Mechanical Engineering - Theses
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ItemHuman learning in visuomotor field: modeling and experimental studies( 2015)As the saying “practice makes perfect” goes, humans have the ability to learn from experiences. Understanding how humans learn or re-learn tasks/skills have drawn lot attentions from evolutionary biology to cognitive science to neurobiology. Moreover, it would play an important role in fully exploring the learning ability to recover the human motor functions for stroke patients, leading to better or more efficient therapy plans and novel apparatus to aid therapists in recovering patients. As learning may be viewed as a process, concepts of “control” and “feedback” have been successfully used to provide reasonable explanations of learning behaviours observed in many carefully designed experiments for healthy subjects. This work attempts to understand whether humans use a common strategy to learn a task when provided with different environments. To do this, this work aims at 1) Designing human-involved experiments to find out whether humans exhibit different learning behaviours in the same task and environment by different training strategies; 2) Building a computational model to capture the major characteristic of human learning observed from the experiments. The experimental results have shown that under different training strategies, humans will respond differently for the same task and environment, indicating that the training strategies play a crucial role in learning tasks and skills. Quantitative computational model based on novel iterative learning control laws are constructed to propose the underlying mechanism of the different strategies and to provide reasoning for the use of such strategies by humans.