Sirwan Darweesh, from the Department of Neurology at the Eramus University School of Medicine in Rotterdam (The Netherlands) has spent years studying the onset and evolution of Parkinson’s. In 1990, researchers from the university began a very ambitious study to follow the health of all the inhabitants over 55 years of age in Ommord, a neighborhood in the Dutch city. Within this work, Darwesh focused on a hundred people who ended up being diagnosed with Parkinson’s. Based on his research, Darwesh can say that “the pathology of the disease begins more than two decades before a clinical diagnosis can be made. The first symptoms usually appear 10 years before diagnosis.” Darwesh agrees with Grandas that Parkinson’s is being diagnosed too late: “Disease-modifying therapies are ineffective in the clinical phase of Parkinson’s. The likely reason is that the pathology of the disease is already too advanced at that stage, as more than 60% of the key dopaminergic brain cells have already been depleted by the time the diagnosis is made.”

One of the weaknesses of the new research is that the smartwatches only recorded activity for a week, but if it were applied in a real environment, the collection of data over time could refine the warning signals. Before Sandor’s current work, a group of scientists in the United States used artificial intelligence to detect patterns in data from smartwatches. They also used the sample from the UK Biobank, but they started with the data of patients who had already diagnosed with Parkinson’s. One of the authors of this research is neurologist Karl Friedl. For him, a full week of sampling movement patterns is enough “to be able to detect someone who is going to have Parkinson’s.” From a broader point of view, “we can help people discover many important characteristics of their health and well-being through the way they move,” adds Friedl. “If we add to it all the other prodromal features that are emerging related to Parkinson’s [anosmia, REM sleep disturbance, depression], the predictive algorithms in our new AI world will become very powerful,” he concludes.

Indeed, the smartwatch study also obtained data on sleep patterns, in this case using a sample of 65,000 people. Again, artificial intelligence was able to detect a decrease in the duration and quality of sleep, both in those diagnosed with Parkinson’s when their activity was recorded and in those who were diagnosis years later. “The smartwatches tell us that people wake up more frequently at night and experience longer sleep duration several years before a Parkinson’s diagnosis,” says Sandor. Combined with daytime and nighttime data, the accelerometers could give doctors time to try to curb the disease.