Can sleep quality be used to predict stress vulnerability?

Roee Admon, School of Psychological Sciences, and Pavel Goldstein, School of Public Health, University of Haifa, Haifa, Israel

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This project aims to identify biomarkers of resilience vs. vulnerability to stress, based on physiological data that is acquired passively using wearable sensors during sleep. The identification of biomarkers could help develop personalized treatment plans for preventing stress psychopathology. More than 150 healthy adult participants have already completed the study and a machine learning model was able to predict variability in their stress levels with 80% accuracy based on their physiological data. Current efforts are directed towards acquiring data from psychopathological populations.

 

 

 

 

 

 

 

 

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