Detection of Mental Fatigue Using Artificial Intelligence for Brain–Computer Interface

Brain–Computer Interfaces (BCIs) performance and usability are significantly impacted by mental tiredness. Accurate mental fatigue detection is crucial for guaranteeing user safety and sustaining system effectiveness as BCIs are rapidly integrated into a variety of applications, such as healthcare, interpersonal interaction, and control systems. This study investigates the application of artificial intelligence (AI) methods for the instantaneous recognition of mental tiredness in BCI users. The term “mental fatigue” describes the loss of cognitive and physical function that might follow from sustained mental effort. We examine the body of research, talk about several AI techniques, and suggest a fresh strategy for identifying mental weariness in BCI users. The use of artificial intelligence has shown to be one of the most effective methods for identifying and managing fatigue. Artificial intelligence models are able to effectively anticipate mental weariness by learning from vast volumes of data. However, when it comes to modeling, acquiring parameters is sometimes given greater attention than examining and validating them within the model.