Browsing by Author "Zilevu, Kobla Setor"
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- Human Computer Interaction for Complex Machine LearningZilevu, Kobla Setor (Virginia Tech, 2022-05-09)This dissertation focuses on taking a human-centric approach to utilize human intelligence best to inform machine learning models. More specifically, the complex relationship between the changes in movement functionality to movement quality. I designed and evaluated the Tacit Computable Empowering methodology across two domains: in-home rehabilitation and clinical assessment. My methodology has three main objectives: first, to transform tacit expert knowledge into explicit knowledge. Second, to transform explicit knowledge into a computable framework that machine learning can understand and replicate. Third, synergize human intelligence with computational machine learning to empower, not replace, the human. Finally, my methodology uses assistive interfaces to allow clinicians and machine learning models to draw parallels between movement functionality and movement quality. The results from my dissertation inform researchers and clinicians on how best to create a standardized framework to capture and assess human movement data for embodied learning scenarios
- Interactive Interfaces for Capturing and Annotating Videos of Human MovementZilevu, Kobla Setor (Virginia Tech, 2019-07-11)In this thesis, I describe the iterative service design process I used in identifying and understanding the needs of diverse stakeholders, the development of technologies to support their mutually beneficial needs, and the evaluation of the end-user experience with these technologies. Over three iterative design cycles, the set of identified end-user customers expanded to include the patient, the supervising therapist, the annotating therapist, and other members of the development team. Multiple versions of interactive movement capture and annotation tools were developed as the needs of these stakeholders were clarified and evolved, and the optimal data forms and structures became evident. Interactions between the stakeholders and the developed technologies operating in various environments were evaluated and assessed to help improve and optimize the entire service ecosystem. Results and findings from these three design cycles are being used to direct and shape my ongoing and future doctoral research