Smartwatch data predicts Parkinson’s diagnosis

The neurodegenerative disorder can be predicted early thanks to AI and data from smartwatches
Smartwatch data predicts Parkinson’s diagnosis
AI and Parkinson's diagnosis

Research has shown that AI and data collected from smart watches can identify Parkinson’s disease early on, as much as seven years before symptoms start to show. The longitudinal research study, published in Nature Medicine, primarily took place between 2013 and 2016 and collected data from more than 103,000 people who were fitted with a medical-grade wearable for seven days.

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The medical-grade wearables continuously measured the speed of the participants’ movement. Movement data and speed of movement, along with shaking and stiffness, are symptoms of the condition, and immediate indicators on the likelihood of a diagnosis.

Parkinson’s is a progressive neurological condition, caused by a combination of age, genetics, and environment. Although many of the symptoms are physical, such as slow movement, shaking, and stiffness, psychological symptoms can include depression and memory issues.

The research, which took place at Cardiff University’s Neuroscience and Mental Health Innovation Institute (NMHII) compared the data gathered over three years with the state of the participants seven years later. They were able to cross-reference the data, and distinguish between those that were healthy with those that went on to develop Parkinson’s.

Dr. Kathryn Peall of the NMHII explained that the movement speed data was a huge indicator of the condition, and could therefore be used to identify those that may be likely to develop the condition. The timeframe could also be derived.

With early detection, those diagnosed with Parkinson’s are able to access more effective treatment options. The smartwatch is a low-cost, accessible accessory that can safeguard the present and future health of people, and identify those at risk.

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