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Research
Prof. Seong-Whan Lee`s paper accepted in IEEE Transactions on Neural Systems and Rehabilitation Engineering
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Prof. Seong-Whan Lee`s new research on `Position-Independent Decoding of Movement Intention for Proportional Myoelectric Interfaces` was accepted in IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Title: Position-Independent Decoding of Movement Intention for Proportional Myoelectric Interfaces
 
Abstract: For the decade, myoelectric interfaces based on pattern recognition have gained considerable  attention thanks to its naturalness enabling human intentions to be conveyed to and control a machine. However, the high variations of EMG signal patterns caused by arm position changes prohibit its application to the real world. In this paper, we propose a novel method of decoding movement intentions robust to arm position changes towards proportional myoelectric interfaces. Specifically, we devise the position-independent decoding that estimates the likelihood of different arm positions, which we predefine during a training step and also decodes the movement intention in a unified framework. The proposed method has an advantage that could be used to decode the movement intentions on untrained arm position that a realistic scenario. Our experimental results showed that the proposed method could successfully decode the continuous movement intentions (e.g., flexion/extension and radial/ulnar deviation) on both trained and untrained arm positions. Our study also proved the effectiveness of the proposed method by comparing with the existing methods in terms of the decoded trajectories as movement intentions in untrained arm position. 


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Research
Prof. Seong-Whan Lee's paper accepted in IEEE Trans. on Pattern Analysis and Machine Intelligence
Prof. Seong-Whan Lee's paper accepted in IEEE Trans. on Pattern Analysis and Mac…
Prof. Seong-Whan Lee's new research, A Novel Linelet-based Representation for Line Segment Detection was accepted in IEEE Trans. on Pattern Analysis and Machine Intelligence. Title: A Novel Linelet-based Representation for Line Segment Detection Abstract: This paper proposes a method for line segment detection in digital images.We propose a novel linelet-based representation to model intrinsic properties of line segments in rasterized image …

2017-02-14

Prof.Jae-Ho Han’s paper accepted in IEEE/ASME Transactions on Mechatronics
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2017-01-17

Prof.Heung-II Suk’s paper accepted in Medical Image Analysis
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2017-01-13

Prof.Byoung-Kyong Min’s paper accepted in Scientific Reports
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2016-10-13

Prof.Byoung-Kyong Min’s paper accepted in Hearing Research
Prof.Byoung-Kyong Min’s paper accepted in Hearing Research
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2016-10-07

Prof. Christian Wallraven’s paper accepted in Human Brain Mapping
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2016-09-26

Prof. Christian Wallraven`s paper accepted in Psychonomic Bulletin & Review
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2016-09-22

Prof. Seong-Whan Lee`s paper accepted in IEEE Transactions on Neural Systems and Rehabilitation Engineering
Prof. Seong-Whan Lee`s paper accepted in IEEE Transactions on Neural Systems and…
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2016-05-27

Prof. Jae-Ho Han`s paper accepted in IEEE/OSA Journal of Lightwave Technology
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2016-05-27

Prof. Heung-Il Suk`s paper accepted in NeuroImage
Prof. Heung-Il Suk`s paper accepted in NeuroImage
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2016-01-05

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