Shintaro Nakatani

Tottori University, Japan Society for the Promotion of Science

Papers

Total Citations

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About

Shintaro Nakatani is a pioneering researcher at the intersection of space robotics and neural rehabilitation engineering. His work spans two seemingly distinct domains—active space debris removal and brain-machine interfaces (BMI) for motor recovery—united by a core focus on robotic systems that interact intelligently with their environment. Nakatani’s most cited work, "Lightweight Robot Arm for Capturing Large Space Debris" (2018, 15 citations), proposes a micro-satellite equipped with a simple robotic arm to address the urgent need for active debris removal, offering a practical solution to a growing orbital threat. In parallel, his contributions to rehabilitation robotics are equally impactful. His 2020 study on a brain-controlled cycling system for paraplegia (9 citations) introduces delay-time prediction to improve sensory feedback, while his 2015 work on EEG-based motion discrimination (5 citations) employs logistic regression and Schmitt-trigger thresholds to decode patient intent for exoskeleton-driven therapy. By integrating machine learning with real-time neural signal processing, Nakatani advances accessible, adaptive rehabilitation technologies. His dual-track research demonstrates a rare versatility, applying robotic innovation to both extraterrestrial challenges and human physiological recovery, making him a notable figure in applied robotics and biomedical engineering.