• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.6 no.2
• /
• pp.15-22
• /
• 2012

The mechanical system of wearable walking assist robot needs to be optimized for adapting with human body structure and the planned control algorithm should have a secure procedure when a incongruity situation which can cause musculoskeletal injury occurs because a wearable robot is attached to a body. The understanding of walking or musculoskeletal motions characteristics must be preceeded and analyzed for developing novel wearable walking assist robot. In this study we tried to find out the capacities of powers and torques of joint actuators to design optimized performances of system and to obtain the analysis data to figure out the characteristics of joint movements during some types of walk. The major types of walk and motion are stair climbing and descending, sit-to-stand motion, and slope walking. In this study all these motions were analyzed experimentally except slope walking.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.10
• /
• pp.933-938
• /
• 2010

In this paper, we propose the organization of a sensor system and user's intent detection algorithm for walking assist rehabilitation robots. The main purpose of walking assist rehabilitation robots is assisting SCI patients to walk in normal environment. To use walking assist rehabilitation robot in normal environment, it is needed to consider various factors about user's safety and detection of user's intent and so on. For these purposes, we have analyzed the use case of rehabilitation robots and organized the system of sensors for walking assist rehabilitation robots and finally, we have developed the algorithm which is used to detect user's intent for those. We applied our proposal method in the rehabilitation robot, ROBIN, and verified their effectiveness by normal, not patient.

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

• Journal of Biomedical Engineering Research
• /
• v.31 no.4
• /
• pp.269-274
• /
• 2010

The purpose of this study was to develop the FSR sensor suit that controls walking assist device for paraplegic patients. The FSR sensor suit was to detect user's intent and patterns for walking by measuring pressure on the palm and the sole of user's foot. It consisted of four modules: sensing pressure from palm, changing modes and detecting pressure on the palm/at the wrist, sensing pressure from the soles of user's foot, and host module that transmit FSR data obtained from sensing modules to PC. Sensing modules were connected to sensing pads which detect analog signals obtained from the palm or the sole of foot. These collect signals from the target regions, convert analog signals into digital signals, and transmit the final signals to host module via zigbee modules. Finally, host modules transmit the signals to host PC via zigbee modules. The study findings showed that forces measured at the palm when using a stick reflected user's intent to walk and forces at the sole of the user's foot revealed signals detecting walking state.

• Journal of Internet Computing and Services
• /
• v.14 no.6
• /
• pp.33-39
• /
• 2013

When the eldery with limited mobility and disabled use a wheelchairs to move, it can cause decreased exercise ability like decline muscular strength in upper limb and lower extremities. The disabled people suffers with spinal cord injuries or post stroke hemiplegia are easily exposed to secondary problems due to limited mobility. In this paper, We designed intelligent wheelchair robot system for upper limb and lower extremities exercise/rehabilitation considering the characteristics of these severely disabled person. The system consists of an electric wheelchair, biometrics module for Identification characteristics of users, upper limb and lower extremities rehabilitation. In this paper, describes the design and configurations and of developed robot. Also, In order to verify the system function, conduct performance evaluation targeting non-disabled about risk context analysis with biomedical signal change and upper limb and lower extremities rehabilitation over wheelchair robot move. Consequently, it indicate sufficient tracking performance for rehabilitation as at about 86.7% average accuracy for risk context analysis and upper limb angle of 2.5 and lower extremities angle of 2.3 degrees maximum error range of joint angle.

• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.7 no.2
• /
• pp.55-62
• /
• 2013

The exoskeleton robot to assist walking of hemiplegia patients or disabled persons has been studied in this paper. The exoskeleton robot with degrees of freedom of 2 axis has been developed and tested for joint motion. The obtained EMG signal from normal person was analyzed and the control signal was extracted from it for convenient and automotive performance of assistance robot to help hemiplegia patient walks as normal person does. the purpose of using FES(Functional Electrical Stimulation) for hemiplegia patient's walk is to restore damaged body function by this, but this could give fatal electrical shock to patients by wrong use or cause quick fatigue in muscle by continuous stimulation. The convenient movement of hemiplegia patients with minimum muscle fatigue was looked possibly by operation of assistance robot exoskeleton using control signal. and the walking assistance exoskeleton robot seemed works more efficiently than using FES stimulator. The experiment in this study was performed based on usual motion in our life like walking, standing-up, sitting-down, and particularly feedback control system using Piezo sensor along with button switch was applied for smooth swing motion in walking. The experiment also shows that hemiplegia patients can move conveniently by using electromyogram signal of healthy leg for the operation signal of assistance robot system attached at damaged symmetrical leg.

• Science of Emotion and Sensibility
• /
• v.13 no.3
• /
• pp.441-448
• /
• 2010

In the aging society, the walking assist robot is a necessary device for being able to help the older and the lower limb disabled people to walk. In order to produce a convenient robot for the older and the lower limb disabled, it is needed for the research to detect the implicit walking intention and to control robot by a user's intention. This study is a previous study to develop the detection model of the walking intention and analyze the user's walking intention while a person is walking with Lofstrand crutches, by the combination of FSR and tilt signals. The FSR sensors attached user's the palm and the soles of foot are sensing force/pressure signals from these areas and are used for detecting the walking intention and states. The tilt sensor acquires roll and pitch signal from area of vertebrae lumbales and reflects the pose of the upper limb. We can recognize the user's walking intention such as 'start walking', 'start of right or left foot forward', and 'stop walking' by the combination of FSR and tilt signals can recognize.