Virtual Tools Based on Medical Imaging and Mechanical Modeling to Optimize the Soft Tissue Envelope in the Transfemoral Residual Limb




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An estimated 185,000 Americans sustain limb amputations every year due to trauma, cancer or vascular diseases such as diabetes. Due to the increased number of people living with obesity and diabetes, the incidences of major upper and lower limb amputations are projected to continue to grow. To improve the quality of life of these individuals such as their abilities for self-care, community integration, employment, and participation in activities of leisure, engineers seek to advance technologies that either improve their abilities or better inform guidelines for their clinical care. These advances in technologies include personalized designs of passive prostheses, intuitive control interfaces of mechanically-active (i.e., robotic) prostheses, and customized and adaptable prosthetic socket solutions, to name a few. With the drive for improved prosthetic technology, it is vital to develop a deeper understanding of how the interface between the assistive device (i.e., the technology) and the human enables or curtails locomotor ability. In these studies, we examine how the mechanical interface between prosthetic legs and the residual (i.e., amputated) limb can be quantitatively assessed and optimized—focusing on techniques that target the limb and its underlying structure independent from the effects of distal components such as prosthetic sockets, knees and feet. Specifically, we focus on assessing and optimizing the soft tissue envelope within the residual limb of individuals with transfemoral amputation using medical imaging, mechanical modeling, and random sampling methods to inform clinical interventions that include surgical recontouring of the limb and its underlying soft tissue. These tools could arm orthopedic and plastic surgeons with quantitative and objective measures when considering the optimal limb “design” for a given individual. This dissertation research contains three Specific Aims that observe (Aim 1), gather data (Aim 2), and inform (Aim 3) how the form of the residual limb and its underlying distribution of soft tissue influence its mechanical properties, and thus its abilities to don a prosthesis.



Engineering, Biomedical