Investigation of Sleep and Sedentary Patterns in Adults Using Data-Driven Models and Actigraphy

This study examines sleep and sedentary patterns among individuals with acute and chronic insomnia. Machine learning is used to distinguish between chronic insomnia and acute insomnia with 81% accuracy. Findings reveal differences in sleep patterns between insomnia and their healthy counterparts. In addition, it reveals an association between sedentary behaviour and poor sleep quality.<p></p>