Papers
8
Total Citations
148
H-Index
6
About
Yuki Ueyama is a multidisciplinary researcher whose work bridges neuroscience, robotics, and biomedical engineering, with particular expertise in motor control, prosthetics, and human-robot interaction. Ueyama's most influential contribution — garnering 45 citations — applies optimal feedback control theory to model dynamic limb stiffness during primate arm movements, offering insights into how the central nervous system manages redundancy that directly inform humanoid robotics design. Complementing this, early experimental work developing the RANARM manipulandum provided the instrumental foundation for studying motor control in Japanese macaques under controlled force perturbations. Ueyama has also made notable strides in clinical robotics, authoring the first reported application of a robotic hip-disarticulation prosthesis and proposing a Bayesian model of the uncanny valley effect to explain why social robots can therapeutically benefit children with autism spectrum disorder — a paper that has attracted 41 citations. His systems identification research further bridges engineering and neuroscience by modeling motor learning, impairment, and recovery mathematically. More recently, Ueyama has turned toward education, developing accessible Arduino-based mobile robots for undergraduate STEM programs. Across these diverse threads, his work consistently demonstrates a commitment to translating fundamental motor neuroscience into practical robotic and rehabilitative applications.
Research Focus
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Top Papers
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