mitigate cancer cachexia, in which agents to modulate IL-6, TNF-α, and NF-κB were essential.

• Journal of Digestive Cancer Research
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• v.5 no.2
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• pp.97-104
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• 2017

Background: Cachexia is a multi-factorial syndrome presenting with chronic illness, decreases in body weight, and loss of adipose tissue and skeletal muscle, mostly in patients with advanced cancer and chronic wasting disease. Even after years of intensive researches, there remains no convincing therapy to prevent cancer cachexia. Methods: In this in vivo study, we have established C26 adenocarcinoma-induced cancer cachexia model in mice to explore the underlying core changes in cytokine, signal transduction, and muscle wasting. The ultimate aim of establishing animal model is to find optimal therapeutics to mitigate cancer cachexia. Results: We have administered C26 adenocarcinoma cells onto BALB/c mice and observed 4 weeks to assess the progression of cancer cachexia. Significant loss of weight accompanied with loss of appetite was noted. As C26 adenocarcinoma xenograft progressed, mortality was started from 3 weeks, accompanied with significant sarcopenia and decreased mice movement. Surges in TNF-α and IL-6 were noted with the commencement of cancer cachexia. Conclusion: Using C26 adenocarcinoma cancer cachexia model, we can screen the optimal therapeutics to mitigate cancer cachexia, in which agents to modulate IL-6, TNF-α, and NF-κB were essential.

• ETRI Journal
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• v.39 no.1
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• pp.87-96
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• 2017

Ultrasonic surgical devices are routinely used for surgical procedures. The incision and coagulation of tissue generate a temperature of $40^{\circ}C-150^{\circ}C$ and depend on the controllable output power level of the surgical device. Recently, research on the classification of grasped tissues to automatically control the power level was published. However, this research did not consider the specific characteristics of the surgical device, tissue denaturalization, and so on. Therefore, this research proposes a robust algorithm that simulates noise to resemble real situations and classifies tissue using conventional classifier algorithms. In this research, the bioimpedance spectrum for six tissues (liver, large intestine, kidney, lung, muscle, and fat) is measured, and five classifier algorithms are used. A signal-to-noise ratio of additive white Gaussian noise diversifies the testing sets, and as a result, each classifier's performance exhibits a difference. The k-nearest neighbors algorithm shows the highest classification rate of 92.09% (p < 0.01) and a standard deviation of 1.92%, which confirms high reproducibility.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.161-164
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• 2008

A realization for EMG signal sensing and vertical control system of robotizing arm is presented in this paper. The system is realized that a fine EMG bio-signals of humans' arm muscle are detected by surface electrode sensor, making a high performance amplifier and filtering, converting analog into digital signal and driving a servomotor for robotizing arm. The system is experimented by monitoring multiple step vertical control angles of robotizing arm corresponding to EMG signals in moving arm muscles. The experimental result are that the vertical control level is measured to around 2 degrees and mean error is 5% approximately.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.6
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• pp.1170-1176
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• 2007

The conventional urodynamic monitoring is fulfilled by artificially filling a bladder with saline. Generally. it is difficult to evaluate the physiological functions of the storage and voiding of a bladder. With this aim, we constructed an ambulatory urodynamic monitoring (AUM) system and proposed a novel method estimating abdominal pressure by measuring bio-impedance variations. Our system was clinically evaluated for 10 patients. It turned out to be that as the intensity of the abdomen contraction increased, the amplitude of bio-impedance signal and the RMS value of EMG increased more as compared to those who observed during the rest mode. Also, we determined the optimum electrode pair for estimating the abdominal pressure using bio-impedance method and consequently compared with the conventional methods. Because impedance changes differ from a weight, a height, contractile force, volume of muscle and blood other or whatever of individuals, it was quantified in terms of impedance change, correlation coefficient and SNR Our results showed the optimum electrode pair (1,9) which could detect impedance changes due to the increase of the intensity in the abdominal pressure. The correlation coefficient and quadratic function between the RMS values of EMG and the impedance changes were 0.87 and $y=0.0014x^2+0.0620x+0.6958$, respectively. Thus, our system demonstrated that the abdominal pressure could be measured noninvasively and conveniently by simply estimating bio-impedance values. We propose that this optimum electrode configuration would be useful for the future studies involving the handy measurements of abdominal pressure with our suggested ambulatory urodynamics monitoring system.

