Brain-computer interfaces translate neural signals into actions, revolutionizing healthcare and enhancing communication for individuals with disabilities.

A new AI algorithm can associate brain activity with certain behaviors, an advancement that can help improve brain-computer interfaces and find new patterns in neural activity.

The signals can then be processed on the computer using the provided Python example code. From there, the raw data can be visualized or plugged into whatever application you have in mind.

Similar brain–computer interface (BCI) devices, which translate signals in the brain into text, have reached speeds of 62–78 words per minute for some people.

Brain computer interfaces (BCIs) are electrodes put in paralyzed people’s brains so they can use imagined movements to send commands from their neurons through a wire, or via radio, to a computer.

By focusing on real-world applications and emerging challenges, the series equips engineers with the knowledge needed to contribute to the future of neurotechnology.

From enhancing mobility and motor function to improving sensory capabilities, brain-computer interfaces (BCI) can expand our human capabilities by enabling seamless communication, improving ...