New machine learning algorithms and computational models may provide insight into the mental demand placed on individuals using prosthetics. These models will improve the current interface in prosthetic devices.

The researchers are studying prosthetics that use an electromyography (EMG)-based human-machine interface. EMG is a technique that records the electrical activity in muscles. This electrical activity generates signals that trigger the interface, which translates them into a unique pattern of commands. These commands allow the user to move their prosthetic device.

Testing different interface prototypes through virtual reality and driving simulations will allow researchers to provide guidance to the engineers creating these interfaces. This will lead to better prosthetics for amputees and other technological advances using EMG-based assistive human-machine interfaces.

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