A study using EEG signals and a custom convolutional neural network (CNN) predicted the outcome of repetitive transcranial magnetic stimulation (rTMS) therapy for major depressive disorder (MDD) with …
A study of neural-interface models reveals a critical gap between formal robustness certificates and real-world safety, with EEGNet's classification accuracy dropping 25.7% under attack while certific…
Researchers found that formal robustness certificates for embedded neural-interface models can pass even when task accuracy collapses, with EEGNet classification accuracy dropping 25.7% under attack w…
Researchers have developed a lightweight custom convolutional neural network to improve the security of EEG-based brain-computer interfaces against adversarial attacks. The proposed model outperformed…