在 VR 中进行运动想象训练前的阿凡达体现不会影响诱发的事件相关非同步化:一项试点研究

IF 3.2 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING Frontiers in virtual reality Pub Date : 2024-01-08 DOI:10.3389/frvir.2023.1265010
Katarina Vagaja, Klaus Linkenkaer-Hansen, Athanasios Vourvopoulos
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引用次数: 0

摘要

运动图像脑机接口(MI-BCI)有望改善神经系统疾病患者的运动功能。其有效性取决于患者生成可靠的与运动图像相关的脑电图(EEG)模式的能力,这可能会受到神经反馈质量的影响。虚拟现实(VR)由于能够诱导本体感(SoE),使人将虚拟身体视为自己的身体,因此已成为增强本体感反馈的一种有前途的工具。尽管之前的研究已经强调了SoE在提高移动智能技能和BCI性能方面的重要性,但迄今为止,还没有任何研究成功地分离或操纵了移动智能训练前VR中的SoE,这使我们对体现在移动智能-BCI中的引物效应的确切作用的理解出现了空白。在本研究中,我们旨在研究虚拟 SoE 作为虚拟化身体现的引子,在 MI 训练前进行评估,是否能增强 MI 诱导的脑电图模式。为此,我们将 26 名健康参与者分为两组:化身组和非化身组,化身组在接受基于 VR 的 MI 训练之前与化身一起体验 SoE;非化身组在接受相同的 MI 训练之前不进行化身阶段,作为对照组。我们分析了体现的主观测量结果、感觉运动节律的事件相关不同步(ERD)功率、ERD 的侧化以及离线分类 BCI 的准确性。虽然体现阶段有效地诱导了体现组的 SoE,但两组均表现出相似的 MI 诱导的 ERD 模式和 BCI 分类准确性。这表明,在多元智能训练之前诱导 SoE 可能不会对训练结果产生重大影响。相反,在多元智能训练过程中融入虚拟现实反馈本身似乎就足以诱导适当的ERD,这一点已为之前的研究所证实。
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Avatar embodiment prior to motor imagery training in VR does not affect the induced event-related desynchronization: a pilot study
Motor-imagery brain-computer interfaces (MI-BCIs) have the potential to improve motor function in individuals with neurological disorders. Their effectiveness relies on patients’ ability to generate reliable MI-related electroencephalography (EEG) patterns, which can be influenced by the quality of neurofeedback. Virtual Reality (VR) has emerged as a promising tool for enhancing proprioceptive feedback due to its ability to induce a sense of embodiment (SoE), where individuals perceive a virtual body as their own. Although prior research has highlighted the importance of SoE in enhancing MI skills and BCI performance, to date, no study has successfully isolated nor manipulated the SoE in VR before MI training, creating a gap in our understanding of the precise role of the priming effect of embodiment in MI-BCIs. In this study, we aimed to examine whether the virtual SoE when induced, as priming of avatar embodiment, and assessed before MI training, could enhance MI-induced EEG patterns. To achieve this, we divided 26 healthy participants into two groups: the embodied group, which experienced SoE with an avatar before undergoing VR-based MI training, and the non-embodied group, which underwent the same MI training without a prior embodiment phase, serving as a control. We analyzed subjective measures of embodiment, the event-related desynchronization (ERD) power of the sensorimotor rhythms, lateralization of ERD, and offline classification BCI accuracy. Although the embodiment phase effectively induced SoE in the embodied group, both groups exhibited similar MI-induced ERD patterns and BCI classification accuracy. This suggests that the induction of SoE prior to MI training may not significantly influence the training outcomes. Instead, it appears that the integration of embodied VR feedback during MI training itself is sufficient to induce appropriate ERD, as evidenced by previous research.
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