• Journal of Digital Convergence
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• v.11 no.11
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• pp.521-528
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• 2013

This study was performed to examine effects of PNF combined pattern training on balance ability and functional ability of hockey players. In order to achieve this purpose, total 28 participants were separated into two group: 14 comparison group and 14 experiment group, and the experiment group performed PNF combined pattern training for 12 week, 3 times a week, 60 minutes a day. Each group was measured beforehand, after 6 week and 12 week. balance ability was measured using GOOD BALANCE system and functional ability was measured using carioca and shuttle-run test. For statistically verifying above measured values, repeated measure analysis of variance was analyzed and have following results. As the comparing results of balance ability, normal standing eye close(NSEC) was ant-post and velocity moment of experiment group showed significant differences(p<.05). And one leg right eye close(OLREC) was ant-post, med-lat and velocity moment of experiment group showed significant differences (p<.05). Also, dynamic balance ability was ant-post and velocity moment of experiment groups showed significant differences(p<.05). As the comparing results of functional ability, shuttle-run of experiment group sowed significant differences(p<.05). From above results, balance ability of hockey players was shown to be improved through symmetric training of PNF combined pattern applied to hockey players, and it can be considered that this is actively recommended for training method to improve athletic performance of hockey players.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.341-342
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• 2021

본 논문에서는 운동 관련 빅데이터를 적용한 인공지능을 활용하여 개개인에게 알맞은 운동 루틴을 추천해 주는 비대면 방식 PT를 제안한다. 이 정책은 '건강한 사람이 앱을 만나 더 건강해진다.'는 모토를 중심으로, 홈 트레이닝을 하고 싶지만 운동방법을 모르는 사람들로 하여금 자신에게 맞추어진 루틴 구성을 통해 운동 수행능력의 효율성을 높이고, 잘못된 자세로 인한 부상 등을 최소화한다. 또한 이 정책은 기존의 일일이 사용자가 입력해야 했던 시스템들에서 머신러닝을 통한 AI 알고리즘을 통한 추천을 통해 비대면 방식의 수동적인 운동 방식에서 AI가 트레이너 역할을 해주는 방식으로 사용자와 상호작용하고, 정확한 운동 목표를 추천함으로써 운동 지속성과 동기성을 부여한다. 본 논문에서는 프로토타입을 통해 제안하는 AI를 적용한 맞춤 헬스 정책이 기존의 헬스 앱 업계에서 시장성을 보일 수 있다는 가능성에 의의를 둔다.

• Korean Journal of Applied Biomechanics
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• v.19 no.3
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• pp.611-617
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• 2009

The primary purpose of this study was to analysis quantitatively the degree of injury and/or the progress of treatment for physical impairment. This study provided a more detailed study that evaluates all test parameters including maximum grip strength, duration of operation, average grip strength, acceleration work, dynamic endurance time and percent change in static endurance. Also, a complete database management system is developed and used to store related training, evaluation, and personal information. In addition, the system is developed a grip sensor using load.cell transducer (${\leq}60kg$). The system will be efficient to operate and convenient to use, furthermore, it can be helped for understanding and analysis the progress of a patient during a doctor's rehabilitation program.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.681-683
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• 2022

코로나 19 로 인해 사회적으로 활동 범위에 제약이 많아져 신체 노화가 진행중인 노년층의 심각한 운동 부족 현상 발생했다. 이에 따라 본 연구는 스마트 미러 트레이닝 프로그램의 범람 속에 신체적인 불편함을 가지고 있는 노인의 건강 증진에 주목하여 스마트 미러와 노인 자세 탐지, 자세 정확성 판단 시스템을 기반으로 한 자세 분류 서비스 제공 프로그램을 제안한다. 스마트 미러에 탑재된 카메라로 받아온 영상을 MoveNet 과 머신러닝 모델을 사용하여 사용자의 동작을 파악하는 방식으로 활동 프로그램을 진행한다. 향후 디지털 소외 계층의 사용 및 노인 자세 데이터 분석에 활용할 수 있을 것으로 기대한다.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.157-166
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• 2022

Exercise is necessary for a healthy life, but it is recommended that it be conducted in a non-face-to-face environment in the context of an epidemic such as COVID-19. However, in the existing non-face-to-face exercise content, it is possible to recognize exercise movements, but the process of interpreting and providing feedback information is not automated. Therefore, in this paper, to solve this problem, we propose a method of creating a formalized rule to track the contents of exercise and the motions that constitute it. To make such a rule, first make a rule for the overall exercise content, and then create a tracking rule for the motions that make up the exercise. A motion tracking rule can be created by dividing the motion into steps and defining a key frame pose that divides the steps, and creating a transition rule between states and states represented by the key frame poses. The rules created in this way are premised on the use of posture and motion recognition technology using motion capture equipment, and are used for logical development for automation of application of these technologies. By using the rules proposed in this paper, not only recognizing the motions appearing in the exercise process, but also automating the interpretation of the entire motion process, making it possible to produce more advanced contents such as an artificial intelligence training system. Accordingly, the quality of feedback on the exercise process can be improved.

