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Multimodal System for Training at Distance in a Virtual or Augmented Reality Environment for Users of Electric-Powered Wheelchairs

机译:用于电动轮椅使用者的虚拟或增强现实环境中的距离训练的多模式系统

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Recently, important progresses for controlling electric-powered wheelchair were made for people with disabilities. However, a significant amount of people affected by severe physical disabilities still cannot take advantage of autonomous mobility. For those situations, the use of biological signals to control the assisted environment emerges as a possible solution. In this scenario, the act of driving an electric-powered wheelchair without training can appear as a serious safety risk, which can be solved by using a virtual driving simulator. Nevertheless, when using biomedical signals as commands (eg.: brain-computer interface - BCIs), it is not possible to ensure a continuous and reliable control of the wheelchair due to state of the art of this technology, being necessary to associate it with features such as semi-automatic obstacle detection or contour, which are difficult and costly to reproduce. Thus, it is interesting to offer to new wheelchair's users the possibility of using a simulator that allows them to learn to drive the wheelchair prototype at distance, making use of appropriated telematics techniques, which is the proposal of this work. This research joints complementary skills from the following universities: Federal University of Amazonas (UFAM), Federal University of Espirito Santo (UFES) and Federal University of Uberlandia (UFU), with the collaboration of researches from the University of Lorraine (UL) in Metz-France.
机译:最近,为残疾人制作了控制电动轮椅的重要进展。然而,受严重身体残疾影响的大量人仍然不能利用自主流动性。对于那些情况,使用生物信号来控制辅助环境作为可能的解决方案。在这种情况下,在不培训的情况下驾驶电动轮椅的行为可能是一个严重的安全风险,这可以通过使用虚拟驾驶模拟器来解决。然而,当使用生物医学信号作为命令时(例如:脑电脑接口 - BCIS),由于本技术的艺术状态,无法确保对轮椅的连续可靠控制,所以必须与之相关联诸如半自动障碍物检测或轮廓等特征,其难以且昂贵。因此,为新的轮椅的用户提供了使用模拟器的可能性,可以使用允许它们在距离驾驶轮椅原型的可能性,利用拨款的远程技术技术,这是这项工作的提议。本研究联合互补技能来自以下大学的互补技能:亚马逊联邦亚马逊(UFAM),联邦Espirito Santo(UFES)和UFUS联邦(UFU)的联邦大学(UFU),并在梅斯洛林大学(UL)的合作合作-法国。

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