轮椅模拟游戏,训练严重残疾人士

Oberdan Pinheiro, L. Alves, M. Romero, Josemar R. de Souza
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引用次数: 30

摘要

患有运动和神经障碍的人对身体的某些部位几乎没有控制力,所以他们走路很困难。基于辅助技术的解决方案的开发,专门为有严重运动障碍的人提供可达性和流动性,智能轮椅就是这类技术的一个例子。然而,如果没有适当的训练,它的使用可能是危险的,一个轮椅模拟器游戏可以是一个很好的工具,训练严重残疾的人。脑电图信号可以用作大脑和智能轮椅之间通信的信息源。这项研究旨在开发一种计算机模型来对脑电图信号进行分类,并利用左右手腕、手腕和双脚的运动图像来控制虚拟轮椅。通过BCI2000系统捕获的eegmidb数据库- EEG Motor Movement/Imagery Dataset获取脑电图信号,并使用10个个体的脑电图信号样本对模型进行验证。所使用的技术很有前途,使其在脑机接口控制的智能轮椅的三维模拟环境中使用成为可能。
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Wheelchair simulator game for training people with severe disabilities
People with motor and neurological impairments have little control over parts of their bodies, so they have great difficulty in walking. The development of solutions based on assistive technology dedicated to people with severe motor disabilities can provide accessibility and mobility, the intelligent wheelchair is an example of this type of technology. However, its use without proper training can be dangerous, a wheelchair simulator games can be a good tool for training people with severe disabilities. The EEG signals can be used as a source of information that allows communication between the brain and an intelligent wheelchair. This research aimed to develop a computer model to categorize electroencephalogram signals and control a virtual wheelchair using motor imagery of the left and right wrists, both wrists and both feet. Signs of electroencephalogram were acquired through the eegmmidb database — EEG Motor Movement/Imagery Dataset, captured by the BCI2000 system, and electroencephalogram signal samples from 10 individuals were used to validate the model. The techniques used are promising, making possible its use in three-dimensional simulation environments for intelligent wheelchair controlled by a brain-computer interface.
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