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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:在电动轮椅使用者的虚拟或增强现实环境中远距离训练的多模式系统

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Abstract: 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:摘要:最近,残疾人电动轮椅控制取得了重要进展。但是,仍有大量受到严重肢体残疾影响的人仍然无法利用自动出行。对于那些情况,使用生物信号来控制辅助环境是一种可能的解决方案。在这种情况下,未经培训就驾​​驶电动轮椅的行为可能会带来严重的安全隐患,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:脑机接口-BCI),由于该技术的最新水平,无法确保对轮椅的连续和可靠控制,因此必须将轮椅与诸如半自动障碍物检测或轮廓之类的特征很难复制且成本高昂。因此,为新轮椅使用者提供一种使用模拟器的可能性很有趣,该模拟器使他们能够学习使用适当的远程信息处理技术来远距离驾驶轮椅原型,这是这项工作的建议。这项研究结合了以下大学的互补技能:亚马逊大学(UFAM),圣埃斯皮里图联邦大学(UFES)和乌伯兰迪亚联邦大学(UFU),以及梅斯洛林大学(UL)的研究成果-法国。

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