Investigating the Relationship Between Depression and Sleep Cycle: A Data-Driven Analysis

Depression and sleep disturbances share a bidirectional relationship that significantly impacts mental health and daily functioning. This research project aims to investigate the correlation between depression severity and sleep cycle patterns using data analysis techniques. Through a combination of psychological assessment tools and sleep tracking data, this study will identify key patterns, such as changes in REM sleep, sleep duration, and sleep onset latency among individuals experiencing depressive symptoms. The goal is to use statistical and machine learning approaches to uncover insights that may aid early detection and treatment strategies for depression.