• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.44-47
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• 1997

This paper is a study on the hand gesture recognition using Instance-based teaming, Symbolic learning algorithms and Power Glove which supplies information on finger position, hand position and orientation. The data were carefully examined, and a few features of the data that would serve as good discriminants between signs when used with the learning algorithms were extracted. The hand gesture data collected from 5 people were applied to the teaming algorithms. In spite of the noise and accuracy constraints of the equipment used, some accuracy rates were achieved.

• Journal of Magnetics
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• v.22 no.1
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• pp.150-154
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• 2017

A novel high precision spatial positioning method utilizing the electromagnetic momentum, i.e., Electromagnetic Momentum Positioning (EMP), is proposed in this paper. By measuring the momentum of the electromagnetic field around the small current loop, the relative position between the sensor and the current loop is calculated. This method is particularly suitable for the application of close-range and high-precision positioning, e.g., data gloves and medical devices in personal healthcare, etc. The simulation results show that EMP method can give a high accuracy with the positioning error less than 1 mm, which is better than the traditional magnetic positioning devices with the error greater than 1 cm. This method lays the foundation for the application of data gloves to meet the accurate positioning requirement, such as the high precision interaction in Virtual Reality (VR), Augmented Reality (AR) and personal wearable devices network.

• Journal of Sensor Science and Technology
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• v.26 no.2
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• pp.128-134
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• 2017

Until now, neuropsychological tests can diagnose the brain dysfunction, however, cannot distinguish the objective data of experiment enough to distinguish the relationships between brain dysfunction and cerebropathia. In this paper, an automatic cognitive test equipment system with 6-axis motion sensors was proposed for the automation of neuropsychological tests. Fist-Edge-Palm(FEP) test and Go-no go test were used to evaluate motor programming of frontal lobe. The motion data from the specially designed motion glove are transmitted wirelessly to a computer to detect the gestures automatically. The healthy 20 and 11 persons are investigated for the FEP and Go-No go test, respectively. The recognition rates of gestures of FEP and Go-No go test are min. 91.38% and 89.09%. In conclusion, the automations of cognitive tests are successful to diagnose the brain diagnostics quantitatively.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.6
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• pp.65-71
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• 2010

The aim of the study intends to investigate wearing practice of personal protective equipment for firefighter in gyeongnam province and to provide the base data for the safety and health of firefighter. The results of the study are as follows. The overall reliability of fire personal protection equipment has been investigated by 3.19 and an overall improvement in the personal protective equipment is needed. Firefighter showed such a low satisfaction leather fire boots(2.68), glove(2.67) and rubber fire boots(2.59) in personal protective equipment and rubber fire boots(2.75), glove(2.77) and leather fire boots(2.97) has been investigated by the state of the poor. For personal protective equipment, firefighters have been experiencing many difficulties on the fit and weight. To overcome this problem, it is necessary to be designed ergonomically and to develop high-performance, lightweight materials.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.2
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• pp.91-96
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• 2015

We propose AirPincher, a handheld pointing device for recognizing delicate mid-air hand gestures to control a remote display. AirPincher is designed to overcome disadvantages of the two kinds of existing hand gesture-aware techniques such as glove-based and vision-based. The glove-based techniques cause cumbersomeness of wearing gloves every time and the vision-based techniques incur performance dependence on distance between a user and a remote display. AirPincher allows a user to hold the device in one hand and to generate several delicate finger gestures. The gestures are captured by several sensors proximately embedded into AirPincher. These features help AirPincher avoid the aforementioned disadvantages of the existing techniques. We experimentally find an efficient size of the virtual input space and evaluate two types of pointing interfaces with AirPincher for a remote display. Our experiments suggest appropriate configurations to use the proposed device.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.890-896
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• 2022

In this paper, gimbal camera control through smart gloves was implemented to increase convenience and accessibility to the control of drones used in various fields. Smart gloves identify human gestures and transmit signals through Bluetooth. The received signal is converted into a signal suitable for the drone through a GCS (Gound Control Station). Signals from smart gloves are expressed in a quaternion method to prevent gimbal locks, but for gimbal cameras, conversion is required to use Roll, Pitch, and Yaw methods. The data conversion mission is performed in the GCS. The GCS transmits an input signal to the control board of the drone through Wi-Fi. The control board generates and outputs the transmitted signal in a PWM manner. The output signal is input to the gimbal camera through the SBUS method and controlled. The input signal of the smart glove averaged 0.093 s and up to 0.099 s to output to the gimbal camera, showing that there was no problem in real-time use.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.933-940
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• 2022

