Emma's Twin

Emma's Twin

A digital health ecosystem for people living with Cystic Fibrosis

A digital health ecosystem for people living with Cystic Fibrosis

Timeline:

4 weeks

Role:

Systems Designer / UX Designer

Industry:

Figma, Claude Code

Meet Emma,

Meet Emma,

Meet Emma,

A 27-year-old nurse living with Cystic Fibrosis

A 27-year-old nurse living with Cystic Fibrosis

A 27-year-old nurse living with Cystic Fibrosis

Emma is a 27-year-old nurse living with Cystic Fibrosis. She takes her medication, sees her care team every three months, and by most measures, she's doing fine.

But CF has a quiet danger: lung function can decline significantly while a person feels completely normal. Emma experienced this firsthand — her lung health numbers kept dropping across appointments while she felt healthy enough to work a full nursing shift. By the time she felt the difference, significant damage had already been done.

newborns are born with CF each year.

newborns are born with CF each year.

newborns are born with CF each year.

Cystic Fibrosis (CF)

A genetic disease that causes thick, sticky mucus in the lungs, digestive system, and other organs.

Respiratory Failure is the leading cause of death in CF.

Respiratory Failure is the leading cause of death in CF.

Respiratory Failure is the leading cause of death in CF.

Emma's Burden

Emma's Burden

Before touching design, I interviewed Emma to understand her experience around current care team and plan to understand the most significant moments of stress or frustration she faces living with CF.

Subjective Vs Objective
Her lung health can decline significantly while she feels completely fine.

Monitoring is Episodic
Pulmonary function tests are effort-dependent, quarterly, and clinic-bound. Decline happens between appointments.

Continuity of Care
Providers change but context doesn't transfer. Emma bears the burden of needing to re-explain—generic baselines don't capture her normal.

The Question:

How might we turn Emma's daily health data into an early warning system, so she can live freely and act early?

How might we turn Emma's daily health data into an early warning system, so she can live freely and act early?

Emma's Twin: A system that sees what Emma can't feel

Emma's smart watch and at-home breathing monitor upload health data via bluetooth to the digital cloud. From there, her data is used to create a digital twin—a predictive model of and for Emma's health. Emma can view insights and predictions of her twin through her iPhone and communicate health concerns predicted by her twin directly with her entire care team.

Emma needs her data—both subjective and objective—to be captured and measured against her personal baseline, continuously, to surface health concerns and address them before she starts feeling sick.

Life with Emma's Twin

Each morning, Emma's Twin prompts her to complete a daily 2 minute, 2 step check-in.

Each morning, Emma is reminded to complete her daily check-in routine.

This check-in, combined with overnight smartwatch tracking, captures subjective and objective health data that informs the predictive model.

Each morning, Emma is reminded to complete her daily check-in routine.

iPhone
Records daily stress and subjective health feelings, in less than a minute

iPhone
Records daily stress and subjective health feelings, in less than a minute

At-home breathing monitor
Records objective lung health stats via a 60 second breathing test

At-home breathing monitor
Records objective lung health stats via a 60 second breathing test

At-home breathing monitor
Records objective lung health stats

Smart watch
Passively captures health data overnight

Smart watch
Passively captures health data overnight

3 mornings of feeling good, but her numbers show decline.

Emma's health stats are tracked overnight through her smartwatch and her daily check-in to capture both objective and subjective data.

Increasing drift from baseline over 3 days

Increasing drift from baseline over 3 days

Increasing drift from baseline over 3 days

The data becomes Emma’s digital twin — a predictive model of her health, in real time. The more it learns, the better it predicts.

The app is the window into Emma's digital twin — surfacing the gap between how she’s feeling and what her body's actually doing.

Emma's Twin catches the drift, so she can alert her care team and get care before she's sick.

Her care team gets the full picture — before Emma gets sick.

Emma's care team steps in early.

Following review of drift alert, Emma’s care team can:

Emma's Twin keeps Emma in the loop on next steps.

What does this mean for Emma?

Reflection

Designing for a close friend made this meaningful beyond being a school project. It pushed me to think in full ecosystems rather than single screens, and to understand where existing systems create friction rather than replace them entirely. The problems Emma described — silent health decline, care that resets every time a provider changes — aren't problems a single app can solve. But a connected ecosystem, designed to work with what already exists and fill in the gaps, is a starting point. The goal was never to add complexity to Emma's life, but to make the invisible visible, quietly, in the background.

Next Steps