The goal of this project is to develop a predictive model that analyzes children's physical activity and fitness data to identify early signs of problematic internet use. Identifying these patterns can help trigger interventions to encourage healthier digital habits.

Python package for preprocessing, modeling, and analyzing actigraphy time series.

Study Title: Insights from nine nights of self-applied, low-density sleep EEG during sleep restriction therapy: a proof-of-concept evaluation. Analysis of the RESTORE study: a pilot feasibility study of wearable technology in participants with insomnia and depression.

📊 Analyze children's activity data to predict and address problematic internet use, fostering healthier digital habits through early intervention.