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首页> 外文期刊>International journal of applied mechanics >A WiSARD Network Approach for a BCI-Based Robotic Prosthetic Control
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A WiSARD Network Approach for a BCI-Based Robotic Prosthetic Control

机译：基于BCI的机器人假肢控制的智慧网络方法

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摘要

There are significant research efforts underway in the area of automatic robotic-prosthesis control based on brain-computer interface aiming at understanding how neural signals can be used to control these assistive devices. Although these approaches have made significant progresses in the ability to control robotic manipulators, the realization of portable and easy of use solutions is still an ongoing research endeavor. In this paper, we propose a novel approach relying on the use of (i) a Weightless Neural Network-based classifier, whose design lends itself to an easy hardware implementation; (ii) a robotic hand designed in order to fit with the main requirements of these kind of technologies (such as low cost, high performance, lightness, etc.) and (iii) a non-invasive light-weight and easy-donning EEG-helmet in order to provide a portable controller interface. The developed interface is connected to a robotic hand for controlling open/close actions. The preliminary results for this system are promising in that they demonstrate that the proposed method achieves similar performance with respect to state-of-the-art classifiers by contemporaneously representing a most suitable and practicable solution due to its portability on hardware devices, which will permit its direct implementation on the helmet board.
机译：基于脑电脑界面的自动机器人假体控制领域有显着的研究工作，旨在了解神经信号如何用于控制这些辅助设备的方式。虽然这些方法在控制机器人操纵器的能力方面取得了重大进展，但仍然是持续的研究努力的便携式和易于使用的解决方案。在本文中，我们提出了一种依赖于（i）一种无重的神经网络的分类器的新方法，其设计为简单的硬件实现提供了一种; （ii）设计了一个机器人手，以适应这些技术的主要要求（例如低成本，高性能，轻盈等）和（iii）一种非侵入性轻量级和易于无侵入的脑电图 - 为提供便携式控制器接口。开发的接口连接到机器人手，用于控制打开/关闭动作。该系统的初步结果在于，他们表明，由于其在硬件设备上的便携性，所提出的方法通过同时代表最合适的和可行的解决方案来实现相似的性能。它在头盔板上的直接实施。

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