Graduate Student Seminar Series
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Presentation Title: Examining and Validating the Integration of Digital Technology for Ankle-Foot Orthosis Registration
Abstract: Ankle-foot deformities can affect an individual’s gait and caused increased pain and discomfort during the activities of daily living. This can significantly affect quality of life and lead to further complications and health-related risks. Custom-made ankle-foot orthotics (AFOs) are widely used in patient care and rehabilitation to improve and restore ankle-foot positioning, support, mobility, and stability. The traditional approach in designing custom-made AFOs relies heavily on the experience and craftsmanship of the orthotist during shape capture, design, and fabrication. Digital workflows in orthotics, including design and fabrication of AFOs, are advancing patient care and rehabilitation by improving the quality and consistency of assistive devices. Recent breakthroughs in digital technology have the potential of transforming the design processes of orthoses by replacing traditional methods. However, there are currently large research-gaps in AFO digital workflows. It remains a challenge to translate the subjective skills of orthotists into the digital realm. Creating a visual representation of manual fabrication methods helps quantify changes in shape. This is often referred to as digital mapping. Registration is the process of digitally overlaying or superimposing two shapes with respect to each other. Consistent and effective registration methods are needed to compare (digitally map) different types of AFO workflows and designs. Current registration methods often require the use of anatomical landmarks as reference points for aligning two shapes. This process is inefficient and tedious. To address this issue, the research objectives are to 1) investigate and validate a suitable registration method for aligning digital AFO models for shape comparison, 2) eliminate the need for manual registration by developing a digital algorithm to streamline the registration process, and 3) utilize the digital algorithm to align models acquired using both traditional and digital shape capture methods.
Supervisor Name: Jan Andrysek
Year of Study: 2
Program of Study: MASc
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