Sleep and Health Metrics Dataset

Dataset Description

The dataset comprises a rich assortment of simulated measurements. Designed to capture the complexity of sleep-related behaviors and health metrics:

• Heart Rate Variability (HRV): Simulated data representing the variability in intervals between heartbeats. A crucial indicator of autonomic nervous system function.
• Body Temperature: Artificially generated data on body temperature measured in degrees Celsius. Reflecting typical fluctuations that occur during sleep and waking hours.
• Movement During Sleep: Synthetic data capturing the frequency and intensity of movements throughout the sleep cycle. Offering insights into restlessness and potential sleep disturbances.
• Sleep Duration (Hours): The total number of hours slept. Simulated to reflect a range of sleep durations, from insufficient to optimal sleep.

Dataset Utilization

The synthetic nature of this dataset allows researchers to explore. A controlled environment where various health and lifestyle factors interact to influence sleep quality. This can be particularly valuable for developing and refining predictive models aimed at understanding sleep health.

Prediction Task

The primary objective with this dataset is to predict the Sleep Quality Score using the other synthetic health and sleep metrics as input features. This task offers an opportunity to delve into the underlying patterns and relationships within the simulated data. Providing actionable insights into the determinants of sleep quality. Such insights can guide the development of personalized strategies for improving sleep and overall health. Contributing to advancements in sleep medicine and wellness.