Objective. A key challenge of virtual reality (VR) applications is to maintain a reliable human-avatar mapping. Users may lose the sense of controlling (sense of agency), owning (sense of body ownership), or being located (sense of self-location) inside the virtual body when they perceive erroneous interaction, i.e. a break-in-embodiment (BiE). However, the way to detect such an inadequate event is currently limited to questionnaires or spontaneous reports from users. The ability to implicitly detect BiE in real-time enables us to adjust human-avatar mapping without interruption. Approach. We propose and empirically demonstrate a novel brain computer interface (BCI) approach that monitors the occurrence of BiE based on the users’ brain oscillatory activity in real-time to adjust the human-avatar mapping in VR. We collected EEG activity of 37 participants while they performed reaching movements with their avatar with different magnitude of distortion. Main results. Our BCI approach seamlessly predicts occurrence of BiE in varying magnitude of erroneous interaction. The mapping has been customized by BCI-reinforcement learning (RL) closed-loop system to prevent BiE from occurring. Furthermore, a non-personalized BCI decoder generalizes to new users, enabling ‘Plug-and-Play’ ErrP-based non-invasive BCI. The proposed VR system allows customization of human-avatar mapping without personalized BCI decoders or spontaneous reports. Significance. We anticipate that our newly developed VR-BCI can be useful to maintain an engaging avatar-based interaction and a compelling immersive experience while detecting when users notice a problem and seamlessly correcting it.

中文翻译：

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基于脑电图错误相关电位定制人类头像映射

客观的。虚拟现实 (VR) 应用的一个关键挑战是维护可靠的人体-化身映射。当用户感知到错误的交互，即闯入实施例时，他们可能会失去对虚拟身体的控制感（代理感）、拥有感（身体所有权感）或定位感（自我定位感） ）。然而，目前检测此类不充分事件的方式仅限于问卷调查或用户自发报告。实时隐式检测 BiE 的能力使我们能够不间断地调整人类头像映射。方法。我们提出并实证证明了一种新颖的脑机接口（BCI）方法，该方法可以根据用户的大脑振荡活动实时监控 BiE 的发生，以调整 VR 中的人类头像映射。我们收集了 37 名参与者在用不同变形程度的虚拟人物进行伸手动作时的脑电图活动。主要结果。我们的 BCI 方法可以无缝预测不同程度的错误交互中 BiE 的发生。该映射已通过 BCI 强化学习 (RL) 闭环系统进行定制，以防止 BiE 的发生。此外，非个性化 BCI 解码器适用于新用户，从而实现基于 ErrP 的“即插即用”非侵入式 BCI。所提出的 VR 系统允许定制人类头像映射，无需个性化 BCI 解码器或自发报告。意义。我们预计，我们新开发的 VR-BCI 可用于维持引人入胜的基于化身的交互和引人入胜的沉浸式体验，同时检测用户何时注意到问题并无缝纠正它。