Hybart Rachel L, Ferris Daniel P
IEEE Trans Neural Syst Rehabil Eng. 2023;31:657-668. doi: 10.1109/TNSRE.2022.3229563. Epub 2023 Feb 2.
Research on embodiment of objects external to the human body has revealed important information about how the human nervous system interacts with robotic lower limb exoskeletons. Typical robotic exoskeleton control approaches view the controllers as an external agent intending to move in coordination with the human. However, principles of embodiment suggest that the exoskeleton controller should ideally coordinate with the human such that the nervous system can adequately model the input-output dynamics of the exoskeleton controller. Measuring embodiment of exoskeletons should be a necessary step in the exoskeleton development and prototyping process. Researchers need to establish high fidelity quantitative measures of embodiment, rather than relying on current qualitative survey measures. Mobile brain imaging techniques, such as high-density electroencephalography, is likely to provide a deeper understanding of embodiment during human-machine interactions and advance exoskeleton research and development. In this review we show why future exoskeleton research should include quantitative measures of embodiment as a metric of success.
对人体外部物体具身化的研究揭示了有关人类神经系统如何与机器人下肢外骨骼相互作用的重要信息。典型的机器人外骨骼控制方法将控制器视为意图与人类协调运动的外部主体。然而，具身化原理表明，外骨骼控制器理想情况下应与人类协调，以便神经系统能够充分模拟外骨骼控制器的输入输出动态。测量外骨骼的具身化应该是外骨骼开发和原型制作过程中的必要步骤。研究人员需要建立具身化的高保真定量测量方法，而不是依赖当前的定性调查方法。移动脑成像技术，如高密度脑电图，可能会在人机交互过程中提供对具身化更深入的理解，并推动外骨骼的研发。在本综述中，我们展示了为什么未来的外骨骼研究应将具身化的定量测量作为成功的衡量标准。
