Papers
48
Total Citations
1,396
H-Index
19
About
Tomoyuki Noda is a pioneering robotics researcher whose work spans rehabilitation engineering, human-robot interaction, and cognitive developmental robotics. He is best known for his groundbreaking contributions to exoskeleton robot design and control, with a particular focus on using electromyography (EMG) signals to create intelligent, adaptive assistive systems. His 2016 paper on adaptive exoskeleton control via EMG feedback minimisation (166 citations) and his 2017 work introducing EMG-based Model Predictive Control for assist-as-needed rehabilitation (146 citations) have become foundational references in the field, demonstrating how machines can learn to support human movement by responding dynamically to muscle activity. Noda's research extends into biomechanics-inspired robotics, including variable stiffness ankle control for balance (86 citations) and hybrid pneumatic-electric actuation systems. His early contribution to the CB2 child robot platform (133 citations) reflects a broader intellectual curiosity encompassing cognitive developmental robotics. His XoR exoskeleton prototype explored brain-machine interface rehabilitation for stroke patients and individuals with spinal cord injuries, bridging neuroscience and assistive technology. With over 900 cumulative citations across his most prominent works, Noda's research has meaningfully advanced the development of safe, responsive, and user-adaptive wearable robots for rehabilitation and physical assistance.
Research Focus
Key Achievements
Top Papers
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- 3CB2: A child robot with biomimetic body for cognitive developmental robotics133 citations · 2007
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- 6XoR: Hybrid drive exoskeleton robot that can balance75 citations · 2011
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- 8Brain-controlled exoskeleton robot for BMI rehabilitation64 citations · 2012
- 9XoR: Hybrid drive exoskeleton robot that can balance46 citations · 2011
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