• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1638-1641
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• 2004

Many walking stands, and assisting tools have been developed for the people with low-limb disability to prevent diseases from bedridden state and to help them walk again. But many of those equipments require user to have some physical strength or balancing ability. In our last research, we developed walking assist system for the people with lower-limb disability. With the system, user can be assisted by actuators, and do not have to worry about falling down. The system adapted the unique closed links structure with four servomotors, three PICs as controller, and four limit switches as HMI (human man interface). We confirmed the adaptability of the system by the experiment. In this research, Muscle Stiffness Sensor was tested as the advanced HMI for walking assist system, and confirmed the adaptability by the experiment. As Muscle Stiffness Sensor can attain the muscle activity, user can interface with any device he want to control. Experimental result with Muscle Stiffness sonsor showed that user could easily control the walking assist system as his will, just by changing his muscle strength.

• Journal of Sensor Science and Technology
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• v.26 no.5
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• pp.353-359
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• 2017

This paper describes the design and manufacture of a ankle two-axis force sensor of a walking assist robot for hemiplegic leg patient. The walking assist robot for the hemiplegic leg patient can safely control the robot by detecting whether the foot wearing the walking assist robot is in contact with the obstacle or not. To do so, a two-axis force sensor should be attached to the robot's ankle. The sensor is used to measure the force of a patient's ankle lower part. The two-axis force sensor is composed of a Fx force sensor, a Fy force sensor and a pulley, and they detect the x and y direction forces, respectively. The two-axis force sensor was designed using by FEM(Finite Element Method), and manufactured using by strain-gages. The characteristics experiment of the two-axis force sensor was carried out respectively. The test results indicated that the interference error of the two-axis force sensor was less than 1.2%, the repeatability error and the non-linearity of the two-axis force sensor was less than 0.04% respectively. Therefore, the fabricated two-axis force sensor can be used to measure the force of ankle lower part in the walking assist robot.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.4
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• pp.83-90
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• 1998

In this paper, we present neural network for control of Left Ventricular Assist Device(LVAD) system with a pneumatically driven mock circulation system. Beat rate(BR), Systole-Diastole Rate(SDR) and flow rate are collected as the main variables of the LVAD system. System modeling is completed using the neural network with input variables(BR, SBR, their derivatives, actual flow) and output variable(actual flow). It is necessary to apply high perfomance control techniques, since the LVAD system represent nonlinear and time-varing characteristics. Fortunately. the neural network can be applied to control of a nonlinear dynamic system by learning capability In this study, we identify the LVAD system with neural network and control the LVAD system by PID controller and neural network feedforward controller. The ability and effectiveness of controlling the LVAD system using the proposed algorithm will be demonstrated by experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.150-155
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• 1997

In this paper,we present neural network for control of Left Ventricular Assist Device(LVAD)system with a pneumatically driven mock cirulation system. It is necessary to apply high perfomance control techniques, since the LVAD system represent nonlinear and time-varing characteristics. Fortunately, the neural network can be applied to control of a nonliner dynamic system by learning capability. In this study,we identify the LVAD system with neural network and control the LVAD system by PID controller and neural network feedforward controller. The ability and effectiveness of controlling the LVAD system using the proposed algorithm will be demonstrated by computer simulation and experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.121-126
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• 1993

Artificial muscle actuators are used in various fields. Especially, they are applied to the power assist circuit to make use of their characteristics. The purpose of this paper is to and analyze the power assist circuit using an artificial muscle actuator. As a result, it is found that the operating feeling of the power assist circuit depends mainly on the flow gain of the pneumatic servo valve. The required flow gain is calculated from the proposed model, and the experimental results agreed with the calculated results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1629-1630
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• 2013

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.2
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• pp.74-80
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• 2000

In this paper, we present a control method of mobile power assist systems. Most of mobile power assist systems have a heavy base for preventing easy tumbling, so continual movement of the base during operations causes high energy consumption and gives the high risk of human injury. Furthermore, the slow dynamics of the base limits the frequency bandwidth of the whole system. Thus we propose a cooperation control method of the mobile base and manipulator, which removes the unnecessary movements of the base. In our scheme, the mobile base does not move until the center of gravity(C.G) of the system goes outside a safety region. When C.G. reaches the boundary of the safety region, the base starts moving to recover the manipulator's initial configuration. By varying the parameters of a human impedance controller, the operator is warned by a force feedback that C.G. is on the marginal safety region. Our scheme is implemented by assigning a nonlinear mass-damper-spring impedance to the tip of the manipulator. Our scheme is implemented by a nonlinear mass-spring impedance to the tip of the manipulator. The experimental results show the efficacy of the proposed control method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.46.1-46
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• 2001

This paper describes a control method of hybrid power assistive system for lower body, HAL, with the techniques of Phase Sequence and the application of EMG. Our objective is to attain the power assist control of motion in the lower body effectively with these two methods. The Phase Sequence which performs basic motion controls of HAL is the method that a motion, the Task, is accomplished by dividing each motion into the unit named Phase and ...

• Journal of the Korean Society for Precision Engineering
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• v.25 no.3
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• pp.141-146
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• 2008

The purpose of this study is to develop the algorithm which can control muscle power assist robot especially for elderly. Recently, wearable robots for power assistance are developed by many researchers, and its application fields are also variable such as for medical or military equipment. However, there are many technical barriers to develop the wearable robot. This study suggest a control method improving performance of a wearable robot system by using a EMG signal of major muscles and a force sensor signal as command signal of system. The result of the robot Prototype efficiency experiment, the case of Maximum Isometric motion it suggest 100% power of muscle, the man need only 66% of MVIC(Maximum Voluntary Isometric Contraction) to lift 5kg dumbbell without robot assist. However the man needs only 52% of MVIC to lift 5kg dumbbell with robot assist. Therefore 20% muscle power increased with robot assist. Also, we designed light weight robot mechanism that extract the command signal verified and drive the wanted motions.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.323-329
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• 2020

This paper presents a control algorithm for a wearable walking aid robot for subjects with paraplegia after stroke. After a stroke, a slow, asymmetrical and unstable gait pattern is observed in a number of patients. In many cases, one leg can move in a relatively normal pattern, while the other leg is dysfunctional due to paralysis. We have adopted the so-called assist-as-needed control that encourages the patient to walk as much as possible while the robot assists as necessary to create the gait motion of the paralyzed leg. A virtual wall was implemented for the assist-as-needed control. A position based admittance controller was applied in the swing phase to follow human intentions for both the normal and paralyzed legs. A position controller was applied in the stance phase for both legs. A power controller was applied to obtain stable performance in that the output power of the system was delimited during the sample interval. In order to verify the proposed control algorithm, we performed a simulation with 1-DOF leg models. The preliminary results have shown that the control algorithm can follow human intentions during the swing phase by providing as much assistance as needed. In addition, the virtual wall effectively guided the paralyzed leg with stable force display.