In a new frontier for deep brain stimulation, researchers used AI to develop individualised algorithms, which helped a skateboarder and other patients with Parkinson’s disease. When Shawn Connolly was diagnosed with Parkinson’s disease nine years ago, he was a 39-year-old daredevil on a skateboard, flipping and leaping from walls, benches and dumpsters through the streets of San Francisco. He appeared in videos and magazines, and had sponsorships from skateboard makers and shops.
But gradually, he began to notice that “things weren’t really working right” with his body. He found that his right hand was cupping, and he began cradling his arm to hold it in place. His balance and alignment started to seem off.
Over time, he developed a common Parkinson’s pattern, fluctuating between periods of rapid involuntary movements like “I’ve got ants in my pants” and periods of calcified slowness when, he said, “I could barely move”. A couple of years ago, Connolly volunteered for an experiment that summoned his daring and determination in a different way. He became a participant in a study exploring an innovative approach to deep brain stimulation.
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