Ya-Hsin Hsueh — accepted AI-conference papers

2024

Machine-Learning-Based Accurate Finger Joint Stiffness Estimation With Joint Modular Soft Actuators

Fuko Matsunaga, Ema Oba, Ming-Ta Ke, Ya-Hsin Hsueh, Shao Ying Huang, José Gómez-Tames +1

RA-L 2024

Finger joint stiffness assessment is very important in quantifying the degree of disability in stroke patients and determining rehabilitation strategies and plans. However, the evaluation methods used in clinical practice rely heavily on the experience of clinicians. In our previous study, we adapte

Cited by 3 Source ↗Scholar ↗

2021

Designing Soft Pneumatic Actuators for Thumb Movements

Yuanyuan Wang, Shota Kokubu, Zhongchao Zhou, Xinyao Guo, Ya-Hsin Hsueh, Wenwei Yu

RA-L 2021

Studies have developed various types of soft robotic gloves for hand rehabilitation in recent years. Most soft actuators achieved a sufficient thumb flexion assist while lacking opposition support, which requires the coordination of thumb flexion and abduction-adduction. The difficulties for thumb s

Cited by 26 Source ↗Scholar ↗