| Abstract [eng] |
The object of this project is to provide a personalized evaluation of the relationship between physical activity and sleep quality. Poor sleep quality is associated not only with health and social problems, such as an increased risk of conditions such as diabetes, obesity, and depression, reduced productivity and engagement in workplaces, but also with the impact on the economy. In the United States, poor sleep costs up to $411 billion annually. In this project, a novel methodology is created and implemented that includes various metrics of physical activity and sleep quality and finds the strongest relationships on an individual level. The results of the personalized multiple regression analysis showed distinct associations from different persons. In addition, the results of the time series cluster analysis with physical activity data showed to be a significant regressor in multiple regression models, showing the effectiveness of the newly recommended approach. This project demonstrated the importance of the need for a personalized analysis of physical activity and sleep quality. The developed methodology can be extended by incorporating additional biometrics or new methods to expand the research area. |
