Towards quantifying upper-arm rehabilitation metrics for children through interaction with a humanoid robot
Brooks, Douglas A.
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The objective of this research effort is to further rehabilitation techniques for children by developing and validating the core technologies needed to integrate therapy instruction with child-robot play interaction in order to improve upper-arm rehabilitation. Using computer vision techniques such as Motion History Imaging (MHI), Multimodal Mean, edge detection, and Random Sample Consensus (RANSAC), movements can be quantified through robot observation. Also incorporating three-dimensional data obtained via an infrared projector coupled with a Principle Component Analysis (PCA), depth information can be utilized to create a robust algorithm. Finally, utilizing prior knowledge regarding exercise data, physical therapeutic metrics, and novel approaches, a mapping to therapist instructions can be created allowing robotic feedback and intelligent interaction.