  While search technologies have evolved to be robust and ubiquitous, the
fundamental interaction paradigm has remained relatively stable for decades.
With the maturity of the Brain-Machine Interface, we build an efficient and
effective communication system between human beings and search engines based on
electroencephalogram(EEG) signals, called Brain-Machine Search Interface(BMSI)
system. The BMSI system provides functions including query reformulation and
search result interaction. In our system, users can perform search tasks
without having to use the mouse and keyboard. Therefore, it is useful for
application scenarios in which hand-based interactions are infeasible, e.g, for
users with severe neuromuscular disorders. Besides, based on brain signals
decoding, our system can provide abundant and valuable user-side context
information(e.g., real-time satisfaction feedback, extensive context
information, and a clearer description of information needs) to the search
engine, which is hard to capture in the previous paradigm. In our
implementation, the system can decode user satisfaction from brain signals in
real-time during the interaction process and re-rank the search results list
based on user satisfaction feedback. The demo video is available at
http://www.thuir.cn/group/YQLiu/datasets/BMSISystem.mp4.
