Arunachalam, Anjana Gayathri2024-09-122024-09-122024-08https://unbscholar.lib.unb.ca/handle/1882/38108Current myoelectric prosthesis control methods lack personalized tuning based on individual user preferences leading to potentially suboptimal user performance. This thesis introduces a model for personalized myoelectric prosthetic control, integrating user preferences into device dynamics through an optimization approach. Drawing on principles of computational motor control, evolutionary multi-objective optimization, and control theory, the model identifies optimal device dynamic parameters based on user preferences for effort, movement time, and reliability. Results from our simulated prosthesis model suggest that customized prosthetic devices could appreciably improve movement outcomes compared to conventional devices. This study provides a foundation for intuitive and effective prosthetic device control. These improvements may have potential applications beyond prosthesis including various human-machine interfaces.xvi, 101electronicenhttp://purl.org/coar/access_right/c_abf2master thesisSensinger, JonathonEnglehart, KevinElectrical and Computer Engineering