Smart watches have become one of the usual accessories on the wrists of a large part of the population. They are no longer just a gadget for athletes or a perfect Christmas gift for a family member. Its benefits have multiplied over the years and the monitoring of different health constants helps us monitor our heart rate, breathing or the quality of our sleep. New research has gone a bit further, stating that smartwatches could help identify the onset of Parkinson’s disease up to seven years before characteristic symptoms appear and a clinical diagnosis can be made.
In this new study published in the journal Nature Medicine, and led by scientists at the UK Dementia Research Institute and the Neuroscience and Mental Health Institute for Innovation (NMHII) at Cardiff University, scientists analyzed data collected by smart watches over a period of 7 days to measure the movement speed of the participants. They found that they could accurately predict, using artificial intelligence (AI), who would later develop Parkinson’s disease.
The researchers say this could be used as a new screening tool for Parkinson’s disease, allowing the disorder to be detected at a much earlier stage than current methods allow.
Parkinson’s affects brain cells called dopaminergic neurons, located in an area of ​​the brain known as the substantia nigra. It causes motor symptoms such as tremor, rigidity (stiffness), and slowness of movement. By the time these hallmark symptoms of Parkinson’s begin to show and a clinical diagnosis can be made, more than half of the cells in the substantia nigra will already have died. Therefore, there is a need for cheap, reliable and easily accessible methods to detect changes early so that intervention can be made before the disease causes extensive damage to the brain.
Data from smartwatches could provide an early detection tool for the disease. As new treatments begin to emerge, people will be able to access them before Parkinson’s causes extensive damage to the brain.
To this end, the researchers analyzed data collected from 103,712 UK Biobank participants who wore a medical-grade smartwatch over a 7-day period between 2013 and 2016. The devices measured average acceleration, that is, the speed of movement, continuously for the period of one week. They compared data from a subset of participants who had already been diagnosed with Parkinson’s disease, with another group who received a diagnosis up to seven years after the smartwatch data was collected. These groups were also compared with healthy people of the same age and sex.
The researchers demonstrated that, using AI, it is possible to identify participants who would later develop Parkinson’s disease from data obtained with wearable technology that tracks the accelerometer on their smartwatch. Not only could these participants be distinguished from healthy controls in the study, but the researchers later expanded on this to show that AI could be used to identify people who would later develop Parkinson’s in the general population. They found that this was more accurate than any other risk factor or other recognized early sign of the disease in predicting whether someone would develop this neurodegenerative disorder. The model was also able to predict the time to diagnosis.
Anticipating the diagnosis would allow treating Parkinson’s at an earlier stage
One limitation of the study is the lack of replication using another data source, as there are currently no other comparable data sets that would allow for similar analysis. However, a thorough evaluation was carried out to mitigate any bias. Lead study author Dr Cynthia Sandor, from the UK Dementia Research Institute at Cardiff University, said: “Data from smartwatches is easily accessible and low cost. As of 2020, about 30% of the population already used smartwatches. Using this type of data, we could potentially identify people in the early stages of Parkinson’s disease within the general population.”
“We have shown here that a single week of captured data can predict events up to seven years in the future. With these results we could develop a valuable screening tool to aid in the early detection of Parkinson’s disease. This has implications for both the research, to improve recruitment into clinical trials, as well as clinical practice, by allowing patients to access treatments earlier, in the future, when such treatments become available.”
Dr Kathryn Peall, a senior clinical professor at Cardiff University’s NMHII, said: “For most people with Parkinson’s disease, by the time they start experiencing symptoms, many of the affected brain cells have already been lost. This means early diagnosis of the condition is challenging.Although our findings here are not intended to replace existing diagnostic methods, data from smartwatches could provide a useful screening tool to aid in early detection of the disease. This means that as new treatments begin to emerge, people will be able to access them before the disease causes extensive damage to the brain.”
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