Modern bionic hand prostheses nearly match their natural counterparts when it comes to dexterity, degrees of freedom, and capability. And many amputees who tried advanced bionic hands apparently didn’t like them. “Up to 50 percent of people with upper limb amputation abandon these prostheses, never to use them again,” says Jake George, an electrical and computer engineer at the University of Utah.
The main issue with bionic hands that drives users away from them, George explains, is that they’re difficult to control. “Our goal was making such bionic arms more intuitive, so that users could go about their tasks without having to think about it,” George says. To make this happen, his team came up with an AI bionic hand co-pilot.
Micro-management issues
Bionic hands’ control problems stem largely from their lack of autonomy. Grasping a paper cup without crushing it or catching a ball mid-flight appear so effortless because our natural movements rely on an elaborate system of reflexes and feedback loops. When an object you hold begins to slip, tiny mechanoreceptors in your fingertips send signals to the nervous system that make the hand tighten its grip. This all happens within 60 to 80 milliseconds—before you even consciously notice. This reflex is just one of many ways your brain automatically assists you in dexterity-based tasks.
Most commercially available bionic hands do not have that built-in autonomic reflex—everything must be controlled by the user, which makes them extremely involved to use. To get an idea of how hard this is, you’d need to imagine trying to think about precisely adjusting the position of 27 major joints and choosing the appropriate force to apply with each of the 20 muscles present in a natural hand. It doesn’t help that the bandwidth of the interface between the bionic hand and the user is often limited.
In most cases, users controlled bionic hands via an app where they could choose predetermined grip types and adjust forces applied by various actuators. A slightly more natural alternative is electromyography, where electric signals from the remaining muscles are in commands the bionic hand followed. But this too was far from perfect. “To grasp the object, you have to reach towards it, flex the muscles, and then effectively sit there and concentrate on holding your muscles in the exact same position to maintain the same grasp,” explains Marshall Trout, a University of Utah researcher and lead author of the study.