In this paper, the algorithm was developed to recognize hand 3D position through 2D image sensor and implemented a system to remotely control the 6 d.o.f. robot arm by using it. The system consists of a camera that acquires hand position in 2D, a computer that controls robot arm that performs movement by hand position recognition. The image sensor recognizes the specific color of the glove putting on operator's hand and outputs the recognized range and position by including the color area of the glove as a shape of rectangle. We recognize the velocity vector of end effector and control the robot arm by the output data of the position and size of the detected rectangle. Through the several experiments using developed 6 axis robot, it was confirmed that the 6 d.o.f. robot arm remote control was successfully performed.

• Journal of the Korean Society of Costume
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• v.55 no.6 s.96
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• pp.24-37
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• 2005

This study was performed to get basic data for gloves size system and pattern planning suitable Korean hand shape. Data was collected through measuring hand size of man and woman from age 18 to 30 as subjects living in metropolitan area. by analysing the measured data, the difference in man and woman and the gloves size system was established. The results of study are as follows: 1. The Deviation of hand girths and hand lengths was larger than that of hand width in both man group and woman group. In all items. deviation in man was larger than woman. 2. In sex difference, there was difference between mall group and woman group in all items. In age difference, there was difference between mall group and woman group in mainly girth and the difference was bigger in group under 24 years old than in group over 24 years old. 3. The weight showed the highest $correlation(r{\geqq}0.8)$ with girths and high correlation with widths $(r{\geqq}0.7).$ The height showed the highest positive $correlation(r{\geqq}0.8)$ with and elbow length and high correlations with width and girths item. There were high positive correlation between vertical lengths in hand and between horizontal lengths but low correlation between vertical lengths and horizontal lengths. 4. The basic parts for gloves size system, hand lengths and hand girths were divided into 1cm interval. The results shouted that $91.0\%$ of man group were ranged from 18cm to 20cm section and $92.4\%$, of woman group were ranged from 16cm to 18cm section. 5. The interval which has the highest covet· rate was hand length 19cm and hand girth 20cm interval which covered $18.65\%$ of man group. The intervals which showed cover rate more than $5\%$ was total 7 and they covered $73.1\%$ of man group. The interval which has which has the highest cover rate was hand length 17cm and hand girth 17cm interval which covered $21.37\%$ of woman group. The intervals which showed cover rate more than $5\%$ was total 6 and they covered $72.5\%$ of total woman group.

• Korean Journal of Applied Biomechanics
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• v.15 no.2
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• pp.113-117
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• 2005

As a preliminary study of finding the relationship between the force at the grip and the success rate during putting stroke, the putting grip sensor system using FSR sensors was developed. The system consisted of the hardware which had the sensor part with 8 sensors per putting glove and data acquisition part as well as the software which had the real-time monitoring program and the offline post-processing program. After experiments with elite-golfer using this system, it is possible to suggest the proper force ranges at the grip during putting stroke.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.690-695
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• 2009

본 논문은 영화, 방송, 애니메이션 등의 다양한 동영상 콘텐츠에 수화 애니메이션을 합성하여 동영상 콘텐츠를 청각 및 언어장애인들에게 이해시키기 위한 수화 통역 VR 콘텐츠 시스템을 제안하고자 한다. 제안된 시스템은 수화 사전에 있는 수화들을 3D 애니메이션으로 DB화하기 위해, 모션 캡처 시스템과 데이터 글러브를 사용하여 실제 사람처럼 자연스러운 애니메이션을 생성하였다. 최종적으로 동영상 콘텐츠의 자막이나 대본의 구문분석을 한 후, 이를 수화용 단어자막을 통해 수화 애니메이션을 DB에서 검색한 후, 실시간적으로 기존 동영상 콘텐츠와 동기합성을 하여 수화 통역 콘텐츠를 제공하는 VR 콘텐츠 시스템을 구현하였고 이 시스템을 동화용 애니메이션에 적용하였다.