Jeffrey Olgin: Data Aggregation for N-of-1 to “N-of-Many-Ones”
“Within a few days we were able to identify the 20 most common triggers of atrial fibrillation. People with those triggers will be micro randomized to an intervention of their choice and monitored for the frequency of atrial fibrillation and the variability of symptoms during cross over testing periods of their trigger.”
Jeffrey Olgin is a renowned cardiologist and the co-principal investigator of the NIH-funded Health eHeart study. Here, he introduces the Eureka platform, which allows individuals to create their own hypotheses and test them with assistance from researchers, while contributing data for larger cohort studies. His talk outlines the possibilities of an “N-of-many-ones” approach, bringing promising self-tracking practices into contact with mainstream group research.
Highlights from the QS Symposium 2018
Introduction to the Quantified Self Symposium 2018
Reza Mirza: The History and Future of Single-Subject Science
Hugo Campos: 10 Years With An Implantable Cardiac Device, Still No Data Access
Jana Beck: Carb Intake and 60 Lipid Measurements
Azure Grant: Lessons from Blood Testers, a Participant-Led Project
Dorothy D. Sears: Circadian Rhythms and Cardiometabolic Health
Carsten Skarke: Characterizing the Chronobiome with “Supertrackers”
Whitney E. Boesel: Cholesterol Variability Across Postpartum Menstrual Cycles
Xiao Li: Finding the Signal in Rich Self-Collected Data
Jeffrey Olgin: Data Aggregation for N-of-1 to “N-of-Many-Ones”
Dana Lewis: Social Infrastructure for Participant-Led Research
Camille Nebeker: Informed Consent, Self-Consent
Steven Steinhubl: Where “All of Us” Meets All of Us
Sunita Vohra: What N-of-1 Can Do
