Study: Brain-computer interface allows paralyzed man to control robotic arm

Implantation of a brain-computer interface (BCI) into tetraplegic participants allowed for consistent control of a robotic arm and hand for reaching and grasping, according to a study performed at the University of California San Francisco (UCSF) and published in Cell.

Tetraplegia, or quadriplegia, is the paralysis or loss of sensation or function in the cervical area of the spine that affects all four of a person’s limbs, both arms and legs. 

UCSF researchers aimed to study the stability and plasticity of the brain and how it strikes a balance between stable, well-practiced actions and being flexible enough to adjust to new situations quickly. 

Using a BCI, researchers tracked paralyzed individuals’ brain activity while they imagined simple movements. They found that the brain’s pattern for these imagined movements remains stable, though it shifted slightly day-to-day. 

Researchers said the brain could adjust how clearly different movements were represented without changing the overall structure of movement patterns, and the mental representations became sharper in the context of using the BCI.

After studying the participants’ brain patterns and how they changed over time, researchers identified a “meta-representational structure with generalizable decision boundaries,” or a deeper structure in the brain’s activity that allowed for long-term neuroprosthetic control of a robotic arm and hand for reaching and grasping.  

Users had complete voluntary control over the neuroprosthetic, with no help from AI or automation.

“This study provides new insights into how the brain maintains stable yet adaptable movement patterns, which could improve long-term control of neuroprosthetic devices,” the authors wrote. 

“Looking ahead, the key challenge for clinically useful BCIs will be balancing long-term stability with the time needed for recalibration.” 

The authors noted that adding vision-based assistance in the future may enhance results, especially for tasks involving complex object interactions.

THE LARGER TREND

Researchers noted limitations within the study, stating it is unclear how different ECoG grid placements in the brain or different participant groups, such as left-handed individuals, may affect the results. 

“Moreover, it is unclear whether there is a ceiling in the number of discrete motor commands that can be used for complex hDoF control. In addition, real-time continuous methods to account for drift might also affect our hDoF PnP results,” the authors noted. 

Future studies need to be done to “more directly contrast long-term adaptation of a biomimetic continuous decoder with IBID for overall performance and long-term PnP.” 

Other companies aiming to utilize BCI technology to allow individuals to control robotic body parts include Elon Musk’s brain-computer interface implant startup, Neuralink. 

In November, Neuralink announced on X that it received approval to launch a new feasibility study, CONVOY, which will test the use of its wireless BCIs, or N1 implant, to control an investigational assistive robotic arm. 

Neuralink’s PRIME (short for Precise Robotically Implanted Brain-Computer Interface) study involves the placement of a small, cosmetically invisible implant in the area of a person’s brain that plans movements. The N1 implant is designed to interpret one’s neural activity to assist them in operating a computer or smartphone by simply intending to move.