This series of demos demonstrate my recent progress in regards to Brain Computer Interface (BCI) system. An electroencephalography (EEG) based Brain Computer Interface (BCI) enables people to communicate with the outside world by interpreting the EEG signals of their brains to interact with intelligent devices such as wheelchairs and robots. More specifically, motor imagery EEG (MI-EEG), which reflects a subject’s active movement intent, has been attracting increasing attention in developing an EEG-based BCI system.
A simulated robot is navigated by our system, which learns user’s intent from EEG recordings, to take a can of beverage from a table in the kitchen and put it in a table in living room.
Reusable source code and dataset are provided in my github (EEG-based-Control repository).
Xiang Zhang, Lina Yao, Chaoran Huang, Quan Z. Sheng and Xianzhi Wang, Intent Recognition in Smart Living Through Deep Recurrent Neural Networks. The 24th International Conference On Neural Information Processing (ICONIP 2017). Guangzhou, China, November 14-18, 2017.(Accepted, CORE Rank A)
Xiang Zhang, Lina Yao, Dalin Zhang, Xianzhi Wang, Quan Z. Sheng and Tao Gu. Intent Recognition in Smart Living Through Deep Recurrent Neural Networks. The 14th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous 2017). Melbourne, Australia Nov 7 - 10, 2017. (Accepted, CORE Rank A)
An online brain typing system is developed to convert user’s thoughts to texts, which based on the high EEG (brainwave) signals classification accuracy. Motor disabled people would benefit greatly from such a system to express their thoughts and communicate with the outer world.
The EEG dataset can be accessed from this link.
Xiang Zhang, Lina Yao, Quan Z. Sheng, Salil S. Kanhere, Tao Gu and Dalin Zhang, Converting Your Thougts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG Signals. IEEE International Conference on Pervasive Computing and Communications (PerCom 2018). Athens, Greece, March 19-23, 2018. (Accepted, CORE Rank A*)