Kohei Baba
Papers
1
Total Citations
11
H-Index
1
About
Kohei Baba is a researcher focused on advancing human-machine interfaces through innovative sensing techniques, particularly in the domain of upper limb motion analysis. His work centers on developing non-invasive methods to capture and interpret human movement, with a primary emphasis on forearm deformation and surface electromyogram (sEMG) signals. Baba’s major contribution lies in his pioneering approach to hand motion recognition, where he introduced a distance sensor array to measure forearm deformation—a novel alternative to traditional sEMG-based systems. This method, detailed in his most-cited 2016 paper (11 citations), offers a robust and practical solution for controlling robotic exoskeletons, prosthetic hands, and evaluating body functions. By addressing the limitations of conventional sEMG, such as signal noise and electrode placement sensitivity, Baba’s work enhances the reliability and usability of assistive technologies. His research has significant implications for rehabilitation engineering and human-robot interaction, making him a notable figure in the field. With a growing citation impact, Kohei Baba continues to push boundaries in wearable sensing, bridging the gap between human intent and machine response for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1