• Smart Media Journal
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• v.12 no.7
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• pp.59-67
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• 2023

Recently, research on behavior analysis tracking human posture and movement has been actively conducted. In particular, OpenPose, an open-source software developed by CMU in 2017, is a representative method for estimating human appearance and behavior. OpenPose can detect and estimate various body parts of a person, such as height, face, and hands in real-time, making it applicable to various fields such as smart healthcare, exercise training, security systems, and medical fields. In this paper, we propose a method for classifying four exercise movements - Squat, Walk, Wave, and Fall-down - which are most commonly performed by users in the gym, using OpenPose-based deep learning models, DNN and CNN. The training data is collected by capturing the user's movements through recorded videos and real-time camera captures. The collected dataset undergoes preprocessing using OpenPose. The preprocessed dataset is then used to train the proposed DNN and CNN models for exercise movement classification. The performance errors of the proposed models are evaluated using MSE, RMSE, and MAE. The performance evaluation results showed that the proposed DNN model outperformed the proposed CNN model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.687-689
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• 2014

Due to the development of health promotion and health care technology of smartphones paradigm from treatment to manage change, and this is increasing the fitness in time for the user. However, fitness club, users find the right exercise law-personal trainer must be costly to pay companies describes the management system is required in order to operate the high costs strain. In this paper, such as scalable servers to OpenWrt Fonera is mainly based on the client to configure the server iOS mobile sensors collect a user's movement through the history of the user's input. This data is sent to the Web and check whether the receiving system via a trainer is to record the users through weight training and to receive feedback.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.4
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• pp.333-338
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• 2017

In recent years, there has been an increasing demand for healthcare services that can periodically monitor health status and maintain health by increasing the weight training population. However, injuries in the absence of trainer are increasing with the increase in the number of members in the fitness training center. Therefore, there is a need for a system that can periodically monitor the user's exercise state and assist in systematic and safe exercise even when the trainer is absent. In this study, we developed an auto training system that can effectively manage the exerciser while supporting the strength movement. The auto training system consists of a cable mount module, a control module, and a training information monitoring module. In order to evaluate performance of the developed system, the assistant force tests are carried out. Experimental results showed that the assistant force works well when the exerciser is out of power.

• Journal of Korea Game Society
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• v.9 no.3
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• pp.121-128
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• 2009

In this paper, we have developed the balance board with electronic devices to use in various fields of remedial and physical balance exercise with interesting game and the functional game. Rehabilitation training using a funny game will be effective for patient's rehabilitation training. A Personal training system uses a balance board with an acceleration sensor and the game controlled by physical balance. To evaluate the operation of the developed system, we developed rehabilitation training game. The proposed game can be applicable to rehabilitation and balance training, and suggested game interface method could use a commercial game with various function through our emulator.

• Korean Journal of Applied Biomechanics
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• v.18 no.1
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• pp.85-95
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• 2008

This study is analyzing about application of taping by movement about shoulder joint's isometric contraction. M. college students take part in experiment. WEMG-8 and HUMAC system are used. Findings were as follows: EMG of muscle's MVIC at each angle before and after taping. 1. In flexion, EMG with taping is effective for supra spinatus at $0^{\circ}{\cdot}45^{\circ}{\cdot}90^{\circ}$, anterior deltoid at $0^{\circ}{\cdot}45^{\circ}$ and biceps brachii at $0^{\circ}{\cdot}90^{\circ}$. 2. In extension, EMG with taping is effective for triceps brachii at $0^{\circ}$, latissimus dorsi at $90^{\circ}$ and posterior deltoid at $45^{\circ}{\cdot}90^{\circ}$. 3. Each angle viewpoint, EMG of latissimus dorsi in extension can be arranged in its high order as $90^{\circ}<45^{\circ}$, $0^{\circ}$ without taping and $90^{\circ}<0^{\circ}$ respectively. EMG of posterior deltoid in extension is in its high order as $90^{\circ}<45^{\circ}<0^{\circ}$ without taping and $90^{\circ}<0^{\circ}$.