A Study Of BCI-based Coordinate Control

Brain computer interface(BCI) is a new communication and control channel which can translate the brain activities directly to the computer commands without the participations of traditional output pathways of peripheral nerves and muscles. As the developing of new theories and technologies, this kind of human-machine interaction reveals significant prospect of applications in medical rehabilitation, industry, and military and so on.As the restriction of brain activity measurements, the practical information transformation rate of BCI was still in a low level, which the system’s real-time performance, reliability and the bandwidth cannot satisfy the requirement of practical applications. This paper aimed to improve the practical communication efficiency of BCI by designing new signal processing algorithm and optimizing control strategy. Through these researches, more reliable, higher efficiency and human-machine coordinate BCI control system can be constructed to improve the control level of BCI system. On the one hand, the signal processing algorithm was improved to extract the intensity of MI from EEG signal based on the classification of limbs’ movement imagery(MI) to construct a linear input-output BCI system. On the other hand, we combined BCI system with autonomous control system using shared control strategy to improve the BCI’s practical communication efficiency and control performance. In this study, the typical instable system – inverted pendulum was selected as our control object. A stimulated virtual inverted pendulum system was designed to test our first program, and a real inverted pendulum was applied for the second protocol.Three health subjects participated in this study. In the stimulated virtual inverted pendulum control experiment, two subjects could adjust the amplitude of the BCI output. The averaged control time of the two subjects was above 20 seconds. In the second experiment, another two subjects successfully balanced the real inverted pendulum, which verify the reliability of our BCI system. These experiment results proved that the signal processing algorithm and human-machine shared control strategy proposed in this paper could successfully improve the practical communication efficiency of BCI, which has important significance for constructing practical BCI control system.