• The Journal of Korean Physical Therapy
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• v.22 no.4
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• pp.29-33
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• 2010

Purpose: The purpose of this study was to assess and compare the reliability of the Modified Tardieu Scale (MTS) with the Modified Ashworth Scale (MAS) in patients with hemiplegia. Methods: Two experienced physical therapists examined twenty six patients (17 male and 9 female) with an age range of 19-83 years (mean=51.9 SD=15.2). They assessed the elbow flexor/extensor muscle spasticity in the affected side. Interand intra-rater reliability of the MAS and the MTS were calculated using kappa statistics. Intraclass correlation coefficient (ICC) was calculated to determine the inter- and intra-rater reliability of the angle of muscle reactions (R2-R1). Results: The intra-rater reliability of the MAS (K=0.39-0.55) and MTS (K=0.33-0.55) was fair to moderate. The inter-rater reliability was significantly higheras measured with MTS (K=0.54-0.66) in comparison with MAS (K=0.52). Intra-rater reliability of R2-R1 was moderate to almost perfect (ICC=0.52-0.86), and inter-rater reliability was substantial (ICC=0.74-0.76). Conclusion: The MTS provides higher inter-rater reliability compared with the MAS in hemiplegia patient analysis, but intra-rater reliability of both scales was not significantly different. Thus further research is needed to examine not only reliability, but also validity of these measurement systems.

• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.3
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• pp.556-561
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• 2008

ChongMyeong-Tang (CMT) have been used clinically to treat patient with amnesia and dementia. In addition, CMT have been also used for examinee to improve learning ability in Korea. This study was designed to investigate the effects of Gagam-ChongMeong-Tang (GCMT) on cognitive dysfunction recovery after ischemic brain injury in rats. Rats were divided into three groups; (1) normal, (2) commercial diet after ischemic brain injury (control), (3) CMT diet after ischemic brain injury (experiment). In our study, we carried out Morris water maze test for cognitive motor behavior test and immunohistochemistry study through the change BDNF in the hippocampus($7^{th},\;14^{th}\;day$). In Morris water maze test, cognitive motor function recovery was significantly increased in the experiment group as compared with control group on $7^{th}\;and\;14^{th}\;day$ day (p<0.01). In immunohistochemistric response of BDNF in the hippocampus, more immune reaction was investigated in the experiment group as compared with control group on $7^{th}\;and\;14^{th}\;day$. Especially more immune reaction was experimented $14^{th}$ day. These results imply that GCMT can play a role in facilitating recovery of cognitive function after ischemic brain injury in rats.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.49-54
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• 2003

In this paper, we propose a controller with the self-organizing neural network compensator for compensating PID controller's response. PID controller has simple design method but needs a lot of trials and errors to determine coefficients. A neural network control method does not have optimal structure as the parameters are pre-specified by designers. In this paper, to solve this problem, we use a self-organizing neural network which has Back Propagation Network algorithm using a Gaussian Potential Function as an activation function of hidden layer nodes for compensating PID controller's output. Self-Organizing Neural Network's learning is proceeded by Gaussian Function's Mean, Variance and number which are automatically adjusted. As the results of simulation through the second order plant, we confirmed that the proposed controller get a good response compare with a PID controller. And we implemented the of controller performance hydraulic servo motor system using the DSP processor. Then we observed an experimental results.

• PNF and Movement
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• v.18 no.1
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• pp.23-34
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• 2020

Purpose: To explore the effects of action observation combined with modified constraint-induced movement therapy on upper-extremity function and the activities of daily living in subacute stroke patients. Methods: Twenty-four subacute stroke patients were randomly assigned to the experimental group or the control group (n = 12 each). Both groups received therapy based on motor learning concepts, including repetitive and task-specific practice. The experimental group watched video clips for 10 minutes related to tasks performed during modified constraint-induced movement therapy while the control group watched videos unrelated to upper-extremity movement. These programs were performed for 40 minutes a day five times a week for four weeks. Their scores on the Fugl-Meyer assessment of upper extremities (FMA-UE), the action research arm test (ARAT), a motor activity log (amount of use [AOU] and quality of movement [QOM]), and the modified Barthel index (MBI) were recorded. Results: In both groups, all variables were significantly different between the pre-test and post-test periods (p < 0.05). The post-test variables were significantly different within each group (p < 0.05). In the experimental group, the changes between pre-test and post-test scores in the FMA-UE (14.39 ± 4.31 versus 6.31 ± 4.63), the ARAT (16.00 ± 4.73 versus 11.46 ± 3.73), MAL-AOU (1.57 ± 0.15 versus 1.18 ± 0.28), and MBI (27.54 ± 4.65 versus 18.08 ± 8.52) were significantly higher than those of the control group (p < 0.05). Conclusion: These findings suggest that action observation combined with modified constraint-induced movement therapy may be a beneficial rehabilitation option to improve upper-extremity function in subacute stroke patients with moderate impairment.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.3
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• pp.171-180
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• 2019

