Desain Soft Pneumatic Networks Actuator Untuk Robot Rehabilitasi Jari Tangan Pasca Stroke

Abstract

Stroke is one of the leading causes of hand motor impairment, reducing patients' ability to perform daily activities. One promising solution for rehabilitation is the use of soft pneumatic actuators due to their flexibility, lightweight structure, and safe interaction with the human body. This study aims to investigate the influence of geometrical parameters on the bending and tip force performance of a Soft Pneumatic Networks (PneuNet) actuator and to determine the optimum configuration for index finger rehabilitation. The design parameters include bottom layer thickness, bottom layer distance, and chamber length. The mechanical behavior of RTV-52 silicone rubber was characterized through uniaxial tensile testing and modeled using the first-order Ogden hyperelastic model. Finite Element Method (FEM) simulations were conducted using a Taguchi L9 experimental design, while multi-response optimization was performed using Grey Relational Analysis (GRA). The results indicate that the geometrical parameters significantly influence the bending angle, tip force, stress, strain, and safety factor of the actuator. Based on the GRA results, the PN 5_4 × 8 configuration was identified as the optimum design with the highest Grey Relational Grade (GRG) of 0.702. The validation results demonstrate that the actuator achieves a bending angle of approximately 185°, which satisfies the required Range of Motion (ROM) for the picking motion but has not yet fulfilled the ROM required for grasping motion. Furthermore, the PN 5_4 × 8 configuration exhibits the best tip force performance among all evaluated configurations. Therefore, the proposed actuator has the potential to be applied as a soft actuator for assisting index finger flexion-extension movement in post-stroke rehabilitation devices.