Shotaro Okajima
Papers
5
Total Citations
54
H-Index
4
About
Shotaro Okajima is a leading researcher in rehabilitation robotics and human–robot interaction, with a focus on exoskeleton systems that restore and augment human motor function. His most cited work, “Selective Assist Strategy by Using Lightweight Carbon Frame Exoskeleton Robot” (23 citations), tackles a fundamental challenge: designing exoskeletons that actively assist users without becoming a burden. Okajima’s approach avoids the need for complex intention estimation, instead leveraging lightweight carbon frames and selective assist strategies to improve daily mobility. He has also pioneered methods for generating human-like movement from symbolized information (12 citations), offering a novel framework to evaluate how closely robotic behavior mirrors natural human motion. In rehabilitation, his grasp-training robot activates both motion intention and reflex responses (8 citations), advancing recovery from paralysis. Okajima’s work on joint stiffness tuning through tacit learning (7 citations) and his theoretical contributions to rehabilitation robot controller design (4 citations) further demonstrate his systematic approach to creating intuitive, effective assistive devices. His research bridges engineering and neuroscience, aiming to make exoskeletons and rehabilitation robots more adaptive, lightweight, and clinically viable for real-world use.
Research Focus
Key Achievements
Top Papers
- 1
- 2Generation of Human-Like Movement from Symbolized Information12 citations · 2018
- 3
- 4Joint Stiffness Tuning of Exoskeleton Robot H2 by Tacit Learning7 citations · 2015
- 5Theoretical approach for designing the rehabilitation robot controller4 citations · 2019