Purpose : The purpose of this study was to investigate the difference in motor cortical excitability during mental practice and action observation in subjects with forward head posture. Methods : This study was performed in two groups, a forward head posture group (n=17) and a normal posture group (n=17). Electroencephalography (EEG) was conducted to investigate cerebral cortex activity, and six electrodes were attached to Fp1, Fp2, C1, C2, C3, and C4 to measure the relative alpha power, relative beta power, relative gamma power, and mu rhythms. The subjects were requested to perform the four different conditions, which were eye opening, eye closing, mental practice, and action observation for 300 seconds. Results : The results showed that the relative alpha waves showed a significant difference between the normal and forward head posture groups in the C1, C2, C3, and C4 regions with the eyes open (p<.05). The relative beta waves also showed a significant difference between the two groups in the Fp1 and Fp2 regions during action observation (p<.05). The relative gamma waves were significantly different between the normal and forward head posture groups in the Fp1 and Fp2 regions during action observation (p<.05) in C1, C2, and C3 with eyes closed (p<.05) and in C1, C2, C3, and C4 with eyes open (p<.05). Conclusion : The results of this study showed that EEG change in the forward head posture group was different from that in the normal control group in action observation rather than in mental practice. Therefore, we are expected to provide a neurophysiological basis for applying action observation to motor skill learning during exercise for correcting forward head posture.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2497-2503
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• 2012

In this study an educational robot for programming education was designed and implemented. The robot in this study is composed of hardware containing a sensor, a processor, and a motor driver circuit, software to control the educational robot, machine parts to manufacture the robot structure, and a teaching material containing educational contents and the manufacturing manual. This robot is characterized by direct programming without a computer, which gives no spatial restrictions on robot education and enables dynamic program education beyond limitations of the existing static computer program education since students' programming results are found in the robot's movements. User-centered functional commands, which make it possible to control the robot with simple knowledge concerning hardware and basic commands, were used to enable even students who first accessed a robot or computer program to make access with ease.

• Journal of Korean Elementary Science Education
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• v.24 no.1
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• pp.86-101
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• 2005

In this study, a brain-basrd model for science teaching and learning was developed based on the natural processes which human acquire knowledge about a natural object or on event, the major domains of science educational objectives of the national curriculum, and the human brain's organizational patterns and functions. In the model, each educational objective domain is related to the brain regions as follows: The affective domain is related to the limbic system, especially amygdala of human brain which is involved in emotions, the psychomotor domain is related to the occipital lobes of human brain which perform visual processing, temporal lobes which perform functions of language generating and understandng, and parietal lobes which receive and process sensory information and execute motor activities of body, and the cognitive domain is related to the frontal and prefrontal lobes which are involved in think-ing, planning, judging, and problem solving. The model is a kind of procedural model which proceed fiom affective domain to psychomotor domain, and to cognitive domain of science educational objective system, and emphasize the order of each step and authentic assessment at each step. The model has both properties of circularity and network of activities. At classrooms, the model can be used as various forms according to subjects and student characteristics. STS themes can be appropriately covered by the model.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1202-1211
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• 2018

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.90-99
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• 2017

Sports climbing requires repeated movements within a limited space, which may cause climbers to lose their constant interest in it. Furthermore, it is important that coaches should give lessons focusing on demonstrations to make sure that learners can understand the movements on their own, However, in traditional sports climbing lessons, they give instructions on almost every movement of learners' hands and feet. Hence, there have been constant calls for replacing these existing sports climbing lessons and presenting new methods to ensure that learners can observe their coaches' demonstrations in real time and emulate them. An introduction of the image training using spatial augmented reality techniques to solve these problems may have a positive effect on the improvement of learners' motor skills and attitudes toward lessons. This study aims to verify the effectiveness of the Climbing Character Animation (CCA) as a learning tool for sports climbing. To achieve this research objective, it applied it to actual sports climbing to verify its utility. As a result, it was shown that the lessons using spatial augmented reality-based CCA had a higher effectiveness than traditional sports climbing lessons in the degree of interest inducement, emersion and learning effects.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.