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Poster Session 3, 1:15 PM - 2:00 PM: Campus Center Auditorium [A40]

Presenter: Sean Wang

Faculty Sponsor: Elena Braynova

School: Worcester State University

Research Area: Computer Science

ABSTRACT

In this project we analyzed sleep quality, health, and lifestyle data to explore relationships between sleep habits, demographics, lifestyle, and a variety of health indicators. After preprocessing, the data was analyzed using a wide variety of visualization, statistical analysis and Machine Learning techniques. We discovered strong correlations between certain attributes, such as sleep duration and sleep quality, sleep quality and stress level, and more. We looked at the data deeper using Machine Learning Classification, Association Rules and Numerical Prediction methods. We found that with very high accuracy we could predict a participant having a sleeping disorder or not. Using a variety of Classification models and methods we found out that the female and male groups in the dataset have different sleeping patterns. Association Rules mining revealed some interesting relationships between gender, sleeping habits, health and lifestyle indicators. Our results on predicting sleep quality using Numerical Prediction methods are also interesting. They show how the sleep quality depends on sleep pattern and health attributes.