145,000 people in the UK are currently living with Parkinson’s, and according to Parkinson’s UK, 1 in 37 people alive today will be diagnosed with it in their lifetime.
Parkinson’s is a condition in which parts of the brain become progressively damaged over many years, with the main characterising symptoms being tremors in parts of the body and issues with mobility.
People living with Parkinson’s may not notice symptoms initially, but as it progresses, people who are experiencing it may have difficulty with walking or speaking. It is also difficult to diagnose given that, according to the NHS, no tests can conclusively show that you have Parkinson’s. Instead, doctors base a diagnosis on symptoms, medical history and a detailed physical examination.
However, with early intervention, the progression of Parkinson’s and the symptoms that people experience can be managed effectively, and much like other conditions, early detection is essential.
Given how difficult diagnosing Parkinson’s can be, this isn’t always possible, but new research led by scientists at UK Dementia Research Institute and Neuroscience and Mental Health Innovation at Cardiff University has provided hope for the future of Parkinson’s diagnosis.
AI could be the future of Parkinson’s diagnosis
The study, which was conducted between 2013 and 2016 and collected data from 103,712 people who wore a medical-grade smartwatch for a seven day period. The watches collected the average speed of each participant, comparing that data with patients who had already been diagnosed with Parkinson’s. This AI model was further able to predict a timescale.
Researchers are hopeful that this technology could be used as a future screening tool that would potentially lead to earlier detection and intervention of Parkinson’s. As around 30% of the population wore smartwatches, study leader Dr Cynthia Sandor, speaking to the BBC said, they might offer a cheap and reliable way to identify early-stage Parkinson’s.
“We have shown here that a single week of data captured can predict events up to seven years in the future,” she said.
Dr Kathyrn Peall, who worked on the study said, “We compared our model across a number of different disorders, including other types of neurodegenerative disorders, individuals with osteoarthritis, and other movement disorders, amongst others, an advantage of being able to work with a dataset such as the UK Biobank,” she said.
“The results from individuals diagnosed with Parkinson’s disease were distinct.”
But whether people should be told they had Parkinson’s, years before symptoms developed, “will always remain an individual and personal choice”.
“Where this work is potentially important to the field is that we ultimately hope that new therapies that allow us to slow disease progression will become available,” Dr Peall added.