• Biomolecules & Therapeutics
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• v.24 no.1
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• pp.25-32
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• 2016

Lichens have been known to possess multiple biological activities, including anti-proliferative and anti-inflammatory activities. Vascular cell adhesion molecule-1 (VCAM-1) may play a role in the development of atherosclerosis. Hence, VCAM-1 is a possible therapeutic target in the treatment of the inflammatory disease. However, the effect of lobaric acid on VCAM-1 has not yet been investigated and characterized. For this study, we examined the effect of lobaric acid on the inhibition of VCAM-1 in tumor necrosis factor-alpha (TNF-${\alpha}$)-stimulated mouse vascular smooth muscle cells. Western blot and ELISA showed that the increased expression of VCAM-1 by TNF-${\alpha}$ was significantly suppressed by the pre-treatment of lobaric acid ($0.1-10{\mu}g/ml$) for 2 h. Lobaric acid abrogated TNF-${\alpha}$-induced NF-${\kappa}B$ activity through preventing the degradation of $I{\kappa}B$ and phosphorylation of extracellular signal-regulated kinases (ERK), c-Jun N-terminal kinases (JNK), and p38 mitogen activated protein (MAP) kinase. Lobaric acid also inhibited the expression of TNF-${\alpha}$ receptor 1 (TNF-R1). Overall, our results suggest that lobaric acid inhibited VCAM-1 expression through the inhibition of p38, ERK, JNK and NF-${\kappa}B$ signaling pathways, and downregulation of TNF-R1 expression. Therefore, it is implicated that lobaric acid may suppress inflammation by altering the physiology of the atherosclerotic lesion.

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.211-220
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• 2019

Surface electromyogram (sEMG), which is a bio-electrical signal originated from action potentials of nerves and muscle fibers activated by motor neurons, has been widely used for recognizing motion intention of robotic prosthesis for amputees because it enables a device to be operated intuitively by users without any artificial and additional work. In this paper, we propose a training-free unsupervised sEMG pattern recognition algorithm. It is useful for the gesture recognition for the amputees from whom we cannot achieve motion labels for the previous supervised pattern recognition algorithms. Using the proposed algorithm, we can classify the sEMG signals for gesture recognition and the calculated threshold probability value can be used as a sensitivity parameter for pattern registration. The proposed algorithm was verified by a case study of a patient with partial-hand amputation.

• Journal of Sensor Science and Technology
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• v.20 no.2
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• pp.137-144
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• 2011

Wireless sensor network(WSN) has the potential to greatly effect many aspects of u-healthcare. By outfitting the potential with WSN, wearable sensor node can collects real-time data on physiological status and transmits through base station to server PC. However, there is a significant gap between WSN and healthcare. WSN has the limited resource about computing capability and data transmission according to bio-sensor sampling rates and channels to apply healthcare system. If a wearable node transmits ECG and accelerometer data of 4 channel sampled at 100 Hz, these data may occur high loss packets for transmitting human activity and ECG to server PC. Therefore current wearable sensor nodes have to solve above mentioned problems to be suited for u-healthcare system. Most WSN based activity and ECG monitoring system have been implemented some algorithms which are applied for signal vector magnitude(SVM) algorithm and ECG noise algorithm in server PC. In this paper, A wearable sensor node using integrated ECG and 3-axial accelerometer based on wireless sensor network is designed and developed. It can form multi-hop network with relay nodes to extend network range in WSN. Our wearable nodes can transmit 1-channel activity data processed activity classification data vector using SVM algorithm to 3-channel accelerometer data. ECG signals are contaminated with high frequency noise such as power line interference and muscle artifact. Our wearable sensor nodes can remove high frequency noise to clear original ECG signal for healthcare monitoring.