Shinya Chiyohara
Advanced Telecommunications Research Institute International
Papers
2
Total Citations
36
H-Index
2
About
Shinya Chiyohara investigates the intersection of human sensorimotor learning and robotic interfaces, with a focus on how technology can enhance motor skill acquisition and rehabilitation. His most impactful work examines how passive training with an upper extremity exoskeleton robot influences proprioceptive acuity and motor learning performance—a study that has garnered 33 citations and sheds light on the neurophysiological mechanisms underlying skill transfer through guided movement. This research has direct implications for sports training and neurorehabilitation, where therapists and trainers physically guide a learner’s limbs. In a more recent contribution, Chiyohara addresses a critical barrier in myoelectric control: the need for user-specific calibration. By applying a collaborative filtering approach, he demonstrates that EMG-based joint torque estimation can be generalized across individuals, paving the way for plug-and-play robotic prostheses and exoskeletons. This work, though early in its citation impact, represents a significant step toward accessible, user-friendly human-robot interaction. Chiyohara’s research bridges robotics, neuroscience, and rehabilitation engineering, offering practical solutions for motor learning and assistive technology.
Research Focus
Key Achievements
Top Papers
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- 2