Lower limb rehabilitation system based on augmented reality and brain computer interface

A lower limb rehabilitation system based on augmented reality and a brain computer interface, comprising:

• a display for a user to wear and configured to receive and play a virtual scene video for the user to watch, to guide the user to perform gait rehabilitation training;
• a plurality of motion sensors respectively disposed at a plurality of parts of a lower limb of the user and configured to sense gait data;
• a brain wave monitor configured to record an electroencephalogram signal by detecting an electric current change in a brain wave of the user, wherein the electroencephalogram signal is a brain wave signal in a brain motor area of the user;
• and
• an analysis platform coupled to the display, the plurality of motion sensors, and the brain wave monitor, wherein the analysis platform is configured to:
• store a plurality of virtual scene videos by using a database unit, and select the virtual scene videos from the database unit and transmit the virtual scene videos to the display;
• receive the gait data sensed by the plurality of motion sensors and compare the gait data with the virtual scene videos, to determine the accuracy of footsteps of the user according to a virtual sign generated by the virtual scene videos and provide the user with feedback;
• input the electroencephalogram signal to a machine learning model, so that the machine learning model quantifies the electroencephalogram signal into an index value, wherein the index value is used for representing a lower limb motor function of the user;
• and output the index value.