Faller J, Torrellas S, Miralles F, Holzner C, Kapeller C, Guger C, Bund J, Müller-Putz G R, Scherer R
Institute for Knowledge Discovery, Graz University of Technology, 8010 Graz, Austria.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:1827-30. doi: 10.1109/EMBC.2012.6346306.
We present the prototype of a context-aware framework that allows users to control smart home devices and to access internet services via a Hybrid BCI system of an auto-calibrating sensorimotor rhythm (SMR) based BCI and another assistive device (Integra Mouse mouth joystick). While there is extensive literature that describes the merit of Hybrid BCIs, auto-calibrating and co-adaptive ERD BCI training paradigms, specialized BCI user interfaces, context-awareness and smart home control, there is up to now, no system that includes all these concepts in one integrated easy-to-use framework that can truly benefit individuals with severe functional disabilities by increasing independence and social inclusion. Here we integrate all these technologies in a prototype framework that does not require expert knowledge or excess time for calibration. In a first pilot-study, 3 healthy volunteers successfully operated the system using input signals from an ERD BCI and an Integra Mouse and reached average positive predictive values (PPV) of 72 and 98% respectively. Based on what we learned here we are planning to improve the system for a test with a larger number of healthy volunteers so we can soon bring the system to benefit individuals with severe functional disability.
我们展示了一个情境感知框架的原型，该框架允许用户通过基于自动校准感觉运动节律（SMR）的脑机接口（BCI）和另一种辅助设备（Integra鼠标口控操纵杆）组成的混合BCI系统来控制智能家居设备并访问互联网服务。虽然有大量文献描述了混合BCI的优点、自动校准和协同自适应事件相关去同步（ERD）BCI训练范式、专门的BCI用户界面、情境感知和智能家居控制，但截至目前，还没有一个系统能将所有这些概念整合到一个集成的、易于使用的框架中，从而通过提高独立性和社会包容性真正造福于严重功能残疾的个体。在此，我们将所有这些技术集成到一个原型框架中，该框架不需要专业知识或过多的校准时间。在首次试点研究中，3名健康志愿者分别使用来自ERD BCI和Integra鼠标的输入信号成功操作了该系统，平均阳性预测值（PPV）分别达到了72%和98%。基于我们在此学到的知识，我们计划改进该系统，以便对更多健康志愿者进行测试，从而尽快使该系统造福于严重功能残疾的个体。
