Brain-Controlled Intelligent Navigation Robot Based on Motor Imagery Brain-Computer Interface

Abstract

With the current continuous development of brain-computer interface technology, significant progress has been made in both signal processing and application areas. The ability to control external devices using EEG signals has opened up new possibilities in medical rehabilitation. Unlike traditional rehabilitation methods, which may be limited by physical constraints, BCI-based approaches offer a more intuitive and accessible means of interaction for patients with severe motor impairments, potentially accelerating recovery and improving overall outcomes. Motion imagery brain-computer interfaces can provide users with new ways of interacting, improving efficiency and experience. By analysing the technological developments in the existing literature and comparing different approaches. Summarise their current application examples and future directions. The review finds that the research currently leaves much room for improvement in terms of signal decoding accuracy, interference and noise handling, user adaptability, and system real-time the review summarises the main technological advances and current challenges faced in the research, providing valuable insights for future research. It is suggested that future research should focus on technology integration and data parsing capability enhancement to advance the field.