The present invention relates to a brain-computer interface system and a method for analyzing a brainwave signal expressed by motor imagery. The method comprises: (a) a step of acquiring a source brainwave signal expressed in motor imagery during a preset measurement time, and filtering the source brainwave signal in a base frequency band associated with motor imagery to generate a brainwave signal; (b) a step of performing an optimal performance search algorithm for calculating a time range and an optimal expression frequency domain of a brainwave feature pattern for the brainwave signal to divide the brainwave signal into preset frequency intervals to convert the brainwave signal into n sub-band signals and then detect a maximum performance time range for each of the sub-band signals; (c) a step of extracting a brainwave feature based on the maximum performance time range for each sub-band signal, using the extracted brainwave feature to generate a classification model for recognizing a motion imagined or intended by a user, and then calculating the accuracy for a classification result of the classification model to perform classification performance evaluation; and (d) a step of detecting an optimal sub-band signal having the highest performance based on result values of the classification performance evaluation, and a maximum performance time range linked to the optimal sub-band signal to provide the optimal sub-band signal and the maximum performance time range in an optimized motor imagery frequency-time domain for each user. The optimal performance search algorithm performs performance evaluation in a plurality of time ranges generated by setting a time search window having a preset time range and applying the time search window at preset critical time intervals in the measurement time of each sub-band signal.
- BRAIN-COMPUTER INTERFACE SYSTEMS AND METHOD FOR ANALYSING BRAIN WAVE SIGNALS EXPRESSED BY MOTOR IMAGERY