Researchers Seek to Control Prosthetic Legs With Neural Signals

Most people don’t think about the difference between walking across the room and walking up a flight of stairs. Their brains (and their legs) automatically adjust to the new conditions. But for people using prosthetic legs, there is no automatic link between their bodies and the prosthetics that they need to negotiate the new surroundings.

Researchers from NC State and the University of Houston (UH) are hoping to change that with a new four-year, $1.2 million collaborative project funded by the National Science Foundation (NSF).

“Our goal is to improve mobility for people using prosthetics, lay the groundwork for a new generation of prosthetic devices and improve our understanding of how brain signals and neuromuscular signals are coordinated,” says Helen Huang, principle investigator (PI) of the NSF grant and an associate professor of biomedical engineering at NC State and UNC.

In recent years, researchers have developed powered prosthetic devices that use internal motors to improve the motion of the artificial limb. The goal of the NSF project is to improve the connection between the prosthetic and the person using it.

Huang’s team will be using sensors to pick up the neuromuscular control signals from residual muscles in the area where the prosthetic is connected to its user. Huang’s goal is to develop an algorithm that translates those neuromuscular signals into machine language that will control the powered prosthesis – making it easier for the user to move seamlessly from standing up, to walking across the room, to climbing the stairs.

Huang’s team also plans to build a prototype power prosthesis that incorporates the new technology. This aspect of the research builds on Huang’s previous experience in designing and fabricating power prosthetics.

Huang’s co-PI on the project, Jose ‘Pepe’ Contreras-Vidal of UH, will be exploring ways to use neurological signals from the brain to control prosthetic legs. This is particularly important for patients who have little or no residual muscle in the area of the missing limb, because that lack of muscle makes it difficult to pick up neuromuscular signals. In those cases, signals picked up directly from the brain may be able to control the prosthetics.

“Ultimately, we’d like to combine both approaches, using signals from the muscles and the brain to provide better control of lower-body prosthetics,” Huang says.