BCI
EEG-based brain–computer interfaces often stumble in the real world: every person’s brain signals look different, and conditions change from moment to moment. A new approach called Backpropagation-Free Transformations (BFT) helps BCIs adapt on the fly—without costly re-training, extra data, or exposing private signals. How it works * For
EEG
What if your AI could sense when a chat feels hard—or when you silently agree? This pilot study tests whether EEG signals can reveal mental workload and implicit agreement during spoken conversation with a conversational AI. Researchers reused established EEG classifiers in two voice-based tasks: a Spelling Bee and
BCI
Brain-to-Vehicle, in Real Time What if your car knew you were about to turn before you moved the wheel? This study turns EEG brainwaves into steering intentions using deep learning, hinting at faster, more intuitive driver assistance. * Task: Predict left, right, or straight intentions while people “drove” in a simulator.