For those without hands, there's Air Guitar Hero

Rehabilitation specialists have taken to Nintendo’s Wii game console as a way to help motivate patients during physical therapy and rehabilitation. The latest addition to the Wii-hab phenomenon is perhaps its coolest—Air Guitar Hero. Researchers at Johns Hopkins University have made the popular Guitar Hero game into a tool for amputees who are being fitted with the next generation of artificial arms. With a few electrodes and some very powerful algorithms, amputees can hit all the notes of Pat Benatar’s “Hit Me With Your Best Shot” using only the electrical signals from their residual muscles.

The new research, which will be presented this Friday at the IEEE Biomedical Circuits and Systems Conference, in Baltimore, is one component of a program sponsored by the U.S. Defense Advanced Research Projects Agency (DARPA). The Revolutionizing Prosthetics (RP) 2009 project, spread over 30 research institutions worldwide and led by the Johns Hopkins University Applied Physics Laboratory (APL), in Laurel, Md., is developing a mechanical arm that closely mimics the properties of a real limb.

Besides developing two prototype mechanical arms, the project has also pioneered a nerve surgery for controlling the limbs. The nerves that once controlled an amputee’s arm are still intact even after the limb is lost. By rerouting these nerves into the chest muscles and affixing electrodes to pick up the electromyographic (EMG) signals, the RP 2009 researchers were able to use those signals to control a mechanical arm. As a result, the user feels as if he were controlling his own arm.

Though the surgery has worked so far to move an arm with six degrees of freedom, that arm still cannot enable individual finger movement—the ultimate goal of the project.

Dexterous motion of individual fingers poses a tricky software problem. To establish a clear link between mind and machine, the software that translates between EMG signals and the mechanical arm must be trained to understand what the different muscle signals mean. Pattern-recognition algorithms have to be trained by correlating input signal patterns (from muscle contractions) with the intended outputs (opening the mechanical index finger).

Read more on IEEE Spectrum Online