Artificial intelligence makes gripping more intuitive

Scientist Patricia Capsi-Morales shows the film she uses for her research. Current hand prostheses already work with the help of an app or sensors attached to the forearm. New research at the Technical University of Munich (TUM) shows this: A better understanding of muscle activity patterns enables more intuitive and natural control of the prostheses. This requires a network of 128 sensors and the use of artificial intelligence . Different types of grippers and bionic design: technological developments have continuously improved hand prostheses in recent decades. Anyone who has lost a hand due to an accident or illness can at least perform some everyday movements again. Some modern prostheses can already be used to move the fingers or rotate the wrist. This requires either a smartphone app or muscle signals from the forearm, which are usually detected by two sensors. For example, by activating the flexor muscle in the wrist, the fingers of the artificial hand can be closed to grip a pen. If the extensor muscle in the wrist is contracted, the hand releases the pen again. If both muscles are contracted at the same time, certain fingers can be moved. "A patient has to learn these movements during rehabilitation," says Cristina Piazza, Professor of Healthcare and Rehabilitation Robotics at TUM. Her research team has now shown that artificial intelligence can help to use a prosthetic hand more intuitively than before. The secret lies in the "synergy principle" and the support of 128 sensors on the forearm. The synergy principle: the brain activates a group of muscle cells . What is the synergy principle?