• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.356-364
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• 2017

This paper presents a force control based on the observer without taking any force or torque measurement from the robot which allows realizing more stable and robust human robot interaction for the developed multi-functional upper limb rehabilitation robot. The robot has four functional training modes which can be classified by the human robot interaction types: passive, active, assistive, and resistive mode. The proposed observer consists of internal disturbance observer and external force observer for distinctive performance evaluation. Since four training modes can be quantitatively identified as impedance variation, position-based impedance control with feedback and feedforward controller was applied to the assistive training mode. The results showed that the proposed sensorless observer estimated cleaner and more accurate force compared to the force sensor and the impedance controller embedded with the proposed observer completed the assistive training mode safely and properly.

• Physical Therapy Korea
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• v.22 no.2
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• pp.30-40
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• 2015

Robot-assisted rehabilitation therapy has been used to increase physical function in post-stroke patients. The aim of this meta-analysis was to identify whether robot-assisted gait training can improve patients' functional abilities. A comprehensive search was performed of PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Physiotherapy Evidence Database (PEDro), Academic Search Premier (ASP), ScienceDirect, Korean Studies Information Service System (KISS), Research Information Sharing Service (RISS), Korea National Library, and the Korean Medical Database up to April, 2014. Fifteen eligible studies researched the effects of robot-assisted gait training to a control group. All outcome measures were classified by International Classification of Functioning, Disability, and Health (ICF) domains (body function and structures, activity, and participation) and were pooled for calculating the effect size. The overall effect size of the robot-assisted gait training was .356 [95% confidence interval (CI): .186~.526]. When the effect was compared by the type of electromechanical robot, Gait Trainer (GT) (.471, 95% CI: .320~.621) showed more effective than Lokomat (.169, 95% CI: .063~.275). In addition, acute stroke patients showed more improvement than others. Although robot-assisted gait training may improve function, but there is no scientific evidence about the appropriate treatment time for one session or the appropriate duration of treatment. Additional researchers are needed to include more well-designed trials in order to resolve these uncertainties.

• Journal of International Academy of Physical Therapy Research
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• v.11 no.2
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• pp.2021-2027
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• 2020

Background: Previous robot-mediated gait training has been proven several limitations such as pointless repeated motion training, decreased presence, etc. In this research, adult stroke patients were participated in robot-mediated gait training accompanied with or without virtual reality program. Objectives: Exploring whether the results indicated virtual reality system has contribution to muscle strength and balance ability. Design: A case series research, cross-over trial. Methods: Eleven participants (male 4, female 7) with adults diagnosed as stroke from medical doctor ware engaged. The participants received 2 treatment sessions of identical duration, robot-assisted gait training with virtual reality and robot-assisted gait training with screen-off randomly crossed over include 1-day for each person of wash-out period. The parameter was muscle activity, the researchers assessed sEMG (surface electromyography). Results: The result showed less muscle activities during training in robot-assisted gait training with virtual reality circumstances, and these indicated muscles were gluteus medius muscle, vastus medialis muscle, vastus intermedius and vastus lateralis muscle, semimembranosus muscle, gastrocnemius-lateral head, and soleus muscle (P<.05). Conclusion: In this study, we analyzed the outcome of muscle activity for clinical inference of robot-assisted gait training with virtual reality (VR). Less muscle activity was measured in the treatment accompanied by VR, therefore, a more systematic, in-depth and well-founded level of follow-up research is needed.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.1
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• pp.91-99
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• 2022

Purpose : The goal of this study is to examine the effect of robot assisted gait training (RAGT) on the kinematic factors (temporospatial gait parameters, gait cycle ratio, and gait line length) of gait in stroke patients. Methods : The subjects of this study were 24 stroke patients selected by inclusion criteria. Participants were randomly allocated to two groups: robot assisted gait training (n=11) and general neurological physical therapy group (n=11). In the robot-assisted gait training group, robot-assisted gait training was mediated for 30 minutes a day in addition to general neurological physical therapy. The general neurological physical therapy group was mediated by general neurological physical therapy for 30 minutes a day in addition to general neurological physical therapy. The number of interventions was 5 times a week for 5 weeks. In order to compare the kinematic factors of walking between the two groups, gait analysis was performed before and after 5 weeks of training using the Zebris gait analysis system. Results : As a result of the gait analysis of the two groups, there were significant differences in temporospatial gait variables (step length, stride length, step width, step time, stride time), gait cycle ratio (swing phase, stance phase) and gait line length. However, there was no significant difference in the cadence (temporospatial gait parameters) in the robot assisted gait training group compared to general neurological physical therapy group. Conclusion : It is considered to be a useful treatment for stroke patients to promote the recovery of gait function in stroke patients. Based on the results of this study, continuous robot assisted gait training treatment is considered to have a positive effect on gait ability, the goal of stroke rehabilitation. In the future, additional studies should be conducted on many subjects of stroke patients, the kinematic factors of the legs according to the severity of stroke and treatment period, and the effect of gait training.

