Scientists have pinpointed brain activity related to inner speech—the silent monolog in people's heads—and successfully decoded it on command with up to 74% accuracy. "This is the first time we've ...

China’s brain-computer interface industry is rapidly scaling from research to commercialization, driven by strong policy support, expanding clinical trials, and growing investor interest.

Brain-computer interfaces are a groundbreaking technology that can help paralyzed people regain functions they’ve lost, like moving a hand. These devices record signals from the brain and decipher the ...

Professor Ngai Wong and Dr Zhengwu Liu from the Department of Electrical and Electronic Engineering at the Faculty of Engineering at the University of Hong Kong (HKU), in collaboration with research ...

Brain-Computer Interfaces (BCIs) are emerging as transformative tools that enable direct communication between the human brain and external devices. With recent advancements in Electroencephalography ...

Brain–machine interfaces (BMIs) represent a transformative field at the intersection of neuroscience, engineering and computer science, allowing for direct communication between the brain and external ...

Brain-computer interfaces (BCIs) have the potential to make life easier for people with motor or speech disorders, allowing them to manipulate prosthetic limbs and employ computers, among other uses.

Researchers researchers bring noninvasive EEG-based BCI one step closer to everyday use by demonstrating real-time brain decoding of individual finger movement intentions and control of a dexterous ...

Brain-computer interface experiments began more than 20 years ago Technology decodes brain signals that control speech and movement Elon Musk's Neuralink is a major player in field, along with ...

New research introduces the Chill Brain-Music Interface (C-BMI), using in-ear EEG sensors to trigger "musical chills" and maximize emotional pleasure in real-time.

Yale University, Dartmouth College, and the University of Cambridge researchers have developed MindLLM, a subject-agnostic model for decoding functional magnetic resonance imaging (fMRI) signals into ...