• Smartwatch detects early signs of Parkinson’s disease
• Slower movement patterns may indicate Parkinson’s risk
• Smartwatch data can help identify individuals for clinical trials

A smartwatch could detect Parkinson’s disease up to seven years before the onset of crucial symptoms.

People who are destined to develop Parkinson’s disease are slower for years before diagnosis, not only in terms of their walking speed but also in terms of mild physical activity, such as cleaning, making the bed, or rising to make a cup of tea.

In a week-long UK study, 103,712 people wore a wrist-worn tracker like a smartwatch.

The medical-grade tracker was unable to distinguish how individuals moved during specific everyday activities, such as housework. But it did record the average speed of their daily movements.

individuals who went on to develop Parkinson’s disease moved significantly more slowly between 7 am and midnight, on average, than individuals of the same age and gender who also wore a fitness tracker but did not develop Parkinson’s disease.

The study does not suggest that a smartwatch can predict Parkinson’s disease risk. Movement data is not precise enough for this purpose.

However, it could be used to identify those in a cohort who may be at greater risk.

This could allow this group to participate in clinical studies before the disease destroys many brain cells.

This would show if innovative medications could save brain cells, expediting Parkinson’s disease treatment.

The condition, which affects Billy Connolly and Jeremy Paxman, has no treatment.

Dr. Cynthia Sandor of the UK Dementia Research Institute at Cardiff University, who led the study, stated, “Smartwatch data is readily accessible and inexpensive.

By the year 2020, approximately 30% of the UK population will be wearing smart devices.

This data may help us identify early-stage Parkinson’s patients in the general community.

We have demonstrated that a single week’s worth of data can predict events as far out as seven years.

The study, which was published in Nature Medicine, compared movement-tracking data analyzed by artificial intelligence to four other methodologies for detecting Parkinson’s disease before its onset.

The movement data performed better than examining people’s genes and family history, the chemical composition of their blood, hazardous lifestyle factors such as smoking and drinking, and other early medical indicators such as loss of smell and urinary incontinence.

The UK Biobank study followed 40-69-year-olds who wore movement trackers for a week.

This included 196 individuals who developed Parkinson’s disease more than two years after monitoring their sedentary behavior, mild, moderate, and vigorous physical activity and sleep with a tracker.

Besides being slower during the day, Parkinson’s patients slept longer and woke up more often.

Beneficially, in the real world, where various age-related diseases can exhibit similar early symptoms. This was not observed in individuals who developed dementia or osteoarthritis.

This indicates that smartwatch data can effectively identify individuals at risk for Parkinson’s disease.

Dopaminergic neurons, which are located in the substantia nigra, are affected by Parkinson’s disease.

It results in motor symptoms such as tremors, rigidity, and sluggishness.

A new study found that many become subtly lethargic years before seeking medical attention.

This could allow their risk of developing Parkinson’s disease to be detected before the typical period of diagnosis – when up to 70% of substantia nigra cells have already been lost.