NSF-IIS-1816687: Computational Modeling of Human Rhythms to Improve Health and Quality of Life
Recent research indicates balance is vital to health and well-being, however humans experience stress and imbalances through lack of attention to mental and physical states when meeting work and life demands. This research proposes to improve health and wellbeing in individuals through awareness of their personal rhythms, which are repeated cycles of internal and external events including biological, mental, social, and environmental. The investigators seek to design and evaluate a data analytic and modeling method to make users aware of potential activities at any given time that align with their biological clock, achieving higher performance in life and work without invoking stress-related disorders. The work leverages advances in wearable devices, sensing technology, and online sources to proactively collect and analyze physiological, psychological, behavioral, social, and environmental data to identify personal rhythms, to explore their relationship to positive physical, mental, and behavioral outcomes, and to provide people with tools to reason about these relationships and to improve outcomes. This research highlights the positive performance and outcomes resulting from integrating personal rhythms into individuals’ daily lives.
We are currently recruiting participants interested in improving their sleep, productivity, and overall wellness by participating in our ongoing study on Human Rhythms. Our study focuses on measuring human rhythms through data collected by participants’ smartphones as well as through a FitBit fitness tracker. If interested, see below recruitment flyer for details, qualifications and how to join.
"Modeling Biobehavioral Rhythms with Passive Sensing in the Wild: A Case Study to Predict Readmission Risk after Pancreatic Surgery"
"Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning of Smartphone and Fitbit Data”