• Convergence Security Journal
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• v.22 no.1
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• pp.135-140
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• 2022

This study aims to analyze exercise cases and issues using smart devices and technologies, and to present the development direction of a smart exercise environment suitable for the wellness life of active seniors with high activity and economic power unlike the existing silver generation. In the fitness industry, the subscription economy that regularly receives or uses necessary exercise tools, services, and digital content is expanding, and business models based on hardware sales and content subscription continue to emerge. In order to have value competitiveness as a platform that provides active seniors with integrated exercise services for health care, not only fitness centers, but also home training exercise equipment, fitness-related applications, and smart wearable device markets should be organically connected to form an expanded total platform. In order to have value competitiveness as a platform that provides active seniors with integrated exercise services for health care, not only fitness centers, but also home training exercise equipment, fitness-related applications, and smart wearable device markets should be organically connected to form an expanded total platform. The linkage of the digital healthcare function, which provides real-time changes to exercise programs based on continuous monitoring and feed back through wearable devices before, after, and during exercise by receiving and selecting exercise programs suitable for individual health status, is the differentiating factor in the smart fitness model.

• Journal of Fashion Business
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• v.26 no.4
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• pp.112-122
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• 2022

The purpose of this study is to investigate the effect of using socks combined with EMS on ankle pain reduction and ankle function improvement in home training participants. In this study, the conductive fabric was combined using socks that can properly compress the ankle. First, VAS was measured during EMS training after fatigue was induced and compared with fatigue during rest. It was confirmed that the level of VAS after EMS training was lower than after rest and fatigue. It was also confirmed that EMS training, which combines EMS with socks, was effective in reducing pain. The experimental action is a measurement action of WBLT and lying posture, and the situation before and after EMS training was compared by performing 30 minutes on the treadmill to cause delayed muscle pain during exercise. As a result of this study, it was found that pain reduction and ROM function were improved when electrical stimulation was performed using EMS socks. It was also confirmed that the application of electrical stimulation to EMS socks effected on ankle fatigue and function improvement. From the study results, it is expected that wearing socks equipped with EMS significantly reduces ankle injuries and improves functional recovery for home training participants.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1967-1983
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• 2020

The goal of this paper is to analyze and build an algorithm to recognize hand gestures applying to smart home applications. The proposed algorithm uses image processing techniques combing with artificial neural network (ANN) approaches to help users interact with computers by common gestures. We use five types of gestures, namely those for Stop, Forward, Backward, Turn Left, and Turn Right. Users will control devices through a camera connected to computers. The algorithm will analyze gestures and take actions to perform appropriate action according to users requests via their gestures. The results show that the average accuracy of proposal algorithm is 92.6 percent for images and more than 91 percent for video, which both satisfy performance requirements for real-world application, specifically for smart home services. The processing time is approximately 0.098 second with 10 frames/sec datasets. However, accuracy rate still depends on the number of training images (video) and their resolution.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.80-89
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• 2009

The importance of personalized services has been attracted in smart home environments according to the development of ubiquitous computering. In this paper, we proposed the smart home personalized service system based on context information using the speech recognition. The proposed service consists of an OSGi framework based service mobile manager, service manager, voice recognition manager, and location manager. Also, this study defines the smart home space and configures the commands of units, sensor information, and user information that are largely used in the defined space as context information. In particular, this service identifies users who exist in the same space that shows a difficulty in the identification using RFID through the training model and pattern matching in voice recognition and supports the personalized service of smart home applications. In the results of the experiment, it was verified that the OSGi based automated and personalized service can be achieved through verifying users in the same space.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.153-155
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• 2020

가상환경 홈 트레이닝 시스템은 바이러스, 날씨, 환경 등으로 인해 외부활동이 제한된 경우 실내에서도 실외에서 운동하는 것과 같은 효과를 얻기 위하여 구성하였다. 사용자는 실내에서도 vr 기기를 사용함으로써 가상환경을 통해 보다 실감나는 환경으로 운동을 할 수 있다

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.28 no.2
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• pp.106-114
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• 2017

