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Concept breakdown of the robotic arm system (via Lancet & the Guardian)

 

I never bought that IQ tests were the ultimate measure of intelligence. A paraplegic woman  has shown that she has an almost genius-like affinity towards learning how to move a robotic arm with only her thoughts, blowing away researchers with her fast progress.

 

 

Jan Scheuermann, now 52 years old, was a business owner in California, when at age 36, she noticed that she was beginning to lose control of her legs. Just six year after, she had lost all movement of her body below her neck due to a spinocerebellar degenerative disease that damaged the connection between her brain and spinal cord.

 

 

In 1998, she returned to her hometown of Pittsburgh, PA, but it was not till 2011 that a friend told her about exciting medical experiments being done at the University of Pittsburgh Medical Center (UPMC) that aimed to help those with quadriplegia. She immediately jumped at the opportunity to be submitted to some experiment.

 

 

Luckily for her, the UPMC was looking for patients to try a new brain-computer interface (BCI, also referred to as a brain-machine interface or a brain-controlled interface) that would allow a paraplegic or quadriplegic patient to control a robotic arm with only their thoughts. This procedure would involve invasive surgery. Before it took place, Scheuermann declared she would feed herself a bar of chocolate before the experiment was over; a feat she has not accomplished in 10 years.

 

 

So the process began by implanting two 4mm^2 microelectrode chips, each containing 96 electrodes, directly over the left motor cortex. Each of these electrodes measure just 1.5mm, and they penetrated just under the surface of the brain. The piece of her skull, which had to be removed for the implant, was put back, but this time, Scheuermann had wires sticking out of her head that connected the electrodes to the computer interface. The BCI was designed to filter and interpret neuron signals, in real-time, using functional magnetic resonance imaging and complex algorithms developed by researcher and professor of neurology, Andrew Schwartz, and his team.

 

 

When she woke, she was connected to the BCI and was told to imagine she was moving her arm, wrist and hand. The researchers were pleased to see the different groups of neurons firing with different motions Scheuermann imagined.

 

 

The robotic arm, whom Scheuermann called Hector, was designed to have 7 degrees of freedom. It moves up and down, side-to-side, forward and backward, control the pitch, yaw and roll of the wrist and open and close the hand. 

 

 

The UPMC system is innovative in that it allows users to use more general thoughts in controlling the robotic arm. Instead of focusing on spatial positioning, patients can think of tasks like “grab the chocolate” and the natural neural messages that would normally accomplish that task are the ones used to direct the robotic arm. Researchers hope this will make the system more intuitive and easier to use.

 

 

With in just two days, Jan could move the arm in all six spatial directions. After three weeks, she could position it in more particular orientations to grab things like cones, blocks and small objects and move them to a desired space. Researchers thought these tasks would take months. After three months, the BCI better ignored false signals and Jan was able to perform 91.6% of all tasks while completing them 30 seconds faster than she initially could.

 

 

Eventually, her performance plateaued partially due to scar tissue that formed on the tips of the electrodes that impeded the clear transmission of neuron signals to the BCI. Researchers will improve future iterations of the system by using electrodes that are 5 thousandths of a millimeter that would not trigger the scarring process.

 

 

In the future, apart from thinner electrodes, the UPMC wants to make the system wireless. Schwartz also said future systems might include electrodes in different parts of the brain with the ability to transmit texture and temperature from the robot arm to the user’s brain.

 

 

With regard to the innovative UPMC system, Dr. Michael Boninger, a fellow UPMC researcher said, “The biggest change is the sophistication with which we’ve learned to interpret electrical activity in the brain.” As for Scheuermann, she said, “I keep saying this is the rollercoaster, this is the skydiving. It’s just fabulous and I’m enjoying every second of it. This is the ride of my life.”

 

 

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