terveys
Kuvittele ruutu täynnä sahalaitaa. Sähköiset aivoaallot piirtyvät riveiksi, kun potilaan päähän on laitettu mittausmyssy. Lääkäri etsii merkkejä siitä, muuttuuko aivojen rytmi tavalla, joka sopisi Alzheimerin tautiin. Usein apuna on tietokoneohjelma, joka ottaa mittauksen vastaan ja sylkee ulos luokituksen: kyllä tai ei, todennäköistä tai epätodennäköistä. Se on kätevää – ja samalla vaivaannuttavan
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
Neuroimaging
What if lab-grade brain imaging could go wearable—and be analyzed with the same, reproducible playbook? Meet Cedalion, an open-source Python framework for making sense of light-based brain data: fNIRS and DOT (they use harmless light to track brain activity). Cedalion unifies the whole pipeline in one place: forward modeling
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.