Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt.
Biomedical Engineering Department, Misr University for Science and Technology, Giza, Egypt.
Neuroinformatics. 2019 Jul;17(3):323-341. doi: 10.1007/s12021-018-9402-0.
The past twenty years have ignited a new spark in the research of Electroencephalogram (EEG), which was pursued to develop innovative Brain Computer Interfaces (BCIs) in order to help severely disabled people live a better life with a high degree of independence. Current BCIs are more theoretical than practical and are suffering from numerous challenges. New trends of research propose combining EEG to other simple and efficient bioelectric inputs such as Electro-oculography (EOG) resulting from eye movements, to produce more practical and robust Hybrid Brain Computer Interface systems (hBCI) or Brain/Neuronal Computer Interface (BNCI). Working towards this purpose, existing research in EOG based Human Computer Interaction (HCI) applications, must be organized and surveyed in order to develop a vision on the potential benefits of combining both input modalities and give rise to new designs that maximize these benefits. Our aim is to support and inspire the design of new hBCI systems based on both EEG and EOG signals, in doing so; first the current EOG based HCI systems were surveyed with a particular focus on EOG based systems for communication using virtual keyboard. Then, a survey of the current EEG-EOG virtual keyboard was performed highlighting the design protocols employed. We concluded with a discussion of the potential advantages of combining both systems with recommendations to give deep insight for future design issues for all EEG-EOG hBCI systems. Finally, a general architecture was proposed for a new EEG-EOG hBCI system. The proposed hybrid system completely alters the traditional view of the eye movement features present in EEG signal as artifacts that should be removed; instead EOG traces are extracted from EEG in our proposed hybrid architecture and are considered as an additional input modality sharing control according to the chosen design protocol.
在过去的二十年中，脑电图（EEG）的研究引发了新的火花，研究目的是开发创新的脑机接口（BCI），以帮助严重残疾人士实现高度独立的美好生活。当前的 BCI 更注重理论，而在实践中面临诸多挑战。新的研究趋势提出将 EEG 与其他简单而高效的生物电输入（如眼动产生的眼动电图（EOG））相结合，以产生更实用、更稳健的混合脑机接口系统（hBCI）或脑/神经元计算机接口（BNCI）。为了实现这一目标，必须对现有的基于 EOG 的人机交互（HCI）应用研究进行组织和调查，以便对结合这两种输入模式的潜在优势形成一个愿景，并提出新的设计方案，最大限度地发挥这些优势。我们的目标是支持和激发基于 EEG 和 EOG 信号的新型 hBCI 系统的设计；为此，首先对当前基于 EOG 的 HCI 系统进行了调查，特别关注基于 EOG 的用于虚拟键盘通信的系统。然后，对当前 EEG-EOG 虚拟键盘进行了调查，强调了所采用的设计协议。最后，讨论了结合这两个系统的潜在优势，并就所有 EEG-EOG hBCI 系统的未来设计问题提出了建议。最后，提出了一个新的 EEG-EOG hBCI 系统的总体架构。所提出的混合系统完全改变了传统观点，即认为 EEG 信号中的眼动特征是伪迹，应予以去除；相反，在我们提出的混合架构中，从 EEG 中提取 EOG 轨迹，并根据所选设计协议将其视为共享控制的附加输入模式。