• The Journal of Korean Physical Therapy
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• v.27 no.2
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• pp.124-127
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• 2015

Purpose: The emphasis on gait rehabilitation after stroke depends on training support through the lower limbs, balance of body mass over the changing base of support. However, muscle weakness, lack of control of lower limb, and poor balance can interfere with training after stroke. For this case study report, a wearable robot orthosis was applied to stroke patients in order to verify its actual applicability on balance and gait ability in the clinical field. Methods: Two stroke patients participated in the training using the wearable robot orthosis. Wearable robot orthosis provides patient-initiated active assistance contraction during training. Training includes weight shift training, standing up and sitting down, ground walking, and stair up and down Training was applied a total of 20 times, five times a week for 4 weeks, for 30 minutes a day. Gait ability was determined by Stance phase symmetry profile, Swing phase symmetry profile, and velocity using the GAITRite system. Balance ability was measured using the Biodex balance system. Results: Subjects 1, 2 showed improved gait and balance ability with mean individual improvement of 72.4% for velocity, 19.4% for stance phase symmetry profile, 9.6% for swing phase symmetry profile, and 13.6% for balance ability. Conclusion: Training utilizing a wearable robot orthosis can be useful for improvement of the gait and balance ability of stroke patients.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.38-44
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• 2002

A walking training robot is proposed to provide stable and comfortable walking supports by reducing body weight load partially and a force control of an arm of walking training robot using sliding mode controller is also proposed. The current gait training apparatus in hospital are ineffective for the difficulty in keeping constant unloading level and for the constraint of patients' free walking. The proposed walking training robot effectively unloads body weight during walking. The walking training robot consists of an unloading manipulator and a mobile platform. The manipulator driven by an electro-mechanical linear mechanism unloads body weight in various levels. The mobile platform is wheel type, which allows patients to walt freely. The developed unloading system has advantages such as low noise level, lightweight, low manufacturing cost and low power consumption. A system model fur the manipulator is established using Lagrange's equation. To unload the weight of the patients, sliding mode control with p-control is adopted. Both control responses with a weight and human walking control responses are analyzed through experimental implementation to demonstrate performance characteristics of the proposed force controller.

• PNF and Movement
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• v.19 no.1
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• pp.67-77
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• 2021

Purpose: The purpose of the study was to identify the effects of proprioceptive neuromuscular facilitation (PNF) training and robot rehabilitation training on trunk stability and standing balance in individuals with chronic stroke. Methods: There were 30 patients with chronic stroke, divided into two groups: 15 subjects who received PNF and robot training (the experimental group) and 15 subjects who received standard conservative training (the control group), that participated. The experimental group received treatment for 60 min: 30 min of conventional physical therapy, 15 min of PNF training, and 15 min of robot training. The control group received conventional physical therapy for 60 min. Trunk stabilization (trunk impairment scale) and standing balance (center of pressure, limit of stability, modified functional reach test, and Berg balance scale) were measured before and after intervention. Results: Within each group, both the experimental and control groups significantly improved after the intervention in all tests; however, the experimental group showed greater improvement in scores on the trunk impairment scale, the center of pressure, the limit of stability, the modified functional reach test, and the Berg balance scale. Conclusion: The study verified that PNF training and robot training had a positive influence on trunk stability and standing balance indices in patients with chronic stroke.

