• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.186-191
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• 2015

Hand gesture is the most common tool used to interact with and control various electronic devices. In this paper, we propose a novel hand gesture recognition method using fuzzy logic based classification with a new type of sensor array. In some cases, feature patterns of hand gesture signals cannot be uniquely distinguished and recognized when people perform the same gesture in different ways. Moreover, differences in the hand shape and skeletal articulation of the arm influence to the process. Manifold features were extracted, and efficient features, which make gestures distinguishable, were selected. However, there exist similar feature patterns across different hand gestures, and fuzzy logic is applied to classify them. Fuzzy rules are defined based on the many feature patterns of the input signal. An adaptive neural fuzzy inference system was used to generate fuzzy rules automatically for classifying hand gestures using low number of feature patterns as input. In addition, emotion expression was conducted after the hand gesture recognition for resultant human-robot interaction. Our proposed method was tested with many hand gesture datasets and validated with different evaluation metrics. Experimental results show that our method detects more hand gestures as compared to the other existing methods with robust hand gesture recognition and corresponding emotion expressions, in real time.

• The Journal of Korean Physical Therapy
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• v.32 no.2
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• pp.70-74
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• 2020

Purpose: This study examined whether 1) the motor inhibition response as cognitive-behavioral component is learning though a stop signal task using stop-signal paradigm, and 2) whether there is a difference in the learning degree according to imagery training and actual practice training. Methods: Twenty young adults (males: 9, females: 11) volunteered to participate in this study, and were divided randomly into motor imagery training (IT, n=10) and practice training (PT, n=10) groups. The PT group performed an actual practice stop-signal task, while the IT group performed imagery training, which showed a stop-signal task on a monitor of a personal computer. The non-signal reaction time and stop-signal reaction time of both groups were assessed during the stop-signal task. Results: In the non-signal reaction time, there were no significant intra-group and inter-group differences between pre- and post-intervention in both groups (p>0.05). The stop-signal reaction time showed a significant difference in the PT group in the intra-group analysis (p<0.05). On the other hand, there was no significant intra-group difference in the IT group and inter-group difference between pre- and post-intervention (p>0.05). Conclusion: These results showed that the motor inhibition response could be learned through a stop-signal task. Moreover, these findings suggest that actual practice is a more effective method for learning the motor inhibition response.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.77-82
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• 2012

We carried out study to prove effectiveness as stimulating corresponding points to lung in hand to experiment applied analysis parameters for image and audio signals in this paper. To this end we collected facial image and voice before and after stimulating corresponding points to lung in hand to a male 20s 25 people. In addition, we analyzed change color, voice energy and speaking rate of right cheek area corresponding points to lung to suggest the theory of the Oriental medicine diagnosis based on data collected. As a result, after performing hand acupuncture, L value of right cheek area decreased average 2.33 and a value b value increased 0.76, 0.97 on average. In addition, size of voice energy increased average 0.42, speaking rate decreased average 0.07. In other words, effect of lung function was improved using hand acupuncture corresponding points to lung.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.824-832
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• 2011

An essential consideration to differentiate prosthetic hand from robot hand is its convenience and usefulness rather than high resolution or multi-function of the robot hand. Therefore, this study proposes a myoelectric hand with a 2 DOF auto wrist module which has 6 essential functions of the human hand such as open, grasp, pronation, supination, extension, flexion, which improves the convenience of the daily life. It consists of the 3 main parts, the myoelectric sensor for input signal without additional attachment to operate the prosthetic hand, hand mechanism with high-torqued auto-transmission mechanism and self-locking module which guarantee the safety under the abrupt emergency and minimum power consumption, and dual threshold based controller to make easy for adopting the multi-DOF myoelectric hand. We prove the validity of the proposed system with experimental results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.4
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• pp.62-68
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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 electrical 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, included noise signal in detected PD signal is well eliminated. we can propose the true shine of PD signal.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.324-329
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• 2009

Hand Motion Modeling and Recognition (HMR) are a fundamental technology in the field of proactive computing for designing a human computer interaction system. In this paper, we present a 3D HMR system including data glove based on 3-axis accelerometer sensor and 3D Hand Modeling. Data glove as a device is capable of transmitting the motion signal to PC through wireless communication. We have implemented a 3D hand model using kinematic chain theory. We finally utilized the rule based algorithm to recognize hand gestures namely, scissor, rock and papers using the 3-D hand model.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.842-847
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• 2005

This paper proposes a novel real-time EMG pattern recognition for the control of a multifunction myoelectric hand from four channel EMG signals. To cope with the nonstationary signal property of the EMG, features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a linear-nonlinear feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. We implement a real-time control system for a multifunction virtual hand. From experimental results, we show that all processes, including virtual hand control, are completed within 125 msec, and the proposed method is applicable to real-time myoelectric hand control without an operation time delay.

• BMB Reports
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• v.39 no.3
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• pp.319-328
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• 2006

SecA protein, a cytoplasmic ATPase, plays a central role in the secretion of signal peptide-containing proteins. Here, we examined effects of signal peptide and ATP on the oligomerization, conformational change, and membrane binding of SecA. The wild-type (WT) signal peptide from the ribose-binding protein inhibited ATP binding to soluble SecA and stimulated release of ATP already bound to the protein. The signal peptide enhanced the oligomerization of soluble SecA, while ATP induced dissociation of SecA oligomer. Analysis of SecA unfolding with urea or heat revealed that the WT signal peptide induces an open conformation of soluble SecA, while ATP increased the compactness of SecA. We further obtained evidences that the signal peptide-induced oligomerization and the formation of open structure enhance the membrane binding of SecA, whereas ATP inhibits the interaction of soluble SecA with membranes. On the other hand, the complex of membrane-bound SecA and signal peptide was shown to resume nucleotide-binding activity. From these results, we propose that the translocation components affect the degree of oligomerization of soluble SecA, thereby modulating the membrane binding of SecA in early translocation pathway. A possible sequential interaction of SecA with signal peptide, ATP, and cytoplasmic membrane is discussed.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.90-94
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• 2013

Research for Manchu character digitalization is at an early stage. This paper proposes a preprocessing algorithm for Manchu character recognition. This algorithm improves the existing Hilditch thinning algorithm so that it corrects thinning error for Manchu characters. The existing algorithm separates the characters into the left-hand side and right-hand side, while our alogorithm uses the central point between the points that strokes exist when it classifies each of characters. The experimentation results show that this method is valid for thinning and classification of Manchu characters.

• Proceedings of the KSRS Conference
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• v.2
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• pp.784-787
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• 2006

Dual-polarized transmission is one of the effective methods to transmit such a high speed data thanks to two independent channel leads to the orthogonal feature between RHCP (Right-Hand Circular Polarization) and LHCP (Left-Hand Circular Polarization). However, in practical case, the transmitted signal by RHCP polarized antenna in satellite can be occurred at the output port of LHCP polarized antenna in ground station, vice versa. XPD (Cross-Polarization Discrimination) is the ratio of the signal level at the output of a receiving antenna that is nominally co-polarized to the transmitting antenna to the output of a receiving antenna of the same gain but nominally orthogonally polarized to the transmitting antenna. In this paper, the detailed estimation of XPD within the interface between satellite and ground station is written and the influence of XPD to link performance is also described.