Hybrid brain-computer interface system and method based on movement imagination

Abstract

The invention discloses a hybrid brain-computer interface system and method based on movement imagination. The system comprises an electroencephalography and electrooculogram collection/processing module, an ICA filter design module, a zero-training MI classification module, a target movement control and path display module and an information feedback module. An ICA filter and a BCI system can be designed on line or off line; and after system design is completed, an eye movement detection module judges whether to get into a electroencephalography processing and classifying mode through analysis of the number of blinks of a user, and the classification result is converted into a command used for controlling a target on a system main interface to move along a specified path. The user can observe the difference between a true movement trace of the target and a planned path, adjust the MI mode in time and control the target to return to the planned path. By aid of the advantages of ICA unsupervised learning, the collection amount of BCI training data is effectively reduced, and through reasonable algorithm module design, the designed hybrid BCI system has good stability and operability.

Description

technical field [0001] The invention belongs to the technical field of brain-computer interface (Brain-Computer Interface, BCI), in particular to a hybrid brain-computer interface system based on motor imagery. Background technique [0002] Brain-computer interface, as a new type of human-computer interaction technology using electroencephalography (EEG) as the information carrier, has received extensive attention in recent years. The realization process of brain-computer interface technology is to analyze and process multi-lead EEG signals, extract task-related feature patterns in EEG and convert them into commands, and then realize the direct control of external devices by the brain. The ultimate goal of BCI technology is to provide a direct communication channel for controlling external devices for groups with physical disabilities (or motor dysfunction). At the same time, BCI technology can also be applied to motor function rehabilitation training, development of brain-...

AI Technical Summary

Problems solved by technology

The difficulty of the asynchronous BCI system lies in the determination of the idle state and non-idle state of the brain, that is, how to accurately determine the start moment of the user's motor imagination. Due to the randomness of the motor imagery and the large individual differences of the users, the realization of the asynchronous BCI system is relatively difficult. Large, and once the current brain state is wrongly judged, the system will have serious misoperations

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