A study of external machine control pathways based on brain-computer interfaces

Abstract. This research analyses three fundamental paradigms in brain-computer interface (BCI) systems: motor imagery (MI), sensorimotor rhythms (SMRs), and P300-based paradigms, focusing on their methodology and applications. Motor imagery-based brain-computer interface (MI-BCI) entails mentally practicing motor activities while adjusting electroencephalography (EEG) patterns and utilising multimodal stimulation to enhance the accuracy of classification. SMR-BCI employs precise EEG band oscillations to operate prosthetics and virtual environments. Sensory threshold neuromuscular electrical stimulation is used to improve performance. The P300 paradigm utilizes event-related potentials to control devices, and includes advancements such as the omitted elicited paradigm to enhance efficiency. In addition, the study examines control strategies for BCI systems, such as PID, MPC, and shared control approaches. By utilizing MATLAB as a tool, one may ascertain the distinction between different control strategies, highlighting their respective contributions to improving system responsiveness and stability.