期刊
IEEE TRANSACTIONS ON ROBOTICS
卷 23, 期 5, 页码 919-926出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TRO.2007.907481
关键词
human factors; intelligent tutoring systems; man-machine systems; robot tactile systems
类别
When humans learn a new motor skill from a teacher, they learn using multiple channels. They receive high level information aurally about the skill, visual information about how another performs the skill, and at times, tactile information from the teacher's physical guidance. This research proposes a novel approach where the student receives real-time tactile feedback, simultaneously over all joints, delivered through a wearable robotic system. This tactile feedback can supplement the visual or auditory feedback from the teacher. Our results using a 5-DOF robotic suit show a 27% improvement in accuracy while performing the target motion, and an accelerated learning rate of up to 23%. We report both of these results with high statistical significance (p <= 0.01). This research is intended for use in a diverse set of applications including sports training, motor rehabilitation after neurological damage, dance, postural retraining for health, and many others. We call this system tactile interaction for kinesthetic learning (TIKL).
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