HeartBridge

The Problem

Cardiac rehabilitation can improve outcomes after a heart event, but participation is low. An American Heart Association study found that roughly one in four eligible older adults with Original Medicare participated in outpatient cardiac rehab. That result has a specific population and study period; it isn't a universal 75% rate.

The participation gap has multiple causes, including health status, referral and program availability, transportation, cost, time, confidence, and support between visits. HeartBridge explored one part of that problem: making check-ins and progress more accessible outside a facility.

The Insight

Information alone doesn't remove every participation barrier. A warmer, voice-driven companion could make check-ins easier, coach people through assigned exercises, and keep an approved care circle informed between appointments. It wouldn't replace clinical care or solve access on its own.

The Solution

HeartBridge is a prototype concept that combines voice coaching, daily progress tracking, and care-circle support in one recovery experience. The judged frontend demonstrated that flow with mock data and browser speech. The follow-on product direction adds model-assisted check-ins and a higher-quality voice layer, with clinical review and consent controls required before real patient use.

How It Works

1. Step 01

   Voice-guided sessions

   The judged prototype used browser speech to walk through the coaching flow. ElevenLabs is the follow-on voice option, not a submission-day integration.

2. Step 02

   Daily check-ins

   The prototype showed short conversational check-ins with mock responses. A real version would need a reviewed data model, consent, and escalation rules.

3. Step 03

   Progress visibility

   The frontend showed recovery milestones, session history, and trends using hardcoded demo data.

4. Step 04

   Care circle

   The prototype demonstrated a care-circle view. Real sharing would require explicit patient consent, identity controls, and a secure backend.

Judged architecture and follow-on path

Build Process

HeartBridge was built in a single day at the Pulse Foundry AI NYC Healthcare hackathon on March 29, 2026. I was placed on a randomly assigned team of 6 strangers. I designed roughly 80% of the product, led the overall build, and presented the winning demo.

The build started with a Lovable MVP to get the UI shell up fast. I then combined that repo with health-domain work from a prior project (VitalMed) in Factory AI using Opus 4.6, re-architecting from a README implementation plan. During the build, I reviewed and merged 5 teammate PRs using Amp smart mode to keep the codebase consistent.

The result was a frontend prototype with browser voice, progress views, and a care-circle dashboard, all presented live to the judges with mock, hardcoded data and no backend. The frozen Devpost record documents those boundaries.

Key Design Decisions

• Voice-first over text-first: Cardiac rehab patients skew older and are recovering physically. A voice interface is lower friction than typing and feels more like a real coach checking in.
• Care circle over solo tracking: Recovery doesn't happen in isolation. Giving family members and clinicians visibility creates a support network without burdening the patient with manual updates.
• Warmth over clinical precision: The tone is encouraging, not medical. HeartBridge isn't replacing a cardiologist. It's filling the motivational gap between appointments.
• Lovable for speed, Factory for structure: Starting with Lovable got a visual prototype up in hours. Moving to Factory AI for the re-architecture let us ship something structurally sound by demo time.
• Amp for team coordination: With 5 strangers submitting code simultaneously, using Amp smart mode for PR review and merging kept the repo from turning into chaos.

Outcomes

• 1st place at the Pulse Foundry AI NYC Healthcare hackathon.

What It Demonstrates

• Hackathon leadership: Designed 80% of the product and led the build with a team of strangers under extreme time pressure.
• Multi-tool orchestration: Combined Lovable, Factory AI, and Amp into a coherent one-day build pipeline, then documented the Claude and ElevenLabs follow-on path separately.
• Healthcare product judgment: The product was shaped around a real participation gap backed by clinical data, not a generic "AI for health" concept.
• Team coordination under pressure: Managed 5 teammate PRs through Amp smart mode while leading the core architecture.