Duk Shin
Tokyo Polytechnic University
66 Papers
114 Citations
Duk Shin is an academic researcher from Tokyo Polytechnic University. The author has contributed to research in topics: Motor control & Computer science. The author has an hindex of 16, co-authored 62 publications. Previous affiliations of Duk Shin include Tokyo Institute of Technology & Toyota.
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Papers
A Myokinetic Arm Model for Estimating Joint Torque and Stiffness From EMG Signals During Maintained Posture
TL;DR: A novel method for estimating static arm stiffness from muscle activation without the use of perturbation is proposed and confirmed that the proposed method can be used to estimate joint torque, joint stiffness, and stiffness ellipses simultaneously for various postures with the same parameters and produces results consistent with the conventional perturbations method.
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Prediction of muscle activities from electrocorticograms in primary motor cortex of primates.
Duk Shin,Hidenori Watanabe,Hiroyuki Kambara,Atsushi Nambu,Atsushi Nambu,Tadashi Isa,Tadashi Isa,Yukio Nishimura,Yukio Nishimura,Yasuharu Koike +9 more
TL;DR: The results demonstrate the feasibility of predicting muscle activity from ECoG signals in an online fashion and verified that E coG signals are effective for predicting muscle activities in time varying series when performing sequential movements.
Decoding of Covert Vowel Articulation Using Electroencephalography Cortical Currents.
Natsue Yoshimura,Atsushi Nishimoto,Abdelkader Nasreddine Belkacem,Duk Shin,Hiroyuki Kambara,Takashi Hanakawa,Yasuharu Koike +6 more
TL;DR: The proposed electroencephalography (EEG) cortical currents as a new approach for EEG-based brain-computer interface spellers demonstrate the potential utility of EEG cortical currents not only for engineering purposes such as brain- computer interfaces but also for neuroscientific purposes such the identification of neural signaling related to language processing.
Slow eye movement detection can prevent sleep-related accidents effectively in a simulated driving task.
TL;DR: It is demonstrated clearly that the SEM detection can prevent sleep‐related accidents effectively in this simulated driving task.
55
Real-Time control of a video game using eye movements and two temporal EEG sensors
Abdelkader Nasreddine Belkacem,Supat Saetia,Kalanyu Zintus-Art,Duk Shin,Hiroyuki Kambara,Natsue Yoshimura,Nasr-Eddine Berrached,Yasuharu Koike +7 more
TL;DR: This paper presents real-time control of video game with eye movements for asynchronous and noninvasive communication system using two temporal EEG sensors using wavelets to detect the instance of eye movement and time-series characteristics to distinguish between six classes of eye movements.