2021年世界机器人大赛:无校准SSVEP中BCI控制机器人比赛获胜方法概述

Rui Bian, Dongrui Wu
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引用次数: 3

摘要

稳态视觉诱发电位(SSVEP)以其高的信息传递率成为近年来最受欢迎的脑电图范式之一。已经提出了几种方法来提高SSVEP的性能。在基于ssvep的脑机接口系统中,无校准场景非常重要,因为受试者是第一次使用该系统。在2021年世界机器人大赛BCI控制机器人大赛的SSVEP竞赛(无标定)中,参赛团队提出了几种有效的无标定算法框架。本文介绍了决赛前五名队伍在算法中使用的方法。最后五个科目的成绩证明了方法的有效性。本文讨论了每种方法在无校准情况下提高系统性能的有效性,并给出了如何在实际系统中使用这些方法的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overview of the winning approaches in BCI Controlled Robot Contest in World Robot Contest 2021: Calibration-free SSVEP
Recently, steady-state visual evoked potential (SSVEP) has become one of the most popular electroencephalography paradigms due to its high information transfer rate. Several approaches have been proposed to improve the performance of SSVEP. The calibration-free scenario is significant in SSVEP-based brain–computer interface systems, where the subject is the first time to use the system. The participating teams proposed several effective calibration-free algorithm frameworks in the SSVEP competition (calibration-free) of the BCI Controlled Robot Contest in World Robot Contest 2021. This paper introduces the approaches used in the algorithms of the top five teams in the final. The results of the five subjects in the final proved the effectiveness of the approaches. This paper discusses the effectiveness of each approach in improving the system performance in the calibration-free scenario and gives suggestions on how to use these approaches in a real-world system.
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