Low-cost sensor-integrated 3D-printed personalized prosthetic hands for children with amniotic band syndrome: A case study in sensing pressure distribution on an anatomical human-machine interface (AHMI) using 3D-printed conformal electrode arrays.

Interfacing anatomically conformal electronic components, such as sensors, with biology is central to the creation of next-generation wearable systems for health care and human augmentation applications. Thus, there is a need to establish computer-aided design and manufacturing methods for producing personalized anatomically conformal systems, such as wearable devices and human-machine interfaces (HMIs). Here, we show that a three-dimensional (3D) scanning and 3D printing process enabled the design and fabrication of a sensor-integrated anatomical human-machine interface (AHMI) in the form of personalized prosthetic hands that contain anatomically conformal electrode arrays for children affected by amniotic band syndrome, a common birth defect. A methodology for identifying optimal scanning parameters was identified based on local and global metrics of registered point cloud data quality. This method identified an optimal rotational angle step size between adjacent 3D scans. The sensitivity of the optimization process to variations in organic shape (i.e., geometry) was examined by testing other anatomical structures, including a foot, an ear, and a porcine kidney. We found that personalization of the prosthetic interface increased the tissue-prosthesis contact area by 408% relative to the non-personalized devices. Conformal 3D printing of carbon nanotube-based polymer inks across the personalized AHMI facilitated the integration of electronic components, specifically, conformal sensor arrays for measuring the pressure distribution across the AHMI (i.e., the tissue-prosthesis interface). We found that the pressure across the AHMI exhibited a non-uniform distribution and became redistributed upon activation of the prosthetic hand's grasping action. Overall, this work shows that the integration of 3D scanning and 3D printing processes offers the ability to design and fabricate wearable systems that contain sensor-integrated AHMIs.

Programming of Multicomponent Temporal Release Profiles in 3D Printed Polypills via Core-Shell, Multilayer, and Gradient Concentration Profiles.

Additive manufacturing (AM) appears poised to provide novel pharmaceutical technology and controlled release systems, yet understanding the effects of processing and post-processing operations on pill design, quality, and performance remains a significant barrier. This paper reports a study of the relationship between programmed concentration profile and resultant temporal release profile using a 3D printed polypill system consisting of a Food and Drug Administration (FDA) approved excipient (Pluronic F-127) and therapeutically relevant dosages of three commonly used oral agents for treatment of type 2 diabetes (300-500 mg per pill). A dual-extrusion hydrogel microextrusion process enables the programming of three unique concentration profiles, including core-shell, multilayer, and gradient structures. Experimental and computational studies of diffusive mass transfer processes reveal that programmed concentration profiles are dynamic throughout both pill 3D printing and solidification. Spectrophotometric assays show that the temporal release profiles could be selectively programmed to exhibit delayed, pulsed, or constant profiles over a 5 h release period by utilizing the core-shell, multilayer, and gradient distributions, respectively. Ultimately, this work provides new insights into the mass transfer processes that affect design, quality, and performance of spatially graded controlled release systems, as well as demonstrating the potential to create disease-specific polypill technology with programmable temporal release profiles.