Smartwatches that can collect physical and physiological data on users could be potentially interesting tools in biomedicine to gain a better understanding of brain diseases and behavioral disorders and possible driver mutations related to these pathologies. This is stated in a study published in the journal Cell, and led by the co-author Mark Gerstein, from Yale University (United States). The study includes the participation of Professor Diego Garrido MartĂn, from the Department of Genetics, Microbiology and Statistics of the Faculty of Biology at the University of Barcelona.
Using smartwatch data from more than 5,000 adolescents, the research team could train artificial intelligence models to predict whether individuals had different psychiatric illnesses and found genes associated with these illnesses. The results suggest that these wearable sensors may enable a much more detailed understanding and treatment of psychiatric illnesses.
In traditional psychiatry, a doctor will assess your symptoms and you’ll either be diagnosed with an illness or won’t. But in this study, we focused on processing the wearable data in a way that could both be leveraged to predict illnesses more comprehensively, and to better connect them to underlying genetic factors”.
Professor Mark Gerstein, expert in biochemistry, computer science, statistics and data science
Detecting illnesses in such a quantitative way is difficult. But wearable sensors, which collect data continuously over time, may be the answer. For the new study, the team used data from the Adolescent Brain Cognitive Development Study, the largest long-term assessment of brain development and child