Overview
What this challenge is about.
Detect Atrial Fibrillation from Wearable Heart-Rate Data. Advanced challenge in code. Writing production code that solves real engineering problems, earn a b...
The Brief
What you'll do, and what you'll demonstrate.
Build a non-diagnostic AFib-detection pipeline from raw wearable PPG data and validate fairness across demographic strata without claiming medical intent.
This is not a coding exercise. It is the work a software engineer does between a Jira ticket and a merged PR. That distinction matters to every hiring manager who has seen candidates solve LeetCode problems and none who have shipped production code under real constraints.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
Earning criteria — what you'll demonstrate
- Preprocess noisy wearable signals with motion-artifact rejection
- Implement beat detection and RR-interval irregularity metrics
- Evaluate biomedical models with patient-level (not sample-level) splits
- Communicate algorithm limitations to a regulatory-aware stakeholder
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Computational Biology and Health Informatics
Master · General Studies
Strong alignment
This challenge maps to Computational Biology and Health Informatics at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Health Sensing
Apply health sensing to solve real industry problems and demonstrate production-level capability.
- Signal Processing
Apply signal processing to solve real industry problems and demonstrate production-level capability.
- Biomedical Signals
Apply biomedical signals to solve real industry problems and demonstrate production-level capability.
- Fairness Evaluation
Apply fairness evaluation to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
- Benchmarking
Apply benchmarking to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Product Manager
Product managers in consumer health who have shipped a non-diagnostic feature understand the regulatory line and ship safely.
This challenge sharpens
- fairness-evaluation
- benchmarking
- health-sensing