Shota Maedono
Papers
4
Total Citations
12
H-Index
3
About
Shota Maedono is a pioneering researcher at the intersection of brain-machine interfaces (BMI) and wearable robotics, with a focused mission to restore and augment human motor function. His core research centers on decoding electroencephalography (EEG) signals to enable intuitive, real-time control of upper-limb exoskeletons for power assistance. Maedono’s major contributions include developing novel motion estimation algorithms that leverage the temporal advantage of EEG—capturing neural commands before physical movement occurs—to proactively drive robotic support. His foundational work, such as the 2017 study on constructing a power-assistive system for upper-limb exoskeletons (4 citations), established a framework for non-invasive, EEG-driven robotic control. He further refined feature extraction techniques for shoulder joint movements (2018, 3 citations) and explored neurofeedback training (2021, 2 citations) to enhance users’ ability to generate reliable brain signals for augmentation. While his citation counts reflect an emerging field, Maedono’s work is notable for its practical, user-centered approach to BMI, aiming to reduce system costs and improve accessibility for both disabled rehabilitation and healthy performance enhancement. His research represents a critical step toward seamless human-robot collaboration, where thought alone can amplify physical capability.
Research Focus
Key Achievements
Top Papers
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