一种前馈神经网络轮椅驾驶操纵杆

Y. Rabhi, M. Mrabet, F. Fnaiech, P. Gorce
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引用次数: 11

摘要

残疾人士,如患有IMC病或帕金森病的人,在操作标准操纵杆时遇到困难,因为他们的震颤程度不同或在移动手臂时遇到困难。这项工作的目的是设计一种适合每个患者的新的神经操纵杆,允许克服这些困难或不完整或错误的动作,以达到最大的安全性。神经网络操纵杆系统的设计是基于训练神经网络对标准操纵杆进行逆建模。经过训练的神经网络随后连接到操纵杆的输出。然后,整个系统用于控制轮椅的所有直流电机和设备。然后使用残疾人的模拟和实验真实数据来突出所设计系统的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A feedforward neural network wheelchair driving joystick
People with disabilities such as those affected by IMC disease or Parkinson's disease have difficulties in operating standard joystick due to their different levels of tremors or difficulties encountered when moving their arms. The objective of this work is to design a new neural joystick suitable for each patient allowing overcoming these difficulties or incomplete or erroneous actions, in order to reach maximum security. The design of the neural network joystick system is based on training a neural network to model the inverse of the standard joystick. The trained resulting neural network is then connected to output of the joystick. The overall system is then used to control all the DC motors and devices of the wheelchair. Simulations and experimental real data recorded on disabled persons are then used to highlight the effectiveness of the designed system.
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