Kinney-Lang E, Murji S, Kelly D, Paffrath B, Zewdie E, Kirton A
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:6078-6081. doi: 10.1109/EMBC44109.2020.9175801.
Early neurological injury or disease can lead to severe life-long physical impairments, despite normal cognitive function. For such individuals, brain-computer interfaces (BCI) may provide a means to regain access to the world by offering control of systems through directly processing brain patterns. However, current BCI applications are often research driven and consequently seen as uninteresting, particularly for prolonged use and younger BCI-users. To help mitigate this concern, this paper establishes a tool for researchers and game developers alike to rapidly incorporate a BCI control scheme (the P300 oddball response) into a gaming environment. Preliminary results indicate the proposed P300 Dynamic Cube (PDC) asset works in online BCI environments (n=20, healthy adult participants), resulting in median classification accuracy of 75 ± 3.28%. Additionally, the PDC tool can be rapidly adapted for a variety of game designs, evidenced by its incorporation into submissions to the Brain-Computer Interface (BCI) Game Jam 2019 competition. These findings support the PDC as a useful asset in the design and development of BCI-based games.
早期神经损伤或疾病可能导致严重的终身身体损伤，尽管认知功能正常。对于这类个体，脑机接口（BCI）或许能通过直接处理脑电模式来控制各种系统，从而为他们提供一种重新与外界建立联系的方式。然而，当前的脑机接口应用往往由研究驱动，因此显得无趣，尤其是对于长期使用和年轻的脑机接口用户而言。为了缓解这一问题，本文为研究人员和游戏开发者创建了一种工具，以便能迅速将脑机接口控制方案（P300 奇偶数反应）融入游戏环境。初步结果表明，所提出的 P300 动态立方体（PDC）资产在在线脑机接口环境中有效（n = 20，健康成年参与者），中位分类准确率为 75 ± 3.28%。此外，PDC 工具能够快速适应各种游戏设计，这在其被纳入 2019 年脑机接口（BCI）游戏节竞赛的参赛作品中得到了证明。这些发现支持了 PDC 作为基于脑机接口的游戏设计与开发中的一种有用资产。
