Abstract

Rehabilitation robotics is one of the major subfields in robotics that is growing rapidly. Neurological disorders, such as stroke, reduce the strength of muscles and the sensation of limbs of a stroke survivor. Soft haptics can be utilized to develop highly compliant soft biofeedback systems that comprise of soft sensors and actuators. Soft sensors are adaptable, conformal and safe for use in devices involving human-machine interaction. This study presents a soft 3D printed resistive force sensor that can be directly manufactured using a low-cost and open-source fused deposition modeling (FDM) 3D printer that uses a commercially available conductive thermoplastic poly(urethane) (TPU). Finite element modeling (FEM) is used to predict accurately the behavior of a single soft resistive sensor under applied mechanical loads. The electrical and mechanical characterization results of the sensor correlate the numerical results with reasonable accuracy. Under an applied mechanical deformation, there is a linear relationship between the output resistance of the sensor and the force generated. This soft force sensor can be tailored to biofeedback systems where it can be implemented and customized using 3D printing.

Full Text
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