Yoshikatsu Hayashi
University of Reading, Ritsumeikan University, Google (United States)
Papers
17
Total Citations
273
H-Index
9
About
Yoshikatsu Hayashi is a leading researcher at the intersection of soft robotics, rehabilitation engineering, and cognitive robotics. His work centers on developing assistive technologies that bridge the gap between human intention and robotic action, with a particular focus on stroke rehabilitation. Hayashi’s major contributions include the formulation of a novel gradient descent MARG orientation algorithm (2019, 75 citations) that improves upon the popular Madgwick filter, enhancing accuracy and robustness for robot teleoperation. He has also pioneered the development of wearable assistive soft robotic devices for elbow rehabilitation (2015, 57 citations), integrating brain-computer interfaces (BCI) with virtual reality and soft robotics to enable active patient engagement through novel EEG autocorrelation analysis (2016, 24 citations). His research extends to grounding natural language in human-robot interaction, introducing probabilistic models for synonym grounding (2019, 18 citations), and exploring anticipation as a bridge between synthetic biology and cognitive robotics (2016, 27 citations). Hayashi’s work on embedded fuzzy logic controllers for pneumatic soft robots (2017) and low-cost electronic hardware for soft robot actuation (2015) demonstrates his commitment to practical, accessible solutions. With over 240 total citations, his interdisciplinary approach continues to shape the future of rehabilitation robotics and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Anticipation: Beyond synthetic biology and cognitive robotics27 citations · 2016
- 4
- 5
- 6
- 7
- 8A Probabilistic Framework for Comparing Syntactic and Semantic Grounding of Synonyms through Cross-Situational Learning9 citations · 2018
- 9A Compact Low-Cost Electronic Hardware Design for Actuating Soft Robots9 citations · 2015
- 10