People with spinal cord injuries often lose the ability to move their arms or legs. In many cases, the nerves in the limbs remain healthy and the brain continues to function normally. Loss of movement occurs because damage to the spinal cord blocks signals traveling between the brain and the body.
This disconnect has led scientists to search for ways to restore communication without repairing the spinal cord itself.
EEG testing as a non-invasive solution
In a study published in Bioengineering APL by AIP Publishing Researchers from universities in Italy and Switzerland investigated whether electroencephalography (EEG) could help bridge this gap. Their research focused on whether EEG can pick up brain signals associated with movement and potentially reconnect them to the body.
When a person tries to move a paralyzed limb, the brain still produces the electrical activity associated with that action. If these signals can be detected and interpreted, they could be sent to a spinal cord stimulator that activates the nerves responsible for movement in that limb.
The movement behind brain implants
Most previous studies relied on surgically implanted electrodes to record movement signals directly from the brain. Although these systems have shown encouraging results, the research team wanted to investigate whether EEG might offer a safer option.
EEG systems are worn as caps covered with electrodes that record brain activity from the scalp. While the setup may seem complicated, the researchers say it avoids the risks associated with placing a device in the brain or spinal cord.
“It can cause infections; it’s another surgery,” said author Laura Toni. “We wondered if it could be prevented.”
Challenges in reading motion signals
Using EEG to decode movement trials pushes the limits of current technology. Because the EEG electrodes are placed on the surface of the head, they try to pick up signals that originate deeper in the brain.
This limitation is less problematic for movements involving the arms and hands. Signals controlling the legs and feet are harder to detect because they come from areas closer to the center of the brain.
“The brain controls the movements of the lower limbs mainly in the central area, while the movements of the upper limbs are more on the outside,” said Toni. “Compared to the lower limbs, it’s easier to have a spatial mapping of what you’re trying to decode.”
Machine learning helps interpret brain activity
To better analyze the EEG data, the researchers used a machine learning algorithm designed to work with small and complex datasets. During testing, patients wore EEG caps and attempted a series of simple movements. The team recorded the resulting brain activity and trained an algorithm to sort the signals into different categories.
The system successfully distinguished between moments when patients tried to move and moments when they remained still. However, it was difficult to distinguish between different movement attempts.
What future research could achieve
The researchers believe that their method can be improved with further development. They plan to improve the algorithm so that it can recognize specific actions such as standing, walking or climbing. The team also hopes to explore how these decoded signals could be used to activate implanted stimulators in patients recovering from spinal cord injury.
If successful, the approach could bring non-invasive brain scanning closer to helping people regain meaningful movement after paralysis.
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