• The Korean Journal of Pain
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• v.8 no.1
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• pp.127-130
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• 1995

A 34 year old male patient visited to our neuro-pain clinic with symtoms of a left frontal headache, eyeball throbbing and occipital pain. Two days after the first visit to our clinic. pain was aggrevated and the skin eruption appeared on the left forehead. He was diagnosed as raving Herpes Zoster Opthalmicus(HZO). We performed stellate ganglion block(SGB), but pain did not subsid. So a continuous cervical epidural block was perfomed(CCEB) and it could relieve the pain promptly. In this case, VAS(visual analogue scale) was diminished from 10 to 3 and the skin eruption was healed 24 days after the treatment with CCEB and SGB. We experienced that CCEB is more effective rather than intermittent SGB in intractable HZO. CCEB should be considered to the treatment of choice in patients with HZO.

• The Korean Journal of Pain
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• v.8 no.2
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• pp.383-385
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• 1995

Postpuncture headache is the most common complication of epidural block, others include abscission of the tip of catheter, epidural abscess and subarachnoid infection, etc. A 69-year-old female patient visited the Neuro-Pain Clinic of Seran General Hospital for treatment of lower back pain and both sciatica. She received continuous epidural block, psoas compartment block, lumbar facet joint block and lumbar facet thermocoagulation. During the epidural block procedure the dura was accidently punctured and auto-logous blood patch was performed. Three days later, she manifested fever, nausea, vomiting, mild neck stiffness and mental deterioration. Meningitis was suspected as the cause of these signs. The CSF study reported: protein 400 mg/dl, sugar 14 mg/dl, WBC $468/mm^3$. She was recovered from the meningitis after adequate antibiotic therapy.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.49-55
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• 2002

A decrease in the birthrate and aging are progressing in Japan and several countries. In that society, it is important that physically weak persons such as elderly persons are able to take care of themselves. We have been developing exoskeletal robots for human (especially for physically weak persons) motion support. In this study, the controller controls the angular position and impedance of the exoskeltal robot system using multiple fuzzy-neuro controllers based on biological signals that reflect the human subject's intention. Skin surface electromyogram (EMG) signals and the generated wrist force by the human subject during the elbow motion have been used as input information of the controller. Since the activation level of working muscles tends to vary in accordance with the flexion angle of elbow, multiple fuzzy-neuro controllers are applied in the proposed method. The multiple fuzzy-neuro controllers are moderately switched in accordance with the elbow flexion angle. Because of the adaptation ability of the fuzzy-neuro controllers, the exoskeletal robot is flexible enough to deal with biological signal such as EMG. The experimental results show the effectiveness of the proposed controller.

• Structural Engineering and Mechanics
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• v.47 no.5
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• pp.679-700
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• 2013

Two new predictive design methods are presented in this study. The first is a hybrid method, called neuro-fuzzy, based on neural networks with fuzzy learning. A total of 280 experimental datasets obtained from the literature concerning concentric punching shear tests of reinforced concrete slab-column connections without shear reinforcement were used to test the model (194 for experimentation and 86 for validation) and were endorsed by statistical validation criteria. The punching shear strength predicted by the neuro-fuzzy model was compared with those predicted by current models of punching shear, widely used in the design practice, such as ACI 318-08, SIA262 and CBA93. The neuro-fuzzy model showed high predictive accuracy of resistance to punching according to all of the relevant codes. A second, more user-friendly design method is presented based on a predictive linear regression model that supports all the geometric and material parameters involved in predicting punching shear. Despite its simplicity, this formulation showed accuracy equivalent to that of the neuro-fuzzy model.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1272-1278
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• 1999

A fault is considered as a variation of physical parameters; therefore the design of fault detection and identification(FDI) can be reduced to the parameter identification of a non linear system and to the association of the set of the estimated parameters with the mode of faults. Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to fault diagnosis. In this paper, we proposes an FDI system for nonlinear systems using neuro-fuzzy inference system. The proposed diagnostic system consists of two neuro-fuzzy inference systems which operate in two different modes (parallel and series-parallel mode). It generates the parameter residuals associated with each modes of faults which can be further processed by additional RBF (Radial Basis Function) network to identify the faults. The proposed FDI scheme has been tested by simulation on two-tank system.

