- Advertisement -Newspaper WordPress Theme

Top 5 This Week

Related Posts

UCLA Researchers Develop Non-Invasive AI Brain-Computer Interface to Boost Motor Control

Researchers at the University of California, Los Angeles (UCLA) have developed a groundbreaking non-invasive brain-computer interface (BCI) that uses artificial intelligence (AI) as a “co-pilot” to enhance motor control. The innovation allows users to operate a robotic arm or control a computer cursor with greater precision and speed compared to existing systems.

Traditional BCI devices often rely on surgical implants, which carry high medical risks and significant costs. By contrast, this new solution leverages electroencephalography (EEG) to capture brain signals externally, avoiding invasive procedures. Advanced AI algorithms then decode these impulses and convert them into precise movement commands. According to the UCLA team, real-time AI-assisted interpretation of user intent dramatically improves the accuracy of tasks.

Jonathan Kao, associate professor of electrical and computer engineering at UCLA’s Samueli School of Engineering and lead researcher of the study, explained that combining AI with BCI creates safer, more accessible pathways for individuals with motor impairments. “Using artificial intelligence alongside brain-computer interfaces, we aim to provide less risky, non-invasive methods that can restore independence,” Kao noted.

The system was tested on four participants, including one with paralysis. During the experiments, users performed tasks such as guiding a mouse cursor between eight on-screen targets and manipulating blocks on a table with a robotic hand. Results showed significant performance improvements when the AI-assisted BCI was enabled. In fact, the paralyzed participant successfully completed a robotic arm task in just six and a half minutes using AI support—whereas without AI, completing the same task was impossible.

The study highlights how AI-enhanced BCI can bridge the gap between invasive implants and less reliable wearable alternatives. While traditional implant-based BCIs achieve high precision, they involve brain surgery. On the other hand, non-invasive devices often struggle to reliably interpret neural signals. UCLA’s approach demonstrates that AI can close this performance gap, making external BCI systems both practical and effective.

Beyond technical advances, the implications for healthcare are significant. People living with paralysis, ALS, or motor impairments could benefit from affordable assistive technologies that restore daily functionality. The researchers envision future AI-BCI hybrid systems capable of enabling individuals to regain independence in communication, mobility, and daily tasks.

Conclusion: UCLA’s non-invasive AI-BCI system represents a major leap toward safer, more accessible neurotechnology. By integrating artificial intelligence as an active partner in interpreting brain signals, researchers have paved the way for practical assistive devices that do not require surgery. If further developed and commercialized, this breakthrough could transform lives by restoring autonomy to individuals with severe motor limitations.

Popular Articles