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Abstract
This paper presents a methodology for modelling expert gestural performances in wheel-throwing pottery. The approach is based on building an operational model that describes how expert gestures are performed, taking also into consideration relationships between different parts of the body. This model is estimated using state-space estimation methodology and its predictive performance is evaluated using system dynamic simulation. Moreover, the confidence bounds derived of the expert gesture performance in wheel-throw pottery are computed. They could be used as benchmarks in real-time experiments in order to generate the appropriate feedback for sensorimotor learning of gestures.
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