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Led by: Azure Grant
University of California, Berkeley; Quantified Self
Contact email: azuredominique@gmail.com
Project website: https://sites.google.com/view/qcyclepublic/home
  • Connected by 24 members.

Are you interested in using your Oura or body temperature data to learn about your cycle? Not cycling? No problem! We're interested in working with you if you've got a question you'd like to answer using your self-collected data.

QCycle seeks to map the diversity of biological rhythms (cycles we all have!) in human physiology, with an emphasis on female ovulatory cycles. We're working on improving open-source ovulation prediction. This project was motivated by that fact that surprisingly little of the attention and funding turned to personalized, predictive, preventative medicine has focused on the female reproductive system: Pregnancy onset cannot be quickly identified, menopause onset and trajectory remain entirely mysterious, and adverse reactions to tools like hormonal birth control are difficult to anticipate. Importantly, there are no automated, cheap, high-accuracy methods for predicting ovulation in the diverse population of cycling people.

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