Papers
11
Total Citations
89
H-Index
6
About
Akihiko Murai is a researcher whose work bridges the fields of biomechanics, robotics, and neuromusculoskeletal modeling, with a particular focus on understanding and replicating human movement in both biological and robotic systems. His most celebrated contribution, the sit-to-stand humanoid robot task (2010, 29 citations), demonstrated the power of learning complex motor behaviors from human demonstration, capturing nuanced stylistic variations in movement. Murai has made significant strides in developing musculoskeletal models and inverse kinematics methods, including a fast pseudo-forward dynamics approach (2023) that advances practical applications in motion capture and human augmentation. His physiological validation work (2014) strengthens the credibility of digital human models used in rehabilitation and sports science. Notably, Murai has explored the neural underpinnings of human motion, modeling somatosensory reflexes and spiking neural networks to illuminate how the nervous system coordinates movement. His comparative studies between humans and humanoid robots further reflect his interdisciplinary vision. More recently, his LVAR framework integrating augmented reality with exoskeletal robotics (2019) addresses pressing societal challenges posed by Japan's rapidly ageing population, showcasing his commitment to translating fundamental research into meaningful real-world impact.
Research Focus
Key Achievements
Top Papers
- 1Sit-to-stand task on a humanoid robot from human demonstration29 citations · 2010
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- 3Musculoskeletal modeling and physiological validation10 citations · 2014
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- 6A Comparative Study Between Humans and Humanoid Robots6 citations · 2018
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- 8A Comparative Study Between Humans and Humanoid Robots3 citations · 2017
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