Scientists tested a prosthesis that allows one animal to use its recorded neural activity to control limb movements in a different, sedated animal.
"The next step is to advance the development of brain-machine interface algorithms using the principles of control theory and statistical signal processing," says Maryam Shanechi. "Such brain-machine interface architectures could enable patients to generate complex movements using robotic arms or paralyzed limbs." (Credit: Maya Ibuki/Flickr)
To help people suffering paralysis from injury, stroke, or disease, scientists have invented brain-machine interfaces that record electrical signals of neurons in the brain and translate them to movement. Usually, that means the neural signals direct a device, like a robotic arm.
Maryam Shanechi, assistant professor of electrical and computer engineering at Cornell University, hopes to help paralyzed people move their own limb, just by thinking about it.
When paralyzed patients imagine or plan a movement, neurons in the brain’s motor cortical areas still activate even though the communication link between the brain and muscles is broken. By implanting sensors in these brain areas, neural activity can be recorded and translated to the patient’s desired movement using a mathematical transform called the decoder.
These interfaces allow patients to generate movements directly with their thoughts.