人工智能
代表(政治)
机器人
机械手
人工神经网络
计算机视觉
仿人机器人
机械臂
任务(项目管理)
作者
Paulina Kieliba,Danielle Clode,Roni O. Maimon-Mor,Tamar R. Makin
出处
期刊:Science robotics
[American Association for the Advancement of Science (AAAS)]
日期:2021-05-19
卷期号:6 (54): 7935-
被引量:16
标识
DOI:10.1126/scirobotics.abd7935
摘要
Humans have long been fascinated by the opportunities afforded through augmentation. This vision not only depends on technological innovations but also critically relies on our brain's ability to learn, adapt, and interface with augmentation devices. Here, we investigated whether successful motor augmentation with an extra robotic thumb can be achieved and what its implications are on the neural representation and function of the biological hand. Able-bodied participants were trained to use an extra robotic thumb (called the Third Thumb) over 5 days, including both lab-based and unstructured daily use. We challenged participants to complete normally bimanual tasks using only the augmented hand and examined their ability to develop hand-robot interactions. Participants were tested on a variety of behavioral and brain imaging tests, designed to interrogate the augmented hand's representation before and after the training. Training improved Third Thumb motor control, dexterity, and hand-robot coordination, even when cognitive load was increased or when vision was occluded. It also resulted in increased sense of embodiment over the Third Thumb. Consequently, augmentation influenced key aspects of hand representation and motor control. Third Thumb usage weakened natural kinematic synergies of the biological hand. Furthermore, brain decoding revealed a mild collapse of the augmented hand's motor representation after training, even while the Third Thumb was not worn. Together, our findings demonstrate that motor augmentation can be readily achieved, with potential for flexible use, reduced cognitive reliance, and increased sense of embodiment. Yet, augmentation may incur changes to the biological hand representation. Such neurocognitive consequences are crucial for successful implementation of future augmentation technologies.
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