Jan Scheuermann, a Pennsylvania wife and mother of two, always enjoyed a good murder. She wrote and produced hundreds of murder-mystery parties, eventually turning her scripts into a novel complete with a spunky, sleuthing heroine.
But in 1998, a real tragedy struck Jan, eventually leaving her paralyzed from the neck down.
After a bit of detective work themselves, doctors identified the culprit — spinocerebellar degeneration.
Spinocerebellar degeneration is a diverse group of rare, slowly progressive, not completely understood neurological diseases that affect a region of the brain called the cerebellum and its related pathways. These diseases cause nerves in the cerebellum to deteriorate and die, leading to impaired balance; a wide-legged, unsteady, lurching walk; tremors; slow, unsteady, jerky movements of the arms or legs; slurred speech; incoordination; and nystagmus, a condition of involuntary eye movement and impaired vision. There is no cure for these disorders and the gradual loss of muscle function is devastating.
“The challenges of not being able to walk or feed myself, being dependent on others, those are not as hard as the emotional challenges, when I couldn’t cook breakfast for my kids anymore,” Scheuermann said in an interview with KDKA, the Pittsburgh CBS station.
However, hope came in the form of a study involving a brain-computer interface (BCI) that would link her mind to a humanlike robotic arm, allowing her to control it and regain some independence.
The first step was to implant two square-shaped microelectrode arrays into the motor cortex of her brain that controls the movement of her right arm and hand. Two cables attach to the electrodes. One cable plugs into the robotic arm’s computer. The other cable connects to a device that detects and records her brain activity.
Scheuermann went to four-hour training sessions three times per week for 13 weeks. She learned to use the arm, which she named Hector, more quickly than researchers anticipated.
By the second day of training, she was able to manipulate the prosthetic limb in a three-dimensional work space. The movement of the arm under her control gradually improved to the point that she accurately reached for, grasped, adjusted and moved objects of various sizes and shapes.
By the end of training, she was able to complete 91 percent of tasks she attempted and performed them more quickly than when she started. Her first goal was to feed herself a bit of chocolate.
BCI relies on complex equations called algorithms to map out the brain signals that correspond to physical movements. For Scheuermann, the team developed a unique algorithm that very closely resembles how the brain actually works to control and operate upper limbs.
While this level of sophisticated and unprecedented control is confined to a lab, it offers great future hope for paralysis patients.