Accurate, inclusive, accessible, and educational menstrual trackers
I am interested in creating accurate, inclusive, accessible, and educational menstrual trackers. This work ranges from exploring the nuances for menstrual trackers whom have received minimal sexual education to improving prediction algorithms based on a plethora of physiological signals.
Investigating Menstrual Prediction Mechanisms and Designs for Menstrual Tracking (Advised by Dr. Khai Truong and Dr. Alex Mariakakis)
We collect and analyze a plethora of physiological data collected over multiple menstrual cycles and self-reported qualitative data for better prediction markers. We collect data such as blood glucose, body temperature, respiratory rate, heart rate, sleep cycle, hormones etc. using smart watches, continuous glucose monitors, hormone tests, etc.
Investigating Culturally Responsive Design for Menstrual Tracking and Sharing Practices (Advised by Dr. Neha Kumar and Dr. Elizabeth Mynatt)
Women who often lack familial and societal sex education, as well as access to specialty health care, suffer from a variety of issues from feelings of lack of control to debilitating and unrelievable pain, yet knowing when something is wrong with their menstrual health is rarely afforded by current menstrual trackers.
References
2024
Functional Design Requirements to Facilitate Menstrual Health Data Exploration
Georgianna Lin, Pierre-William Lessard, Minh Ngoc Le, and 4 more authors
In Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024
Menstrual trackers currently lack the affordances required to help individuals achieve their goals beyond menstrual event predictions and symptom logging. Taking an initial step towards this aspiration, we propose, validate, and refine five functional design requirements for future interface designs that facilitate menstrual data exploration. We interviewed 30 individuals who menstruate and collected their feedback on the practical application of these requirements. To elicit ideas and impressions, we designed two proof-of-concept interfaces to use as design probes with similar core functionalities but different presentations of phase timing predictions and signal arrangement. Our analysis revealed participants’ feedback regarding the presentation of predictions for menstrual-related events, the visualization of future signal patterns, personalization abilities for viewing signals relevant to their menstrual experience, the availability of resources to understand the underlying biological connections between signals, and the ability to compare multiple cycles side-by-side with context.
2023
Blood glucose variance measured by continuous glucose monitors across the menstrual cycle
Georgianna Lin, Rumsha Siddiqui, Zixiong Lin, and 4 more authors
Past studies on how blood glucose levels vary across the menstrual cycle have largely shown inconsistent results based on limited blood draws. In this study, 49 individuals wore a Dexcom G6 continuous glucose monitor and a Fitbit Sense smartwatch while measuring their menstrual hormones and self-reporting characteristics of their menstrual cycles daily. The average duration of participation was 79.3±21.2 days, leading to a total of 149 cycles and 554 phases in our dataset. We use periodic restricted cubic splines to evaluate the relationship between blood glucose and the menstrual cycle, after which we assess phase-based changes in daily median glucose level and associated physiological parameters using mixed-effects models. Results indicate that daily median glucose levels increase and decrease in a biphasic pattern, with maximum levels occurring during the luteal phase and minimum levels occurring during the late-follicular phase. These trends are robust to adjustments for participant characteristics (e.g., age, BMI, weight) and self-reported menstrual experiences (e.g., food cravings, bloating, fatigue). We identify negative associations between each of daily estrogen level, step count, and low degrees of fatigue with higher median glucose levels. Conversely, we find positive associations between higher food cravings and higher median glucose levels. This study suggests that blood glucose could be an important parameter for understanding menstrual health, prompting further investigation into how the menstrual cycle influences glucose fluctuation.
2022
Investigating Culturally Responsive Design for Menstrual Tracking and Sharing Practices Among Individuals with Minimal Sexual Education
Human-Computer Interaction (HCI) research on menstrual tracking has emphasized the need for more inclusive design of mechanisms for tracking and sharing information on menstruation. We investigate menstrual tracking and data-sharing attitudes and practices in educated, young (20-30 years old) menstruating individuals based in the United States, with self-identified minimal menstrual education backgrounds. Using interviews (N=18), a survey (N=62), and participatory design (N=7), we find that existing mechanisms for tracking and sharing data on menstruation are not adequately responsive to the needs of those who seek relevant menstrual education, are not in the sexual majority, and/or wish to customize what menstrual data they share and with whom. Our analysis highlights a design gap for participants with minimal sexual education backgrounds who wish to better understand their cycles. We also contribute a deepened understanding of structural health inequities that impact menstrual tracking and sharing practices, making recommendations for technology-mediated menstrual care.
