Modeling Biological Rhythms to Predict Mental and Physical Readiness; The Desire for Success: How American Students are Striving to Increase Their Productivity
Palombi, Leah, School of Engineering and Applied Science, University of Virginia
Doryab, Afsaneh, EN-Eng Sys and Environment, University of Virginia
Norton, Peter, EN-Engineering and Society, University of Virginia
How can productivity be improved? Productivity can contribute to personal success, but many struggle to be as productive as they desire. Technology can enhance productivity, but it also can also introduce distractions.
Rhythm-aware technology can improve users’ awareness of personal rhythms, which in turn can improve productivity. The circadian rhythm, a 24-hour physiological cycle, influences human productivity. We hypothesized that a system that helps users align their biological cycles with their daily lives would improve their personal productivity. We collected quantitative data associated with circadian rhythm from four volunteers. Four Oura Rings and four Empatica E4 devices tracked sleep cycle, electrodermal activity, skin temperature, and physiological markers to model biobehavioral rhythms. The Oura readinesss score was used as our dependent variable. This data was analyzed through the Chronomics Analysis Toolkit to build models of rhythms and determine relationships between productivity and wellbeing. Our analysis found that heart rate was most highly correlated with overall readiness.
How are U.S. university students striving to increase their productivity? To succeed in college, students employ various productivity strategies. Students’ objectives vary, and may include various kinds of academic or athletic success. Students’ methods vary too; some use wearable technology and stimulants. A student’s method of choice may be less effective than perceived.
BS (Bachelor of Science)
biological rhythms, modeling, productivity
School of Engineering and Applied Science
Bachelor of Science in Systems Engineering
Technical Advisor: Afsaneh Doryab
STS Advisor: Peter Norton
Technical Team Members: Ben Carper, Dillon McGowan, Samantha Miller, Joe Nelson, Lina Romeo, Kayla Spigelman