Information Feedback for Human Motor Skill Transferring System Using Augmented Reality

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This paper presents the study and development of information feedback for human motor skill transferring system. The proposed system has an ability of capturing the demonstrator’s bimanual movement using Kinect which is the Microsoft’s sensing device. Then, the spatial and temporal data of the recorded movement will be encoded into the probabilistic model. When the learner wants to learn the demonstrator’s movement, the reproduced trajectory will be retrieved from the encoded model. After that, the augmented information guidance which is in the form of computer graphics using augmented reality technique will be presented to the learner during the practicing process. A virtual music performance is selected as the case study of transferring the demonstrator skill to the novice. The performance of proposed system guidance on the human motor skill transferring will be investigated. The experimental results indicate that augmented visual feedback leads to reducing the average position error of the novice’s movement with 67.2%. Moreover, 75% of the participants can improve their movement accuracies after being trained with augmented system guidance.

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603-610

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August 2016

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