Brain Computer Interface

Brain-computer interfaces (BCIs) aim to establish direct communication pathways between the brain and external devices, primarily using electroencephalography (EEG) signals. Current research heavily emphasizes improving decoding accuracy and efficiency through advanced machine learning techniques, including deep learning architectures like transformers and convolutional neural networks, as well as novel signal processing methods such as Riemannian geometry and wavelet analysis. These advancements are crucial for enhancing the reliability and practicality of BCIs, with potential applications ranging from assistive technologies for individuals with motor impairments to neurorehabilitation and the understanding of cognitive processes.