• PNF and Movement
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• v.20 no.2
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• pp.295-306
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• 2022

Purpose: This study aimed to investigate the effect of robot-assisted gait training on the active ranges of motion, gait abilities, and biomechanical characteristics of gait in patients who underwent lower extremity surgery, and to verify the effectiveness and clinical usefulness of robot-assisted gait training. Methods: This study was conducted on 14 subjects who underwent lower extremity surgery. The subjects participated in robot-assisted gait training for 2 weeks. The active ranges of motion of the lower extremities were evaluated, and gait abilities were assessed using 10-m and 2-min walk tests. An STT Systems Inertial Measurement Unit was used to collect data on biomechanical characteristics during gait. Spatiotemporal parameters were used to measure cadence, step length, and velocity, and kinematic parameters were used to measure hip and knee joint movement during gait. Results: Significant improvements in the active ranges of motion of the hip and knee joints (flexion, extension, abduction, and adduction) and in the 10-m and 2-min walk test results were observed after robot-assisted gait training (p < 0.05). In addition, biomechanical characteristics of gait, spatiotemporal factors (cadence, step length, and velocity), and kinematic factors (gait hip flexion-extension, internal rotation-external rotation angle, and knee joint flexion-extension) were also significantly improved (p < 0.05). Conclusion: The results of this study are of clinical importance as they demonstrate that robot-assisted gait training can be used as an effective intervention method for patients who have undergone lower extremity surgery. Furthermore, the findings of this study are clinically meaningful as they expand the scope of robot-assisted gait training, which is currently mainly applied to patients with central nervous system conditions.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.28 no.1
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• pp.71-80
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• 2022

Background: This study investigated the effect of robot-assisted arm training on muscle activity of arm and weight bearing in stroke patients. Methods: The study subjects were selected 20 stroke patients who met the selection criteria. 10 people in the robot-assisted arm training group and 10 people in the task-oriented arm training group were randomly assigned. The experimental group performed robot-assisted arm training, and the control group performed task-oriented arm training for 6 weeks, 5 days a week, 30 minutes a day. The measurement tools included surface electromyography and smart insole system. Data were analyzed using independent sample t-test and the paired sample t-test. Results: Comparing the muscle activity of arm within the group, the experimental group and the control group showed significant differences in muscle activity in the biceps brachii, triceps brachii, anterior deltoid, upper trapezius, middle trapezius, and lower trapezius. Comparing the muscle activity of arms between the groups, the experimental group showed significant difference in all muscle activity of arm compared to the control group. Comparing the weight bearing within the groups, the experimental group showed significant difference in the affected side and non-affected side weight bearings and there were significant differences in anterior and posterior weight bearing. The control group showed significant difference only in the non-affected side weight bearing. Comparing the weight bearings between groups, the experimental group showed significant difference in the affected side and non-affected side weight bearings compared to the control group. Conclusion: This study confirmed that robot-assisted arm training applied to stroke patients for 6 weeks significantly improved muscle activity of arm and weight bearing. Based on these results, it is considered that robot-assisted arm training can be a useful treatment in clinical practice to improve the kinematic variables in chronic stroke patients.

• Physical Therapy Rehabilitation Science
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• v.6 no.3
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• pp.106-112
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• 2017

Objective: Robot assisted gait training is implemented as part of therapy for the recovery of gait patterns in recent clinical fields, and the scope of implications are continuously increasing. However clear therapy protocols of robot assisted gait training are insufficent. The purpose of this study was to investigate the effects of robot-assisted gait training applied with guidance force on balance and gait performance in persons with hemiparetic stroke. Design: Two group pre-test post-test design. Methods: Nineteen persons were diagnosed with hemiparesis following stroke participated in this study. The participants were randomly assigned to the unilateral guidance group or bilateral guidance group to conduct robot-assisted gait training. All participants underwent robot-assisted gait training for twelve sessions (30 min/d, 3 d/wk for 4 weeks). They were assessed with gait parameters (gait velocity, cadence, step length, stance phase, and swing phase) using Optogait. This study also measured the dynamic gait index (DGI), the Berg balance scale (BBS) score, and timed up and go (TUG). Results: After training, BBS scores were was significantly increased in the bilateral training group than in the unilateral guidance group (p<0.05). Spatiotemporal parameters were significantly changed in the bilateral training group (gait speed, swing phase ratio, and stance phase ratio) compared to the unilateral training group (p<0.05). Conclusions: The results of this study suggest that robot-assisted gait training show feasibility in facilitating improvements in balance and gait performance for subacute hemiparetic stroke patients.