Browsing by Author "Haghiashtiani, Ghazaleh"

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    3D Printing of Soft Electromechanical Transducers and Their Application in Development of Patient-Specific Organ Models
    (2020-01) Haghiashtiani, Ghazaleh
    The ability to mimic nature and biological systems has revolutionized various fields and has inspired a plethora of scientific discoveries to solve human problems. Medicine is among the areas that has vastly benefited from bio-inspired innovations, such as the gecko-inspired adhesive and parasitic worm-inspired microneedle. Driven by the fact that medical errors are among the leading causes of death, several efforts have been focused to create phantoms that mimic the actual patients’ organ with the main purpose of enhancing preoperational planning and surgical outcomes, as well as reducing the risk of intraoperative errors and postoperative complications. Over the past decade, 3D printing technologies have played an important role in fabrication of patient-specific organ phantoms, however, despite being anatomically correct, these 3D printed organ models mostly lack the precise mimicry of the sense and mechanical properties of the biological tissue of interest. In addition, they lack advanced functionalities, such as tactile sensing, to provide quantitative feedback during organ handling which can be a valuable metric in different surgical interventions or for training purposes. This dissertation aims at addressing these two limitations by conducting an investigation at the intersection of soft biomimicking electroactive, and tissue-like material systems and electromechanical transducer design coupled with multi-material, extrusion-based 3D printing process, for primary applications in development of smart, patient-specific organ models. Specifically, the design and development of (i) a tunable silicone-based material system with tissue-like mechanical properties compatible with direct ink writing 3D printing process, (ii) soft electromechanical actuators and sensors based on the biomimicking hydrogel-elastomer hybrid material system, and (iii) coalescence of these concepts for fabrication of patient-specific organ models with integrated functionalities were presented. It is envisioned that these organ models can augment the current practices in a gamut of medical applications, including preoperative planning, clinical training, patient education, and development of next-generation medical devices with the end goal of enhancing surgical outcomes, reducing medical errors, and improving patient safety. In addition, on a long-term basis, the outcomes of this work could contribute to the incorporation of cell-seeded structures into the organ models, thus setting the stage for development of dynamic bionic organs.
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    Applying the DMAIC method for developing a PVDF matrix composite for integrated structural load sensing
    (2014-08) Haghiashtiani, Ghazaleh
    This thesis introduces a new carbon fiber reinforced composite structure that uses polyvinylidene difluoride (PVDF) as the matrix material instead of the polymers that are typically used. The piezoelectric properties of PVDF enable the proposed composite material to act both as the structure and as an integrated sensor for in situ structural health monitoring. In this study, the fabrication process, the polarization process, and the mechanical and piezoelectric characterization of the composite structure are discussed. In addition, the DMAIC method was applied to the polarization process in order to identify the factors affecting the degree of polarization. As part of the improve phase, a 23 factorial design of experiment (DOE) was performed to investigate the optimal conditions of the identified factors for the polarization process. Lastly, the future market potential of the proposed composite structure is explored by applying strategic market analysis tools including SWOT analysis, Ansoff's matrix, and technology S-curve.
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    Supporting data for "3D printed electrically-driven soft actuators"
    (2020-06-09) Haghiashtiani, Ghazaleh; Habtour, Ed; Park, Sung-Hyun; Gardea, Frank; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    Soft robotics is an emerging field enabled by advances in the development of soft materials with properties commensurate to their biological counterparts, for the purpose of reproducing locomotion and other distinctive capabilities of active biological organisms. The development of soft actuators is fundamental to the advancement of soft robots and bio-inspired machines. Among the different material systems incorporated in the fabrication of soft devices, ionic hydrogel–elastomer hybrids have recently attracted vast attention due to their favorable characteristics, including their analogy with human skin. Here, we demonstrate that this hybrid material system can be 3D printed as a soft dielectric elastomer actuator (DEA) with a unimorph configuration that is capable of generating high bending motion in response to an applied electrical stimulus. We characterized the device actuation performance via applied (i) ramp-up electrical input, (ii) cyclic electrical loading, and (iii) payload masses. A maximum vertical tip displacement of 9.78 ± 2.52 mm at 5.44 kV was achieved from the tested 3D printed DEAs. Furthermore, the nonlinear actuation behavior of the unimorph DEA was successfully modeled using an analytical energetic formulation and a finite element method (FEM).
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    Supporting data for "3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors"
    (2020-05-22) Qiu, Kaiyan; Zhao, Zichen; Haghiashtiani, Ghazaleh; Guo, Shuang-Zhuang; He, Mingyu; Su, Ruitao; Zhu, Zhijie; Bhuiyan, Didarul B; Murugan, Paari; Meng, Fanben; Park, Sung Hyun; Chu, Chih-Chang; Ogle, Brenda M; Saltzman, Daniel A; Konety, Badrinath R; Sweet, Robert M; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    The data set includes the experimental data and the corresponding MRI stereolithography (STL) file supporting the results reported in Kaiyan Qiu; Zichen Zhao; Ghazaleh Haghiashtiani; Shuang-Zhuang Guo; Mingyu He; Ruitao Su; Zhijie Zhu; Didarul B. Bhuiyan; Paari Murugan; Fanben Meng; Sung Hyun Park; Chih-Chang Chu; Brenda M. Ogle; Daniel A. Saltzman; Badrinath R. Konety; Robert M. Sweet; Michael C. McAlpine. 3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors. Adv. Mater. Technol. 2018, 3, 1700235. The design and development of novel methodologies and customized materials to fabricate patient-specific 3D printed organ models with integrated sensing capabilities could yield advances in smart surgical aids for preoperative planning and rehearsal. Here, we demonstrate 3D printed prostate models with physical properties of tissue and integrated soft electronic sensors using custom-formulated polymeric inks. The models show high quantitative fidelity in static and dynamic mechanical properties, optical characteristics, and anatomical geometries to patient tissues and organs. The models offer tissue-like tactile sensation and behavior and thus can be used for the prediction of organ physical behavior under deformation. The prediction results show good agreement with values obtained from simulations. The models also allow the application of surgical and diagnostic tools to their surface and inner channels. Finally, via the conformal integration of 3D printed soft electronic sensors, pressure applied to the models with surgical tools can be quantitatively measured.
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    Supporting data for "3D printed patient-specific aortic root models with internal sensors for minimally invasive applications"
    (2020-06-09) Haghiashtiani, Ghazaleh; Qiu, Kaiyan; Sanchez, Jorge D Zhingre; Fuenning, Zachary J; Nair, Priya; Ahlberg, Sarah E; Iaizzo, Paul A; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    Minimally invasive surgeries have numerous advantages, yet complications may arise from limited knowledge about the anatomical site targeted for the delivery of therapy. Transcatheter aortic valve replacement (TAVR) is a minimally invasive procedure for treating aortic stenosis. Here, we demonstrate multi-material 3D printing of patient-specific soft aortic root models with internally-integrated electronic sensor arrays that can augment testing for TAVR preprocedural planning. We evaluated the efficacies of the models by comparing their geometric fidelities with postoperative data from patients, as well as their in vitro hemodynamic performances in cases with and without leaflet calcifications. Furthermore, we uniquely demonstrated that internal sensor arrays can facilitate the optimization of bioprosthetic valve selections and in vitro placements via mapping of the pressures applied on the critical regions of the aortic anatomies. Such models may pave new avenues for mitigating the risks of postoperative complications, as well as facilitating the development of next-generation medical devices.