Smartwatches equipped with artificial intelligence (AI) algorithms can detect the early signs of Parkinson’s disease up to seven years before symptoms become evident, according to a groundbreaking UK study. The research, conducted by scientists at Cardiff University, suggests that analyzing data collected by smartwatches over a seven-day period can provide valuable insights into the development of Parkinson’s disease.
A key feature of Parkinson’s disease is the gradual loss of dopamine-producing brain cells, which leads to motor symptoms such as tremors and slower movement. Detecting the disease early is challenging, as by the time symptoms manifest, a significant number of brain cells have already been lost. However, the study led by Dr. Kathryn Peall, a clinical senior lecturer at Cardiff, indicates that smartwatches can address this issue by tracking movement speed.
To investigate this further, the researchers analyzed information from over 500,000 individuals aged between 40 and 69. They compared data on movement speed, known as accelerometery, with genetic profiles, lifestyle factors, blood biochemistry, and early-stage Parkinson’s symptoms. They then trained AI software to analyze the movement speed data, enabling it to accurately identify both clinically diagnosed Parkinson’s patients and individuals at an earlier stage of the disease.
Importantly, the researchers believe that the findings are unique to Parkinson’s disease, as they did not observe similar movement speed patterns in individuals with other disorders. Cynthia Sandor, a researcher from Cardiff’s Dementia Research Institute, emphasized the potential of accelerometery to identify individuals at an elevated risk of developing Parkinson’s disease on a large scale. She highlighted the fact that smart devices capable of collecting accelerometer data, such as activity trackers and smartwatches, are already worn daily by millions of people.
While further research is needed before these findings can be translated into clinical practice, the discovery marks a significant leap forward in the early diagnosis of Parkinson’s disease. Sandor suggests that smart devices like smartwatches and activity trackers could play a crucial role in monitoring individuals for signs of Parkinson’s disease. Their widespread use and accessibility make them ideal tools for continuous monitoring, which has been historically challenging due to the associated costs, time requirements, and sensitivity.
This study has the potential to revolutionize the early detection and management of Parkinson’s disease, offering more effective treatment options and improved patient outcomes. By harnessing the power of AI and utilizing the data collected by smartwatches, researchers can identify individuals at risk long before symptoms become apparent. While there is still much work to be done, this groundbreaking research paves the way for a future where wearable technology plays a vital role in healthcare, helping to detect and diagnose debilitating diseases at an early stage.
