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A soft, synergy-based robotic glove for grasping assistance

Ryan Alicea, Michele Xiloyannis, Domenico Chiaradia, Michele Barsotti, Antonio Frisoli, Lorenzo Masia

发表年份
2021
引用次数
35
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摘要

This paper presents a soft, tendon-driven, robotic glove designed to augment grasp capability and provide rehabilitation assistance for postspinal cord injury patients. The basis of the design is an underactuation approach utilizing postural synergies of the hand to support a large variety of grasps with a single actuator. The glove is lightweight, easy to don, and generates sufficient hand closing force to assist with activities of daily living. Device efficiency was examined through a characterization of the power transmission elements, and output force production was observed to be linear in both cylindrical and pinch grasp configurations. We further show that, as a result of the synergy-inspired actuation strategy, the glove only slightly alters the distribution of forces across the fingers, compared to a natural, unassisted grasping pattern. Finally, a preliminary case study was conducted using a participant suffering from an incomplete spinal cord injury (C7). It was found that through the use of the glove, the participant was able to achieve a 50% performance improvement (from four to six blocks) in a standard Box and Block test.

关键词

GRASPWired gloveActuatorComputer scienceSimulationBlock (permutation group theory)UnderactuationRobotArtificial intelligenceMathematics

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