Introduction: : Only 9% of the 2.3 million Americans living with limb loss have upper-extremity devices, with half reporting unmet prosthetic needs due to lengthy fabrication processes requiring multiple fittings (Mitton et al., 2017). Current 3D printed hands rely on isotropic infill patterns and manual CAD adjustments that limit mechanical performance (Park et al., 2024; Siegel et al., 2024). Here, we propose the use of 3D printed metamaterials to create highly functional prosthetics that are also efficiently manufactured. Such prosthetics can aid in medical needs for users, while having further extensions in areas such as military applications where the U.S. Army Research Laboratory prioritizes "print-where-you-fight" prosthetic devices for field deployment (Patel et al., 2024). We developed a parametric workflow combining metamaterial lattice structures with dual-material printing to produce customized prosthetic hands in under 12 hours from anthropometric input to finished device. The system uses automated Python scripting to generate PA12 structural cores with TPU flexible joints, eliminating iterative fitting cycles while meeting Army field deployment requirements (Bustamante et al., 2018; Sun et al., 2021). The process uses computation to customize patient-specific designs and adaptive mechanical properties through engineered metamaterials.
Materials and
Methods: : A Python pipeline was created to input standardized anthropometric measurements to generate parametric hand geometries without individual scanning requirements (Tian et al., 2021). Range of motion is governed by range of motion parameters from literature (Hume et al., 1990). 27 morphological ratios can be input using established parameter methods (Sun et al., 2021) and result in a metamaterial with diamond-truss lattice unit cells with adjustable beam thicknesses (0.8-2.4 mm) to create tunable stiffness from 0.2-4.8 GPa (Al Masud et al., 2025) and compliant actuation (Figure 1).
Further design parameters were input to create hand geometries in Figure 2. Morphological ratios were informed by anthropometric validation that used published datasets from the 2012 US Army Anthropometric Survey (ANSUR II) containing 93 dimensional measurements for over 6,000 personnel (Gordon et al., 2014) and NASA anthropometric data for astronaut populations (Francisco, 2025). Metamaterials were initially tested through tensile testing to characterize effective properties such as elastic modulus and yield stress to inform computational modeling results.
Based on the mechanical data, a parametric graphical user interface (GUI) was developed to facilitate rapid design customization for field deployment scenarios (Figure 3). This GUI manages 48 parameters, supports multi-objective optimization, provides real-time feedback, and directly integrates with multi-material fused deposition modeling printing for rapid design customization and fabrication in the field. Prosthetic hands were printed on an Ultimaker S3 dual-extrusion system using 245°C/70°C for PA12 and 230°C/40°C for TPU with 0.16mm layer height. Post-processing involved support removal and TPU stringing cleanup (Bustamante et al., 2018).
Results, Conclusions, and Discussions:: Results The python optimization workflow generated a prosthetic hand geometry in about 17 seconds, excluding outlying generations prompting programming changes. The generation was conducted using an Intel Core Ultra 9 185H vPro Enterprise (Al Masud et al., 2025). The total anthropometric-input-to-print time averaged about 6 hours, thereby eliminating the need for multi-session fitting requirements (Park et al., 2024). The metamaterial core in Figure 1 (black regions) reduces design and fabrication time by eliminating solid infill bodies. The complete input to print workflow, comprising importation of U.S. Army anthropometric data into CAD via Python, model generation, slicing, and Ultimaker printing, was executed and timed over three independent trials. The user interface is enabled so that the metamaterial core can be instantly generated and is shown in Figure 3's GUI. The Layout of the GUI is organized in quadrants with the bottom left for human factors input, the bottom right for material and fabrication input, graphical data in the top left quadrant, and the top right quadrant displays the generated STL file.
Conclusions This workflow enables the automated creation of prosthetic hands using computational design. It transforms user-specific data into personalized, functional prosthetics. The metamaterial lattice architecture allows varied mechanical properties through density gradients and tunable stiffness zones, providing flexibility at joints and rigidity in load-bearing areas. The computational design system leverages parametric modeling to generate patient-specific geometries while metamaterial structures eliminate multi-component assembly through single-print manufacturing. The Python-based computational framework accelerates personalization by automating the design pipeline.
Discussion Compared to existing 3D printed prosthetics that rely on manual CAD adjustment (Park et al., 2024), this parametric approach offers significant time savings and standardization potential. Primary limitations include the need for extended durability and grip testing beyond basic actuation evaluation, optimization of lattice parameters for specific functional requirements, and validation across broader anthropometric populations. TPU stringing and interface quality between materials requires continued post-processing refinement. Future work should focus on long-term mechanical testing, expanded validation with diverse hand geometries, and integration with existing military supply chains.
Acknowledgements and/or References (Optional):: Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-24-2-0208. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.
