• 재활복지
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• v.17 no.4
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• pp.401-420
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• 2013

This study was performed to investigate the impact of the Neurocognitive Rehabilitation Therapy on the upper limb function recovery of patients with stroke and their abilities to perform daily activities and to provide basic data for a long-term treatment. A total of 30 patients with hemiplegia that occurred due to stroke were recruited as subjects of the present study, and 15 patients were randomly assigned to a Neurocognitive Rehabilitation Therapy group and a conventional treatment group, respectively. And, tests were performed over four weeks, five times a week, and 30 minutes a session. Manual Function Test(MFT), Fugl-Meyer Assessment Scale(FMA), and Korean-Modified Bathel Index(K-MBI) were used to measure the degree of the functional recovery before and after the experiment. According to the data of this study, in the upper limb function test, the Neurocognitive Rehabilitation Therapy group showed significant increase of the measurement values of MFT and FMA(p <.05), and when the difference between the two groups were compared, the upper limb function showed a statistically significant difference. In the daily activity performance test, only the Neurocognitive Rehabilitation Therapy group showed a significant improvement of K-MBI value(p <.05). Based on the results of the present study, it was demonstrated that the Neurocognitive Rehabilitation Therapy was effective in enhancing the upper limb functions and daily activity performance of patients with stroke.

• Therapeutic Science for Rehabilitation
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• v.12 no.2
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• pp.85-98
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• 2023

Objective : We investigated the efficacy of an artificial intelligence computerized cognitive training program using motion capture to identify changes in cognition, depression, and quality of life in older adults with mild cognitive impairment. Methods : A total of seven older adults (experimental group = 4, control group = 3) participated in this study. During the COVID-19 period from October to December 2021, we used a program, "MOOVE Brain", that we had developed. The experimental group performed the program 30 minutes 3×/week for 1 month. We analyzed patients scores from the Korean version of the Mini-Mental State Examination-2, the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet for Daily Life Evaluation, the short form Geriatric Depression Scale, and Geriatric Quality of Life Scale. Results : We observed positive changes in the mean scores of the Stroop Color Test (attention), Stroop Color/Word Test (executive function), SGDS-K (depression), and GQOL (QoL). However, these changes did not reach statistical significance for each variable. Conclusion : The study results from "MOOVE Brain" can help address cognitive and psychosocial issues in isolated patients with MCI during the COVID-19 pandemic or those unable to access in-person medical services.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.209-214
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• 2010

In this paper, We analyzes the image along the platform (Open Eye), through prevention of dementia or stroke patients and cognitive rehabilitation for the proposed system. This way through the camera image according to user's movement gained OpenCV image processing library, which is based on motion analysis, a part of this rehabilitation is to apply to cognitive rehabilitation. Therefore, this paper proposes a new image analysis system has been exposed to the elderly or stroke patients with dementia, their hand gestures through which patients can detect the image of the cognitive rehabilitation to help them in the analysis of the image analysis system is proposed.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.491-498
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• 2019

Digital twin is a technology that virtualizes physical objects of the real world on a computer. It is used by collecting sensor data through IoT, and using the collected data to connect physical objects and virtual objects in both directions. It has an advantage of minimizing risk by tuning an operation of virtual model through simulation and responding to varying environment by exploiting experiments in advance. Recently, artificial intelligence and machine learning technologies have been attracting attention, so that tendency to virtualize a behavior of physical objects, observe virtual models, and apply various scenarios is increasing. In particular, recognition of each robot's motion is needed to build digital twin for co-robot which is a heart of industry 4.0 factory automation. Compared with modeling based research for recognizing motion of co-robot, there are few attempts to predict motion based on sensor data. Therefore, in this paper, an experimental environment for collecting current and inertia data in co-robot to detect the motion of the robot is built, and a motion prediction model based on the collected sensor data is proposed. The proposed method classifies the co-robot's motion commands into 9 types based on joint position and uses current and inertial sensor values to predict them by accumulated learning. The data used for accumulating learning is the sensor values that are collected when the co-robot operates with margin in input parameters of the motion commands. Through this, the model is constructed to predict not only the nine movements along the same path but also the movements along the similar path. As a result of learning using SVM, the accuracy, precision, and recall factors of the model were evaluated as 97% on average.

• The Journal of Korean society of community based occupational therapy
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• v.2 no.1
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• pp.49-63
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• 2012

Objective : The purpose of study was to verify the clinical effect of a Korean Computer-based cognitive rehabilitation program(called CoTras) for recovering the visual perception function and ADL in stroke. Methods : A CBCRT was applied to 14 Stoke patients who rehabilitation professional medical treatment hospital. All participant were evaluated with four standardized assessment tolls(Motor-Free Visual Perception Test; MVPT, Korean version of Mini-Mental State Examination; MMSE-K, Assesment of Motor and Process Skills: AMPS) before and after the planned computer based cognitive rehabilitation sessions. Results : A significant effect was confirmed (p<.05) from the CBCRT which visual perception function. By each entry comparative result, visual memory, figure ground, visual close, spatial relation, visual discrimination, were the order of treatment. Neither was found any significant effect in improving process skills from AMPS. Conclusion : These results indicate that CoTras have effects on improving visual perception and ADL performance in stroke patients. Will be able to present with the fundamental data CoTras will be able to contribute to increase visual perception function & ADL performance to the stroke patient who has visual perception dysfunction.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.327-345
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• 2016

