In the study published in the Journal of Neurophysiology, they placed between 79-128 electrodes from the EMG onto the chest muscles of five patients to see if they could identify the unique EMG patterns emitted with 16 different elbow, wrist, hand, thumb and finger movements they asked the patients to perform. The EMG signals from each of the 16 movements were analyzed using advanced signal processing techniques. The study found that the researchers could recognize the signals associated with the different arm movements with 95% accuracy.
The next step is to use this information to program these new moves into the microprocessor of the artificial arm, so that instead of just opening and closing a hand and bending and straightening an elbow, now the signals can produce various hand grasp patterns, such as the one needed to hold a baseball, pick up a pen or grasp a tool.
May benefit soldiers
Kuiken and his colleagues have begun to work with the military at Brooke Army Medical Center at Fort Sam Houston in Texas and the Walter Reed Army Hospital in Washington, D.C. to apply this technology to soldiers who have lost limbs.
Were excited to move forward in doing this surgery with our soldiers some day, he said. Weve been able to demonstrate remarkable control of artificial limbs and its an exciting neural machine interface that provides a lot of hope.
There are a couple of additional things to note in the work of Kuiken and his colleagues: They performed nerve transfer surgery 9-15 months after the injury that led to amputation, showing that these neural pathways remain intact, even when they have not been used for awhile.
Also, when the researchers touch these patients on their chests, the patients say it feels like they are being touched somewhere on their arm or hand -- the arm or hand that is no longer there. Thats not real
|Contact: Christine Guilfoy|
American Physiological Society