• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.437-439
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• 2008

This paper presents the training system of myoelectric hand prosthesis controlling according to myoelectric signal generated in the human muscle. The training system consist of a trainer, a program for training. The experimental results proved the reliability of proposed training system.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.700-704
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• 1989

A robotic system with a 3-dimensional profile measuring sensor is developed in order to measure the complicated shape of the target body. Due to this 3-dimensional profile measuring sensor, a computer is able to adjust the posture of the robot hand so that complicated global profile of the target body can be recognized after several measurements from the variant directions. In order to enable fast data processing, a digital signal processor and a look-up table is introduced.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.172-177
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• 2013

With Brain Computer Interface (BCI) system, a person with disabled limb could use this direct brain signal like electroencephalography (EEG) to control a device such as the artifact arm. The precise force control for the artifact arm is necessary for this artificial limb system. To understand the relationship between control EEG signal and the gripping force of hands, We proposed a study by measuring EEG changes of three grades (25%, 50%, 75%) of hand grip MVC (Maximal Voluntary Contract). The acquired EEG signal was filtered to obtain power of three wave bands (alpha, beta, gamma) by using fast fourier transformation (FFT) and computed power spectrum. Then the power spectrum of three bands (alpha, beta and gamma) of three classes (MVC 25%, 50%, 75%) was classified by using PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis). The result showed that the power spectrum of EEG is increased at MVC 75% more than MVC 25%, and the correct classification rate was 52.03% for left hand and 77.7% for right hand.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1248-1255
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• 2011

In daily life, another major role of human hand is a communicative function using hand gestures besides grasp function. Therefore, if amputees can express their intention by the prosthetic hand, they can much actively participate in social activities. Thus, this paper propose myoelectric multi-function prosthetic hand which can express 6 useful hand gestures such as Rock, Scissors, Paper, Indexing, Ok and Thumb-up. It was designed as under-actuated structure to minimize volume and weight of the prosthetic hand. Moreover, in order to effectively control various hand gestures by only two EMG sensors, we propose a control strategy that the signal type are expanded as "Strong" and "Light", and hand gestures are hierarchically classified for the intuitive control. Finally, we prove the validity of the developed prosthetic hand with the experiment.

• Journal of Biomedical Engineering Research
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• v.5 no.1
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• pp.5-8
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• 1984

As the ensemble averaged dz/dt signal during exercise gets smoothed, it is difficult to find the distinctive marks for estimation of stroke volume. The cross correlation function was made use of estmating these marks for automatic calculation by computer from the ensemble averaged dz/dt signal. LVET(Left Ventricular Ejection Time) and stroke volume were estimated based on the calculated parameters from the characteristic points. LVET, stroke volume calculated by hand, by the ensemble average and the cross correlation were compared for accuracy validation.

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1679-1681
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• 2001

In this paper, As the wavelet transform has the properties of multi-resolution analysis and time-frequency domain localization, application of wavelet transform is used at partial discharge(PD) signal detected by electromagnetic wave detection method to extract PD signal's various frequency component and its time domain. therefore we can analyzed PD signal's time-frequency domain simultaneously. On the other hand, using wavelet transform denoising process, inclued noise signal in detected PD signal is well elimiated. we can propose the true shape of PD signal.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.291-296
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• 2021

Recently, the dual-polarized antenna array has drawn attention due to the dependency of its signal processing gain on the signal polarization. Even though this polarization dependency makes it possible to mitigate a non-right-hand circularly polarized (non-RHCP) jamming signal from the same direction as a GPS signal, the dual-polarized antennas are not yet widely used for various applications. This study suggests a method that can acquire the polarization dependency of the signal-processing gain by intentionally misaligning antenna elements in a single-polarized antenna array. The simulation results show that the proposed method can successfully mitigate a non-RHCP jammer from the same direction as a GPS signal as if a dual-polarized antenna array does and provide comparable signal-to-jammer-plus-noise ratio (SJNR) performance with a completely aligned single-polarized antenna array and a dual-polarized antenna array.

• Journal of the Korean Institute of Plant Engineering
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• v.23 no.4
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• pp.21-27
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• 2018

This paper proposed the real-time monitoring methodology of a traffic signal controller. The proposed methodology is based on the simulation technology, and it is necessary to construct a simulation model imitating the behavior of a traffic signal controller. By executing the simulation model, we can obtain the 'nominal system trajectory' of the traffic signal controller. On the other hand, an IoT(Internet of Things)-based monitoring device is implemented in a traffic signal controller. Through the monitoring device, it is possible to obtain the 'actual system trajectory'. By comparing the nominal system trajectory and the actual system trajectory, we can estimate the degree of deterioration of a traffic signal controller.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.300-305
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• 2009

This paper describes the intelligent robot's hand with three-axis finger force sensors for an intelligent robot. In order to grasp an unknown object safely, it should measure the mass of the object, and determine the grasping force using the mass, then control the robot's fingers with the grasping force. In this paper, the intelligent robot's hand for an intelligent robot was developed. First, the three-axis finger force sensors were designed and manufactured, second, the intelligent robot's hand with three-axis finger force sensors were designed and fabricated, third, the high-speed control system was designed and manufactured using DSP( digital signal processor), finally, the characteristic test to grasp an unknown object safely was carried out. It was confirmed that the developed intelligent robot's hand could grasp an unknown object safely.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.876-881
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• 2003

This study focused on to design and toanalysis of a myoelectronic hand. We considered a low frequency factor in human life and to quantify low frequency which a human body responded to using a 1-axis ant a 3-axis accelerometer. The dynamic myoelectronic hand are important for tasks such a continuous prosthetic control and a EMG signal recognition, which have not been successfully mastered by the most neural approached To control myoelectronic hand, classifying myoelectronic patterns are also important. Experimental results of FEM are 110㎫ on Thumb, 200㎫ on Index finger, 220㎫ on Middle finger 260㎫ on Ring finger and 270㎫ on Little finger. Experimental results of accelerometer are 1.4-0.4(m/s2) ,(5-20(〔Hz〕) in Feeding activity and 0.4-0(m/s2) (0-10〔Hz〕) in Lifting activity. Considering these facts, we suggest a new type myoelectronic hand.