Daiki Arase
Papers
1
Total Citations
5
H-Index
1
About
Daiki Arase is a researcher in biomechatronics and rehabilitation robotics, with a primary focus on the development of intelligent robotic ankle–foot orthoses (AFOs) for gait rehabilitation. His key research areas include electromyography (EMG) signal processing, deep neural network models, and sensor-minimized control systems for assistive devices. Arase’s major contribution lies in addressing the critical challenge of maintaining gait estimation accuracy while reducing sensor inputs—a necessary step toward practical, low-cost wearable robotics. By systematically comparing deep neural network architectures and evaluating the effectiveness of specific EMG feature values for estimating dorsiflexion, he has advanced the understanding of how to balance computational efficiency with clinical precision. His most-cited work (2021, 5 citations) provides a foundational benchmark for researchers seeking to streamline sensor configurations without sacrificing performance. This work is particularly notable for its potential to translate complex robotic AFOs from laboratory settings to everyday clinical use, making gait rehabilitation more accessible. Arase’s research sits at the intersection of machine learning and assistive technology, offering practical solutions for individuals with gait impairments.
Research Focus
Key Achievements
Top Papers
- 1