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

Matsunaga, Fuko; Oba, Ema; Ke, Ming-Ta; Hsueh, Ya-Hsin; Huang, Shao Ying; Gomez-Tames, Jose; Yu, Wenwei

doi:10.1109/lra.2024.3416073

IEEE Robot. Autom. Lett.

2024

DOI: 10.1109/lra.2024.3416073

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

Fuko Matsunaga,

Ema Oba,

Ming-Ta Ke

et al.

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A Pneumatic Soft Exoskeleton System Based on Segmented Composite Proprioceptive Bending Actuators for Hand Rehabilitation

Li,

Zhang,

Chu

et al. 2024

Biomimetics

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Soft pneumatic actuators/robotics have received significant interest in the medical and health fields, due to their intrinsic elasticity and simple control strategies for enabling desired interactions. However, current soft hand pneumatic exoskeletons often exhibit uniform deformation, mismatch the profile of the interacting objects, and seldom quantify the assistive effects during activities of daily life (ADL), such as extension angle and predicted joint stiffness. The lack of quantification poses challenges to the effective and sustainable advancement of rehabilitation technology. This paper introduces the design, modeling, and testing of pneumatic bioinspired segmented composite proprioceptive bending actuators (SCPBAs) for hand rehabilitation in ADL tasks. Inspired by human finger anatomy, the actuator’s soft-joint–rigid-bone segmented structure provides a superior fit compared to continuous structures in traditional fiber-reinforced actuators (FRAs). A quasi-static model is established to predict the bending angles based on geometric parameters. Quantitative evaluations of predicted joint stiffness and extension angle utilizing proprioceptive bending are performed. Additionally, a soft under-actuated hand exoskeleton equipped with SCPBAs demonstrates their potential in ADL rehabilitation scenarios.

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A Pneumatic Soft Exoskeleton System Based on Segmented Composite Proprioceptive Bending Actuators for Hand Rehabilitation

Li,

Zhang,

Chu

et al. 2024

Biomimetics

View full text Add to dashboard Cite

show abstract

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

Cited by 1 publication

References 24 publications

A Pneumatic Soft Exoskeleton System Based on Segmented Composite Proprioceptive Bending Actuators for Hand Rehabilitation

A Pneumatic Soft Exoskeleton System Based on Segmented Composite Proprioceptive Bending Actuators for Hand Rehabilitation

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