The 58-year-old — who has chosen to remain anonymous — was diagnosed with amyotrophic lateral sclerosis (ALS) in 2008. Over the years, the disease destroyed her capacity to control most of her body and caused her to develop locked-in syndrome, an inability to move or communicate due to paralysis while still maintaining consciousness.
Up until recently, the patient communicated by spelling out words using an eye-tracking system. The solution was temporary, however, as a third of all ALS patients eventually lose control of their eye movements. Other methods — like the one used by physicist Stephen Hawking, who communicates through a smaller sensor controlled by his cheek muscles — also rely on capabilities that may not always be reliable.
The at-home brain-computer interface (BCI) was developed by Nick Ramsey’s team at the Brain Center of University Medical Center Utrecht in the Netherlands. Previous research has seen the development of probes that have enabled users to control artificial limbs through brain signals, but so far these devices have been impractical outside of the laboratory due to their constant need for calibration.
To mitigate this issue, Ramsey and his team focused on detecting just the brain signals that fire when the brain counts backwards and commands the body to click a mouse.
The new device connects electrodes to the brain through a small hole beneath the skull. The electrodes register brain signals and transmit them wirelessly to a tablet that translates the signals into “clicks,” which specialized software can use to help the patient spell words or select items.
“I want to contribute to possible improvements for people like me,” the patient told New Scientist.
In her first day of use, the patient was able to generate a brain signal with the system. Six months later, she had an accuracy of 95 percent. Ramsey presented his team’s work yesterday at the Society for Neuroscience in San Francisco, California.
The current system isn’t perfect though. Due to its simplicity, it won’t likely be able to handle complicated tasks, such as controlling artificial limbs, in the future. And it’s slower than the eye tracker, taking about 20 seconds to select a single letter.
But the system’s simplicity makes it ideal for practical, at-home applications. And it offers the patient more freedom, since the previous device often couldn’t register slight eye movements while she was outdoors. “Now I can communicate outdoors when my eye-track computer doesn’t work,” she said. “I’m more confident and independent now outside.”
Ramsey and his team plan to trial the system with another patient. While refining the software, they expect future tests to advance faster than the first. Hardware updates may one day may it possible to capture more commands like driving a wheelchair.
