Control prosthetic hands more precisely with the power of thought

Researchers from the German Primate Center – Leibniz Institute for Primate Research in Göttingen have developed a new training protocol for brain-computer interfaces in a study on rhesus monkeys. The method allows precise control of prosthetic hands using only signals from the brain.

For the first time, the researchers were able to show that the neural signals that control different hand postures in the brain are mainly important for this control, and not, as previously thought, the signals that control the speed of movement.

The results, published in Neuronare essential to improve the fine control of neural hand prostheses, which could restore all or part of their mobility to paralyzed patients.

Carrying shopping bags, pulling a thread through the eye of a needle: powerful and precise handles are part of our daily lives. We only realize the importance (and greatness) of our hands when we can no longer use them, for example because of paraplegia or diseases like ALS, which cause progressive muscle paralysis.

To help patients, scientists have been studying neuroprosthetics for decades. These artificial hands, arms or legs could restore mobility to disabled people. The damaged nerve connections are connected via brain-computer interfaces that decode brain signals, translate them into movements and can thus control the prosthesis.

However, until now, hand prosthetics in particular did not have the fine motor skills needed to be used in everyday life.

“The functioning of a prosthesis mainly depends on the neural data read by the computer interface that controls it,” explains Andres Agudelo-Toro, scientist in the neurobiology laboratory of the German Primate Center and first author of the study.

“Previous studies on arm and hand movements have focused on signals that control the speed of a grasping movement. We wanted to know if neural signals representing hand postures might be better suited to controlling neuroprosthetics. “

For this study, the researchers worked with rhesus monkeys (Macaca mulatta). Like humans, they have a highly developed nervous and visual system as well as pronounced fine motor skills. This makes them particularly suitable for researching gripping movements.

To prepare for the main experiment, the scientists trained two rhesus monkeys to move the hand of a virtual avatar on a screen. During this training phase, the monkeys performed the hand movements with their own hand while simultaneously seeing the corresponding movement of the virtual hand on the screen. A data glove with magnetic sensors, which the monkeys wore during the task, recorded the animals’ hand movements.

Once the monkeys learned the task, they were trained to control the virtual hand in a next step by “imagining” the grip. The activity of populations of neurons in cortical areas of the brain that are specifically responsible for controlling hand movements was measured.

The researchers focused on the signals that represent the different postures of the hands and fingers and adapted the brain-computer interface algorithm, which translates neural data into movement, into a corresponding protocol.

“By deviating from the classic protocol, we adapted the algorithm so that not only the destination of a movement is important, but also the way in which we get there, that is to say the execution path”, explains Agudelo-Toro. “This ultimately led to the most accurate results.”

The researchers then compared the avatar’s hand movements with the real hand data they had previously recorded and were able to show that these were executed with comparable precision.

“In our study, we were able to show that signals that control the posture of a hand are particularly important for controlling a neuroprosthesis,” explains Hansjörg Scherberger, head of the neurobiology laboratory and lead author of the study.

“These results can now be used to improve the functionality of future brain-computer interfaces and thus also to improve the fine motor skills of neural prostheses.”