The purpose of this study was to carry out cognitive movement therapy program for children with affective and behavioral disorder based on neuro science, psychology, motor learning, muscle physiology, biomechanics, human motion analysis, movement control and to quantify characteristic of expression and gestures according to change of facial expression by emotional change. We could observe problematic expression of children with affective disorder, and could estimate the efficiency of application of movement therapy program by the face expression change of children with affective disorder. And it could be expected to accumulate data for early detection and therapy process of development disorder applying converged measurement and analytic method for human development by quantification of emotion and behavior therapy analysis, kinematic analysis. Therefore, the result of this study could be extendedly applied to the disabled, the elderly and the sick as well as children.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.93-94
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• 2015

본 논문에서는 전기자동차의 주행에 있어 발생되는 소음이 아주 적다는 장점이 보행자들에게 있어서는 차량이 접근하고 있다는 인지능력을 감소시키는 단점으로 발생된다. 따라서 인위적인 가상의 엔진음을 발생시켜 보행자들로 하여금 차량이 접근하고 있다는 인지능력을 향상시키기 위한 전기자동차 가상 엔진음 발생기 설계에 대한 연구내용 및 방법을 제시한다. 이 시스템은 전기자동차의 전원이 ON됨과 동시에 동작하여 가상의 엔진음을 발생시키고 적정 거리의 보행자도 무리없이 소리를 인지하여 차량의 접근을 인지할 수 있도록 하여 보행자의 안전을 보장하기 위한 시스템 개발이 최종 목적이다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.739-741
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• 2005

상황 인식(Context-Aware) 시스템은 현재 자신이 처한 상황 정보를 인식하여 그에 맞는 행동을 결정하고 그 결과에 따라 동작하는 시스템을 일컫는다. 이러한 상황 인식 시스템은, 유비쿼터스 컴퓨팅을 비롯해 특정 작업을 수행하기 위해 사용자로부터 주어지는 입력 값 이외의 환경 정보를 필요로 하는 분야에서 주로 사용된다. 이때 시스템이 인지하는 상황은 자신의 작업을 수행하기 위해 필요한 환경 정보로 구성되어 있다. 가령 온도조절 서비스를 담당하는 에이전트가 있다고 할 때, 이 에이전트는 사용자의 요청 온도를 맞춰주기 위해 현재 실내 온도를 측정할 수 있어야 한다. 그래야 요청 온도에 도달했을 때, 동작을 멈출 수 있기 때문이다. 이처럼 각 에이전트가 자신이 필요로 하는 정보를 인지하고 그에 따라 작업을 수행할 때, 다일 에이전트 혼자 그 공간에 존재한다면, 자신이 필요한 정보만을 인지하는 것으로 적절한 작업 수행을 기대할 수 있지만. 둘 이상의 에이전트가 동일 공간에 존재하고, 각 에이전트의 작업 과정이 서로의 수해 과정에 영향을 미칠 가능성 즉, 에이전트 사이의 충돌 발생 가능성이 존재한다. 이미 오디오가 동작하고 있는 방안에서 TV를 작동시키게 된다면, 음악을 들을 수도, TV를 볼 수도 없는 상황이 발생한다. 이에 본 논문에서는 동일 공간에 존재하는 상황 인식 에이전트들 사이에 발생하는 충돌을 해결하기 위한 방법을 제안한다.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.819-830
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• 2009

When simulating large crowds, it is inevitable that the models and motions of many characters will be cloned. McDonnell et al. analyzed user's perception to find cloned characters. They established that clones of appearance are far easier to detect than motion clones. In this paper, we expand McDonnell's research[1], with the focus on multiple clones and the appearance variety in real-time game environment. Introducing the perceptual organization, we show the appearance variety of crowd clones by using game items and texture modulation. Other factors that influence the ability to detect clones were examined, such as the moving direction and distance between character clones. Our results provide novel insights and useful thresholds that will assist in creating more realistic crowds of game environments.

• Information and Communications Magazine
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• v.23 no.8
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• pp.25-34
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• 2006

본 논문은 디지털 홈에서 가동될 다양한 홈 네트워크 장비의 분류와 발전 전망, 그리고 이들 장비가 홈 네트워크에서 서로 연결되어 동작할 때 필요한 소비전력을 최소화하기 위하여 구축하는 에너지 인지 홈 플랫폼의 기술에 대하여 기술한다. 에너지 인지 홈 플랫폼 기술은 홈 네트워크에서 동작하는 각 시스템 수준의 소비 전력 절감 기술과 홈 네트워크 차원의 소비전력 절감 기술을 기본으로 구성된다. 시스템 수준의 소비 전력 제어 기술은 시스템과 이에 연결된 디바이스에 장착되는 소자가 제공하는 소비 전력 제어 기술을 모아서 시스템 수준에서 낭비되는 소비 전력을 줄이는 기술이다. 홈 네트워크차원의 소비 전력 제어 기술은 홈 네트워크에서 연동되는 시스템간에 소비 전력 정보를 공유하여 홈 네트워크 전체에서 소비되는 전력을 제어하는 기술을 말하며, 이를 위한 소비 전력제어 프로토콜을 제안한다.