A low-cost, soft exoskeleton glove, controlled by muscle signals, offers new hope for grasping movement in paralysis.
Breakthrough Glove Uses Muscle Signals to Restore Grip
A team at the Institute for Cognitive Systems has developed a soft-hand exoskeleton in the form of a glove that assists people with paralysis. The device uses electromyography (EMG) signals from the thumb muscle to predict grasping movements with 97% reliability.
Built from Low-Cost Materials
The glove, sewn by the researchers, is made of low-cost fabric. The development involved close collaboration with a patient with amyotrophic lateral sclerosis (ALS) who retained movement in the first thumb joint.
How It Works
A sensor on the forearm detects signals from the flexor pollicis longus muscle. These signals trigger the inflation of air cushions in the glove, enabling the grasping motion.
“The glove uses electromyography (EMG) signals from the thumb muscle to predict grasping movements with 97% reliability.”