The invention discloses a method and
system for driving and controlling a
lower limb exoskeleton through brain-computer interface intention confidence, and relates to the technical field of
medical rehabilitation. The method comprises the following steps: firstly, identifying an original electroencephalogram
signal to obtain intention confidence, and mapping an impedance parameter group containing
joint stiffness and a damping coefficient in combination with
gait phase information; secondly, extracting a motion position and an interaction force error, comparing an intention confidence coefficient with an actual execution state by using a
sliding time window to obtain a nerve matching error, and fusing the three into a total composite error; meanwhile, the human-
machine coupling compliance is evaluated based on the
human body joint angle and the
exoskeleton torque variation, and a safety
gain coefficient is discriminated and generated; and finally, performing
gain operation on the total composite error based on the impedance parameter group, and performing safety
gain coefficient correction to obtain a
target control torque to be output to a driving
actuator. In this way, a nerve-force-motion three-closed-loop framework is constructed, and compliant self-adaptive on-demand assistance and high-safety man-
machine collaborative
rehabilitation with defense protection are achieved.