March 16, 2026
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Brain implant allows people who are paralyzed to write using their thoughts with captioning
A brain-computer interface allowed two people who had lost the ability to move their limbs to type at speeds of up to 22 words per minute
A BrainGate participant writes with the help of a brain implant.
For people with near-total paralysis, the ability to communicate easily in real time is a challenge. For years, researchers have worked to correct this by developing devices that can decode brain signals and translate them into computer cursor movements or text.
These devices are a type of brain-computer interface, or BCI, and consist of electrode chips implanted inside the brain to listen to and decode the electrical whispering of neurons. In the past, BCIs allowed people to type using a virtual keyboard, but the speed was frustratingly slow. Now, however, a team of researchers reports that their BCI keyboard helped two people with paraplegia at speeds of up to 22 words per minute—almost as fast as the average person can text with a smartphone. The findings were published today in Nature Neuroscience.
“This is an important technical advance that brings brain-computer typing much closer to practical communication speeds for people with paralysis,” said Edward Chang, a professor of neurological surgery at the University of California, San Francisco, who was not involved in the study.
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“At about 22 words per minute, this is among the fastest motor-cortex typing BCIs to date and dramatically faster than most previous neural spellers,” says Chang, who has worked on another speech-decoding BCI.
BCI technology has evolved significantly since its inception in the 1960s, when researchers began using single electrodes implanted in the brains of monkeys to record their neural activity. In 2006, a consortium of researchers called BrainGate reported that a BCI allowed people with paralysis to control a computer cursor and operate a prosthetic hand. In recent years, the BrainGate BCI was used to control a virtual keyboard with a cursor and to decode letters from handwriting areas in the brain. Other groups’ BCIs also have decoded words or short phrases directly from speech-related brain regions.
Previous versions of these brain-typing systems required participants to control a cursor on a screen and individually select letters, “which is far slower than being able to access any key at any time using your fingers,” says lead study author Justin Jude, a postdoctoral researcher at BrainGate, based at Brown University, and an appointed fellow at Massachusetts Medical School and Harvard.
In the new paper, Jude and his colleagues trained BCI using artificial intelligence to recognize intended hand or finger movements from a part of the brain’s movement area, called the precentral gyrus, when participants tried to move their paralyzed hands or fingers. The AI model predicted the letters on a QWERTY keyboard that the gestures were most likely to match. They tested their system on two participants: a person with amyotrophic lateral sclerosis, a progressive neurological disease that causes paralysis, and one with a spinal cord injury that left them paralyzed but still able to speak.
Using the device, the latter participant was able to type at 110 characters or 22 words per minute, with a word error rate of 1.6 percent. The second participant’s writing was slower, but still impressive for someone who lacked the ability to speak. In comparison, the BrainGate handwriting BCI several years ago achieved speeds of 90 characters per minute (about 18 words per minute). Another previous BCI implanted in a speech-related brain region by Chang and his colleagues was used to achieve a typing speed of 78 words per minute, but the median word error rate was far higher – 25 percent.
“One of the things we talk about a lot is the speed of communication. The reason we do that is not just to have a faster system than anybody else,” said Daniel Rubin, a critical care neurologist at Massachusetts General Hospital and an assistant professor of neurology at Harvard Medical School, who co-authored the new study.
People who have lost the ability to speak and use their hands may be able to use an eye-tracking system to type, but this method is slow. “Communication speed is important, because it’s important to be part of a conversation,” says Rubin.
The researchers say that the QWERTY keyboard system is more successful than the version that decoded mental handwriting. However, it remains to be seen whether decoding from brain regions that control finger movements or from speech-related regions is a better strategy in general, says Chang. Signals in the brain’s motor cortex are easier to decode, but those in speech-related areas can be faster and more direct.
The technology is not yet ready for widespread use; the study was small, and the device requires brain surgery, which carries risks. “The major limitations are the small number of participants and the need for invasive intracortical implants,” says Chang.
Another limitation is the need to calibrate the BCI each time before it can be used. “It’s almost like a musical instrument, and you have to tune it every day,” says Rubin. Having an instrument that can tune itself is a major goal for the field, he says.
Several companies are developing commercial BCIs, primarily for use in people who are paralyzed. Perhaps the most hyped has been Elon Musk’s Neuralink, but there are others, such as Paradromics and Synchron. (Some of the study authors consult for these companies and receive research funding from them.)
China recently approved the first invasive BCI for use in people with a form of partial paralysis. No such devices have been approved by the Food and Drug Administration for use by people with paralysis in the United States
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