To achieve this result electrodes were implanted in Oskam’s skull and spine. And signals between the brain and spine were sent every 300 milliseconds to and from the electrodes.
A machine-learning program then observes which parts of the brain light up as the patient tries to move different parts of his body. This thought decoder was able to match specific electrode activity with particular intentions. And one configuration lit up whenever Oskam tried to move his ankles, another when he tried to move his hips.
