“The reason people with diabetes live shorter lives is because they are at much higher risk of developing heart problems,” says Wamil. “We hope that in the future this data can be used to detect early signs to alert the patient and doctor about their future risk of heart attack and stroke.”

Predicting neurological problems

But many applications of smartwatches could extend far beyond the heart. In July 2023, researchers at Cardiff University published a study using data from over 100,000 people, who were given a smartwatch to wear for a week. The results showed that it was possible to identify individuals with signs of Parkinson’s disease up to seven years before their clinical diagnosis. This was achieved by detecting subtle anomalies in their walking patterns, as measured by the watch’s motion sensors.

Cynthia Sandor, who directed the studybelieves it might be possible to identify these signs even earlier by combining movement data with other smartwatch measurements such as sleep quality, which is known to be disrupted in people who develop disease.

“In Parkinson’s disease, diagnosis is preceded by a long phase during which signs such as subtle motor changes become apparent,” says Sandor. “We found that the most predictive feature was a slowing of movements during light physical activity, too subtle to be noticed by the individuals themselves.”

Sandor believes this information could soon be used to recruit individuals for clinical trials. One theory as to why effective treatments for Parkinson’s disease have proven so elusive is that patients are diagnosed at a stage when significant brain damage has already occurredand it may be easier to slow or even reverse the disease at an earlier stage. “We hope that early detection tools based on smart watch data can identify people at an early stage, which could enable successful trials of neuroprotective treatments,” she says.

There is also hope that smartwatches could one day soon help people living with chronic illnesses such as epilepsy, by providing warning signs that a seizure is about to occur. Falls and serious accidents following convulsions are known risk factors for those living with epilepsy.

“Uncertainty about when seizures might occur is one of the most difficult aspects of living with epilepsy,” says Aileen McGonigal from the Queensland Brain Institute. “Forecasts regarding seizures, however, are still in their early stages.”

McGonigal wants to know if a special prototype version of the Empatica Smart Watch designed for research can help predict seizures. In a current research projectit applies AI algorithms to a combination of data streams. These include heart rate variability, skin temperature, body movements, and changes in skin electrical conductance due to sweating, which reflects alterations in the body’s autonomic nervous system. Each of these parameters can be measured by the watch.

“We aim to analyze trends in the hours before seizures,” says McGonigal. “Ideally, epilepsy researchers and clinicians would like patients to be able to predict when seizures are more likely to occur, which could allow treatment to be tailored, including varying doses of medication and tailoring. daily activities to reduce the risk of falls and seizure-related injuries,” she says.

But while there is considerable excitement about what the combination of powerful AI algorithms and increasingly precise wearable measurements could achieve, some doctors are also cautious about the results they will achieve. the potential for false positives. There are concerns that the overuse of smartwatches will lead to an increase in the number of people. patient anxietyas well as testing the resources of already overburdened health systems.