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Replicating human brain mechanisms towards balancing

机译:复制人脑机制以达到平衡

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Understanding the performance of the human brain to stabilize the body remains an open fundamental research question. In this article, we study the hypothesis of internal model of the Central Nervous System (CNS) by a novel proposed architecture based on a recurrent neural network. The overall objective of the article and the main contribution stems from demonstrating the capability of replicating the balancing mechanisms of the brain by training the proposed bio-inspired network architecture with human balancing data and in the sequel applying the resulting control structure for controlling a single link inverted pendulum. Towards this direction, the body kinetics and kinematics measurements of forty-five subjects during upright stance trails were collected and utilized for training the proposed neural network. The efficacy of the proposed scheme will be proven through multiple simulation results with a single link inverted pendulum, where it will be demonstrated that the brain-inspired control scheme achieves a proper balance. Keywords: Internal model, recurrent neural network, human motor control, postural control.
机译:理解人脑稳定身体的性能仍然是一个悬而未决的基础研究问题。在本文中,我们通过基于递归神经网络的新颖架构来研究中枢神经系统(CNS)内部模型的假设。本文的总体目标和主要贡献来自于通过用人类平衡数据训练拟议的生物启发式网络体系结构并随后应用由此产生的控制结构来控制单个链接来证明复制大脑平衡机制的能力。倒立摆。朝着这个方向,收集了四十五名受试者在直立姿态时的身体动力学和运动学测量结果,并将其用于训练所提出的神经网络。该方案的有效性将通过单连杆倒立摆的多个仿真结果得到证明,其中将证明大脑启发性控制方案达到了适当的平衡。关键字:内部模型,递归神经网络,人体运动控制,姿势控制。

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