ヒトを対象として、脳が運動指令を作るプロセスについて、生体信号計測と機械学習などの情報学的手法を組み合わせて研究しています。
とくに、生体信号から運動の意図や脳の状態をリアルタイムに推定する技術の開発し、これを活用して脳の状態と運動パフォーマンスの関係を調べています。
外部機器の操作を補助するBrain-Machine Interfaceの開発や、脳の活動を自己調節する訓練で運動技能の獲得を支援するシステムの構築を目指します。
My research topic is neural mechanism underlying motor control. Using informatics techniques such as machine learning, I sought neural correlates of motor performance and manipulate it with neurofeedback. Furthermore, using technology that estimates movement intentions and brain states in real time from biosignals, we aim to develop Brain-Machine Interfaces that assist in operating external devices and to build systems that support the acquisition of motor skills.
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https://youtu.be/74nq67wFKwI?feature=shared
This work was supported by Moonshot R&D program.
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https://youtu.be/Br2d2T3ZTzY?feature=shared
In collaboration with Dr. Kawasaki in Masaki Takahashi Lab. at Keio Univ. This work was supported by Moonshot R&D program.
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<aside> 🧠
https://youtu.be/cO9zqplQ8Ng?feature=shared
The wheelchair part was performed in collaboration with Dr. Kawasaki in Masaki Takahashi Lab. at Keio Univ.
This work was supported by Moonshot R&D program.
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Iwama S, Yanagisawa T, Hirose R, Ushiba J. Beta rhythmicity in human motor cortex reflects neural population coupling that modulates subsequent finger coordination stability. Commun Biol 5, 2022. https://www.nature.com/articles/s42003-022-04326-4
Iwama S*, Ueno T*, Fujimaki T, Ushiba J. Enhanced human sensorimotor integration via self-modulation of the somatosensory activity. iScience 28, 112145, 2025.
https://doi.org/10.1016/j.isci.2025.112145
