Designing The First App for Fertility Tracking Using An Earring.
Delphea.
AV
Enhancing Wearable-App Integration for Fertility Tracking
Enhancing Wearable-App Integration for Fertility Tracking
At a Glance
At a Glance
Delphea (under Aurelia Vitals) isn’t just another period app. It’s a wearable earring and mobile experience designed to utilize biomedical data and machine learning to predict fertility windows, with the rigor required for FDA clearance. As a founding product designer, I helped transform a rough CSV-export prototype into a scalable product with clear user flows, a design system, and approachable visuals.
Delphea (under Aurelia Vitals) isn’t just another period app. It’s a wearable earring and mobile experience designed to utilize biomedical data and machine learning to predict fertility windows, with the rigor required for FDA clearance. As a founding product designer, I helped transform a rough CSV-export prototype into a scalable product with clear user flows, a design system, and approachable visuals.
6 months (and counting)
My Role:
Product Designer
1-4 Product Designers
1 Marketer
1 Data Scientist
3 Developers
2 Elec Engineers
7 months
My Role:
Product designer, researcher and strategist.
1-4 Product Designers
1 Marketer
1 Data Scientist
3 Developers
2 Elec Engineers
1-4 Product Designers
1 Marketer
1 Data Scientist
3 Developers
2 Elec. Engineers
Results:
Results:
89%
of test users reported Delphea would be useful to guide pregnancy planning/prevention choices
89%
89%
of test users reported Delphea would be useful to guide pregnancy planning/prevention choices
of test users reported Delphea would be useful to guide pregnancy planning
89%
of test users reported Delphea would be useful to guide pregnancy planning/prevention choices
7 months
My Role:
Product Designer
1-4 Product Designers
1 Marketer
1 Data Scientist
3 Developers
2 Elec Engineers
PROBLEM
PROBLEM
The Missing Link in Fertility Support.
The Missing Link in Fertility Support.
For women trying to plan or prevent pregnancy, decisions often hinge on cycle
For women trying to plan or prevent pregnancy, decisions often hinge on cycle predictions that feel unreliable. Irregular periods, missed logs, and confusing data make it difficult to know when to feel confident and when to be cautious. Existing tools often leave users overwhelmed with input requirements or under-informed with vague insights, which erodes trust.
For women trying to plan or prevent pregnancy, decisions often hinge on cycle predictions that feel unreliable. Irregular periods, missed logs, and confusing data make it difficult to know when to feel confident and when to be cautious. Existing tools often leave users overwhelmed with input requirements or under-informed with vague insights, which erodes trust.
Solution Preview→
RESEARCH
RESEARCH
No menstrual cycle tracking app had FDA-level accuracy and automatic data collection.
No menstrual cycle tracking app had FDA-level accuracy and automatic data collection.
User interviews (13) →
User interviews (13) →
My team and I conducted 13 interviews in order to investigate the most significant pain points of our target users. We found that the top priorities for users were cycle prediction and prep, monitoring sexual health, and symptom tracking.
My team and I conducted 13 interviews in order to investigate the most significant pain points of our target users. We found that the top priorities for users were cycle prediction and prep, monitoring sexual health, and symptom tracking.
Women interviewees with irregular cycles.
"I hate logging every day"
"Existing apps are too playful"
Sexually active women interviewees who are worried about pregnancy.
"I need more accurate predictions"
Persona 2: Sexually active women who are worried about pregnancy
Persona 1: Women with irregular cycles
"Daily logging is a chore"
"Privacy is a must"
"Existing apps are too playful"
Persona 1: Women with irregular cycles
"Daily logging is a chore"
"Existing apps are too playful"
Persona 2: Sexually active women who are worried about pregnancy
"Privacy is a must"
54%
54%
of interviewees wanted more accurate cycle predictions
of interviewees wanted more accurate cycle predictions
Competitor Analysis →
Competitor Analysis →
My team and I analyzed 7 apps in depth and 12 total existing solutions for menstrual tracking. We discovered significant issues that these apps were not sufficiently addressing.
My team and I analyzed 7 apps in depth and 12 total existing solutions for menstrual tracking. We discovered significant issues that these apps were not sufficiently addressing.
Requires constant user input.
Inaccuracies due to monitoring location.
Only FDA-Cleared birth control app, but still requires manual entry.
Requires constant user input.
Inaccuracies due to monitoring location.
Only FDA-Cleared birth control app, but still requires manual entry.
Inaccuracies due to monitoring location.
Only FDA-Cleared birth control app, but still requires manual entry.
Our Direction →
How might we give users confidence in cycle tracking through a design that balances warmth and scientific rigor?
Our Direction →
How might we give users confidence in cycle tracking through a design that balances warmth and scientific rigor?
Secondary Research →
After reviewing online forums, published papers, and other sources, my team found that while users want menstrual tracking apps to be accurate and educational, they are often frustrated by non-inclusive designs and inaccurate predictions. We identified a significant lack of data privacy and security as the primary barrier to trust, as many apps share sensitive data, creating legal risks. Full research document
Our Direction →
How might we give users confidence in cycle tracking through a design that balances approachability and scientific rigor?
Our Direction →
How might we give users confidence in cycle tracking through a design that balances warmth and scientific rigor?
How might we give users confidence in cycle tracking through a design that balances warmth and scientific rigor?
