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In this work, a cost-effective, scalable pneumatic silicone actuator array is introduced, designed to dynamically conform to the user’s skin and thereby alleviate localised pressure within a prosthetic socket. The appropriate constitutive models for developing a finite element representation of these actuators are systematically identified, parametrised, and validated. Employing this computational framework, the surface deformation fields induced by 270 variations in soft actuator array design parameters under realistic load conditions are examined, achieving predictive accuracies within 70 µm. The results elucidate how individual design factors influence surface deformation and, consequently, pressure distribution. A novel speckle imaging technique is employed to address the complex non-linear deformations, enabling surface displacement measurements with an accuracy of approximately 40 µm. These measurements confirm that the Ogden N3 model can predict actuator deformation with an accuracy of 16%. These findings elucidate the relationships among actuator geometry, material behaviour, and surface deformation. Although demonstrated in a dynamically reconfigurable socket for transtibial amputees, these insights are readily transferable to other robotics applications that require soft, deformable, load-bearing interfaces. This validated modelling strategy and imaging technique provide a foundation for optimising soft actuator arrays, ultimately improving user comfort and enhancing the functionality of future prosthetic and robotic devices.

Abstract Electrical impedance tomography (EIT) is an imaging method that can be used to image electrical impedance contrasts within various tissues of the body. To support development of EIT measurement systems, a phantom is required that represents the electrical characteristics of the imaging domain. No existing type of EIT phantom combines good performance in all three characteristics of resistivity resolution, spatial resolution, and stability. Here, a novel EIT phantom concept is proposed that uses 3D printed conductive material. Resistivity is controlled using the 3D printing infill percentage parameter, allowing arbitrary resistivity contrasts within the domain to be manufactured automatically. The concept of controlling resistivity through infill percentage is validated, and the manufacturing accuracy is quantified. A method for making electrical connections to the 3D printed material is developed. Finally, a prototype phantom is printed, and a sample EIT analysis is performed. The resulting phantom, printed with an Ultimaker S3, has high reported spatial resolution of 6.9 µm, 6.9 µm, and 2.5 µm for X, Y, and Z axis directions, respectively (X and Y being the horizontal axes, and Z the vertical). The number of resistivity levels that are manufacturable by varying infill percentage is 15 (calculated by dividing the available range of resistivities by two times the standard deviation of the manufacturing accuracy). This phantom construction technique will allow assessment of the performance of EIT devices under realistic physiological scenarios.