• The Korean Journal of Pain
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• v.9 no.1
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• pp.215-218
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• 1996

Frostbite involves freezing of tissues and usually affects the distal aspects of the extremities or exposed parts of the face. such as the ears, nose, chin, and cheeks. It produces tissue injury by ice crystal formation between the cells, cellular dehydration, and microvascular occulsion. There are four degrees of frostbite. First degree is accompanied by erythema and edema; second degree, by vesiculation, blistering, and eschar formation; third degree, by hemorrhagic blistering and bluish gray discoloration; and fourth degree, by injury to subcutaneous tissue, muscle, tendon, and bone leading to mottled, dry, black, and necrotic changes. We successfully treated 2 patients suffering from frostbite by performing sympathetic ganglion block with pure alcohol. We concluded sympathetic ganglion block is one of the most effective treatments for frostbite.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1439-1450
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• 2013

This paper investigates a robust neuro-fuzzy control (NFC) method which can accurately follow the speed reference of an interior permanent magnet synchronous motor (IPMSM) in the existence of nonlinearities and system uncertainties. A neuro-fuzzy control term is proposed to estimate these nonlinear and uncertain factors, therefore, this difficulty is completely solved. To make the global stability analysis simple and systematic, the time derivative of the quadratic Lyapunov function is selected as the cost function to be minimized. Moreover, the design procedure of the online self-tuning algorithm is comparatively simplified to reduce a computational burden of the NFC. Next, a rotor angular acceleration is obtained through the disturbance observer. The proposed observer-based NFC strategy can achieve better control performance (i.e., less steady-state error, less sensitivity) than the feedback linearization control method even when there exist some uncertainties in the electrical and mechanical parameters. Finally, the validity of the proposed neuro-fuzzy speed controller is confirmed through simulation and experimental studies on a prototype IPMSM drive system with a TMS320F28335 DSP.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.1
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• pp.41-46
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• 2016

It has been proven that the dissolved gas analysis (DGA) is the most effective and convenient method to diagnose the transformers. The DGA is a simple, inexpensive, and non intrusive technique. Among the various diagnosis methods, IEC 60599 has been widely used in transformer in service. But this method cannot offer accurate diagnosis for all the faults. This paper proposes a fault diagnosis method of oil-filled power transformers using IEC code based neuro-fuzzy model. The proposed method proceeds two steps. First, IEC 60599 method is applied to diagnosis. If IEC code can't determine the fault type, neuro-fuzzy model is applied to effectively classify the fault type. To demonstrate the validity of the proposed method, experiment is performed and its results are illustrated.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.671-676
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• 2007

In this paper, a novel neuro-fuzzy controller is presented. The generic fuzzy controller is compensated by a neural network controller so that an overall control structure forms a neuro-fuzzy controller. The proposed neuro-fuzzy controller solves the difficulty of selecting optimal fuzzy rules by providing the similar effect of modifying fuzzy rules simply by changing crisp input values. The performance of the proposed controller is tested by controlling humanoid robot arms. The humanoid robot arm is analyzed and implemented. Experimental studies have shown that the performance of the proposed controller is better than that of a PID controller and of a generic fuzzy PD controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.2
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• pp.48-54
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• 2002

In this study, a neuro-fuzzy controller which has the characteristic of fuzzy control and artificial neural network is designed. A fuzzy rule to be applied is automatically selected by the allocated neurons. The neurons correspond to fuzzy rules are created by an expert. To adapt the more precise model is implemented by error back-propagation learning algorithm to adjust the link-weight of fuzzy membership function in the neuro-fuzzy controller. The more classified fuzzy rule is used to include the property of dual mode method. In order to verify the effectiveness of the proposed algorithm designed above, an operating characteristic of a DC servo motor with variable load is investigated.