Our Direction →
DEVELOPMENT
DEVELOPMENT
From messy exports to meaningful predictions.
From messy exports to meaningful predictions.
Initial Planning and Ideation →
Initial Planning and Ideation →
When I joined, the app flow was clunky: pair device → export CSV → AirDrop to computer→ lose your data because the app deleted it. Not exactly user-friendly. So in order to create a functional app, we started by determining the necessary features, information architecture, and user flow (onboarding and other screens have been left out for simplicity):
When I joined, the app flow was clunky: pair device → export CSV → AirDrop to computer→ lose your data because the app deleted it. Not exactly user-friendly. So in order to create a functional app, we started by determining the necessary features, information architecture, and user flow (onboarding and other screens have been left out for simplicity):
How might we provide effective at-a-glance summaries for the wearable's data?→
Home Iterations→
Fertility predictions:
Displaying temperature data:
Sliding bar suggests too much confidence
Clear explanation and prediction
Text is too on the nose and insensitive
No trend visible - hard to interpret
Error bars are information overload
Home Screen
Easy to digest information
How might we effectively display predictions and past data for ovulation and menstrual periods?→
Card and "dot" design
Glowing/Gradient Design
Large Pill and Flat Design
Preview of daily log is helpful but cluttered
the dot symbols are unintuitive
Darkness of ovulation indication seems to indicate a definite prediction
Color coding at the top is helpful but is distracting & not accessible
"glowing" indicators are tacky & hard to develop
Months aren't clearly separated
Ovulation and periods are clearly indicated
Interface is decluttered
Months are clearly seperated
TESTING & MAJOR PIVOT
TESTING & MAJOR PIVOT
Prioritizing a Welcoming Aesthetic Based on Initial User Feedback.
Prioritizing a Welcoming Aesthetic Based on Initial User Feedback.
80% of the test users expressed issues with the app's aesthetic, reporting the app felt "unfriendly" and "sterile"
Getting initial feedback →
After the initial high-fidelity prototype was designed, I became the sole UX designer on the project. To validate the work, I tested the designs with users, who gave negative feedback on the aesthetics and had issues using the device.
Prioritizing warmth and approachability →
Prioritizing warmth andapproachability →
To address these concerns, I updated the design system and core screens, replacing clinical tones with a warmer, more approachable palette. The redesign balances updated aesthetics with established mental models for cycle tracking.
To address concerns surfaced in user testing, I began ideating new ways to show the connected device and changing the overall color scheme of the app.
I experimented with gradient backgrounds, but I got feedback that they were too playful.
I added a card for the wearable device in the middle of the screen to make it more obvious.
Designing for Device Maturity →
Designing for Device Maturity →
With improved battery performance the user no longer had to initiate data transfer so I decluttered the interface by deemphasizing the battery status and streamlining the flow for real-time data syncing.
With improved battery performance the user no longer had to initiate data transfer so I decluttered the interface by deemphasizing the battery status and streamlining the flow for real-time data syncing.
80%
Of the 5 test users reported that the app didn't feel welcoming (uh oh!)
FINAL PRODUCT
FINAL PRODUCT
The World's First Earring-Integrated Health App.
The World's First Earring-Integrated Health App.
Seamless Biotracking via a Wearable Earring.
1
1
Biometric wearable integration →
Biometric wearable integration →
The app syncs with the new biometric wearable to reduce data entry.
Pending approval to be the only FDA-approved wearable integrated birth control app.
The app syncs with the new biometric wearable to reduce data entry. The app is pending approval to be the only FDA-approved wearable integrated birth control app.
Machine Learning Predictions →
Machine Learning Predictions →
The app uses temperature data and other inputs from the wearable to predict fertility levels in users using a machine learning model.
The app uses temperature data and other inputs from the wearable to predict fertility levels in users using a machine learning model.
2
2
3
3
Retained User Input & Logging →
Retained User Input & Logging →
In order to track other factors, such as pregnancy tests or period flow levels, the app also has functionality to input symptoms.
In order to track other factors, such as pregnancy tests or period flow levels, the app also has functionality to input symptoms.
The Result →
The Result →
of 9 test users reported trust in the app to make fertility decisions.
of 9 test users reported trust in the app to make fertility decisions.
89%
89%
89%
89%
of 9 test users reported trust in the app to make fertility decisions.
89%
Of 9 test users reported trust in the app to make fertility decisions.
89%
of 9 test users reported trust in the app to make fertility decisions.
FINAL THOUGHTS:
Key learnings and next steps
I learned that Designing for AI in healthcare tracking is about trust as much as accuracy.
I learned to translate messy biomedical predictions into approachable guidance.
I discovered that designing for new hardware is about building for the long term, as hardware constraints are discovered or solved.
Next Steps →
Next, we plan to conduct user testing with updated machine learning predictions integrated into the interface, allowing us to more holistically evaluate the app’s predictive capabilities. As the wearable evolves beyond temperature tracking, we will also introduce additional health data to broaden insights. Finally, the product will undergo FDA testing as we work toward official approval.
Finishing up development and launching the product!
Adding more vitals features like heart rate and blood oxygen.
Going through the FDA testing process.
Thanks for visiting! I go into more detail on my work over calls/interviews. Feel free to reach me here.
Thanks for visiting! I go into more detail on my work over calls/interviews. Feel free to reach me here.
But Wait, There's More!
But Wait, There's More!
