Yasuharu Koike


Yasuharu Koike


Computational NeuroscienceHuman Motor Control TheoryHuman interface

Expectations for WRHI

I hope that collaborative research with overseas universities will progress, including exchange of students.

Research Projects

  • Visualization and Skill Tradition for knowledge of dexterity

    In this research, we aim to develop equipment and structure that can be passed on to people by visualization.Especially on issues that require the control of the force, to measure and analyze the work of Takumi such as "intuition" or "remember in the body", to understand the problem to the extent possible program.
    Implementation period: December 2018~March 2021
    Related researchers: Natsue Yoshimura, Hiroyuki Kambara, Atsushi Takagi

    Skillstraditionmusculoskeletal modelelectroencephalogram

  • Development of a new brain machine interface based on brain prediction function

    In this research, under the hypothesis that a motion command is generated so as to correct the error between the future state prediction by the movement and the target state, under the hypothesis that this error information is extracted from the brain activity, it seems like to manipulate his / her body We aim to create a brain machine interface that manipulates robots.
    Implementation period: April 2018~March 2019
    Related researchers: Yasuhiro Wada, Hidekazu Yoshida, Ganesh Gowrishankar, Hideyuki Ando, Natsue Yoshimura

    Prediction errorEEGHuman interface

  • Development of robot control technology recognizing comfort and integration with people

    IWe aim to develop control technology of robot which can be recognized and operated as a part of the body without being conscious of the machine by being integrated with the person.
    Implementation period: April 2018~March 2021
    Related researchers: Natsue Yoshimura, Hiroyuki Kambara, Atsushi Takagi

    EEGmusculoskeletal modelhuman interface

  • Motion and force are estimated from ECoG signals

  • Analysis of subjective feeling basedn on computational model

Tokyo Institute of Techonology, Precision & Intelligence Lab. Assistant Professor
Tokyo Institute of Techonology, Precision & Intelligence Lab. Professor
Tokyo Institute of Techonology, Solution Research Lab. Professor
Tokyo Institute of Techonology, Institute of Innovative Research, Professor

Japanese Neural Network Society the Research Award of Excellence
Three-dimensional Fingertip Trajectory Decoded from Electrocorticogram of Human Cerebral Cortex
Yasuhiko Nakanishi (Tokyo Tech), Takufumi Yanagisawa (Osaka Univ), Duk Shin, Hiroyuki Kambara, Natsue Yoshimura (Tokyo Tech), Ryohei Fukuma (ATR), Haruhiko Kishima, Masayuki Hirata (Osaka Univ), Yasuharu Koike (Tokyo Tech):NC2014-102


Japanese Neural Network Society the Research Award of Excellence
Muscle synergy recruitment during arm movements in patients with hemiparesis
Toshihiro Kawase (Tokyo Tech), Atsuko Nishimura, Atsuko Nishimoto, Fumio Liu (Keio Univ.), Hiroyuki Kambara, Natsue Yoshimura, Yasuharu Koike (Tokyo Tech) NC2015-38


2016 Controlling an electromyography-based power-assist device for the wrist using electroencephalography cortical currents, Toshihiro Kawase, Natsue Yoshimura, Hiroyuki Kambara, Yasuharu Koike, Advanced Robotics, Vol.31, 88-96, doi: 10.1080/01691864.2016.1215935

2016 Decoding of covert vowel articulation using electroencephalography cortical currents, Natsue Yoshimura, Atsushi Nishimoto, Abdelkader Nasreddine Belkacem, Duk Shin, Hiroyuki Kambara, Takashi Hanakawa, Yasuharu Koike, Frontiers in Neuroscience, 10(175), pp.1-15, doi: 10.3389/fnins.2016.00175

2016 Individual weight perception from motion on a slope, Kalanyu Z., Shin D., Kambara H., Yoshimura N., and Koike Y., Scientific reports, 6:25432, pp. 1-11 IF=5.228


2017 Mapping ECoG channel contributions to trajectory and muscle activity prediction in human sensorimotor cortex, Yasuhiko Nakanishi, Takafumi Yanagisawa, Duk Shin, Hiroyuki Kambara, Natsue Yoshimura, Masataka Tanaka, Ryokei Fukuma, Haruhiko Kishima, Masayuki Hirata, Yasuharu Koike, Scientific Reports, 7:45486, doi:10.1038/srep4586

2017 Hybrid control of a vision-guided robot arm by EOG, EMG, EEG biosignals and head movement acquired via a consumer-grade wearable device, Nakanishi Y., Yanagisawa T., Shin D., Kambara H., Yoshimura N., Tanaka M., Fukuma R., Kishima H., Hirata M., and Koike Y. Scientific Reports, 7(45486), pp. 1-13, DOI: 10.1038/srep45486, IF = 5.228