Objectives: This study was to examine the effectiveness of computerized cognitive ability enhancement program (CCAEP) using Smarttoy. The CCAEP using Smart-toy which can interact with children via bluetooth is a kids-friendly and convenient method for improving children's cognitive abilities by increasing their motivation for performing the program. We developed the CCAEP which designed to train auditory-verbal memory, visual-spatial memory, auditory-verbal working memory, and visual-spatial working memory. Methods: Eighteen children aged 8 to 10 participated in CCAEP individual training composed of 8 sessions of 40 minutes each for 4 weeks. The effect of the training was measured with Smart Toyweb's cognitive assessment tasks (smart device based assessment) as well as traditional neuropsychological tests before and after the training. Results: Children showed significant improvement in auditory-verbal memory, visual-spatial memory, auditory-verbal working memory and visual-spatial working memory abilities after the training. Conclusion: This study demonstrated promising results suggesting the effectiveness of CCAEP using Smart-Toy in clinical settings as well as school and home situations. Further controlled study with larger sample size including various clinical groups is needed to confirm the present results.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.209-215
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• 2019

In order to provide a safe free-weight-training environment to people without workout trainers, we suggest a smart bench press machine with an automatic weight control system sensitive to user tiredness. Physical weight plates on the machine are replaced with a hydraulic cylinder as a press load and the cylinder knob is coupled with a step motor to change its tensile force automatically in-between lifting exercises. Three subjects participated to verify the usability of the smart bench press machine. They were asked to lift a 6-RM press load 10 times with 3 different lifting conditions: 1) no assistance, 2) a human assistance, and 3) the automatic weight control. All subjects were not able to complete the 10 sets without assistance due to tiredness, but they finished the full sets under the two assistive conditions. Average lifting speeds under the automatic weight control condition showed the most consistent level. Normalized quasi-tension data based on surface electromyogram signals of both Pectoralis Majors revealed that the subjects maintained the target muscle activation level above 50% but not more than 80% throughout the 10 sets. Therefore, the smart bench press machine is expected to both keep pace with the lifting exercise and reduce risk of injuries due to excessive muscle tensions.

• Journal of Practical Engineering Education
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• v.11 no.2
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• pp.283-289
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• 2019

Recently, product mobility, data compatibility and communication connectivity have become very important to the control system, depending on the application of smart manufacturing. Accordingly, embedded systems are essential in all industries including home appliances, telecommunication, and national defense. Therefore, the demand for embedded system development personnel is increasing further, and education and training programs are needed to combine the practical skills of industrial sites, including programming skills and hardware. Currently, embedded system education offers a variety of education centered on Aduino, but this is mostly for beginners and is not sufficient for majors. In addition, while various prototype studies related to embedded systems are active, the training and training programs for working-level human resources needed at industrial sites are very scarce. Therefore, in order to foster the working personnel of the embedded system for the application of smart manufacturing, this paper selected the capability unit through in-depth interviews and survey analysis of 10 experts based on NCS, and developed education and training programs and contents.

• Information Systems Review
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• v.23 no.4
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• pp.183-198
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• 2021

Due to the Covid-19 pandemic, the home-training app market is growing rapidly and numerous apps are entering the market. It is becoming more difficult for an app to secure the profitability. In this study, by analyzing actual user data of a reward-based home-training app, we propose a model that predicts cash-cow users of the app. Cash-cow users are the users who watch in-stream ads to watch training videos although they cannot earn any rewards by doing so. Thus, these users make profits for the app yet do not incur any costs. The results of this study show that the users who irregularly watch training videos are more likely to be cash-cow users than the users who regularly watch training videos. This result suggests that, paradoxically, for sustainable profitability, home-training apps may need to find a way to retain the users who watch training videos irregularly so that they can be satisfied with the service and continue use the apps.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.830-832
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• 2019

IoT 기술의 도래로 인하여 실생활에 사용되는 사물들에 Sensor가 부착되어 시간마다 Sensor data가 발생하는 세상이 열리게 되었다. 이러한 IoT Device들에 부착되어 있는 sensor를 통하여 수집이 된 data는 방대한 양을 가지기 때문에 Deep Learning에 적용하는데 충분하며 아주 중요한 역할을 한다. 이러한 IoT Device들은 우리의 실제 생활에 아주 가까이 다양한 환경으로 접할 수 있다. 예를 들어 스마트시티, 스마트팩토리, 스마트홈 등이 있다. 이러한 것들은 우리의 일상생활에 편리함과 직결되어 있다. 본 논문에서는 Smart home 환경에서의 Multi Resident Activity Recognition이다. Smart home의 가구에 부착되어 있는 센서에서 발생된 센서데이터를 활용하여 1) Training Similarity Network, 2) Embedding, 3) Clustering, 4) Recognizing 네 단계 프로세스를 거쳐 문제를 해결한다. 그 결과, 우리가 제안한 프로세스를 통하여 차원 축소 효과와 Un-seen data를 효과적으로 처리할수 있게 된다.