---
title: Heartline
emoji: 🫀
sdk: gradio
sdk_version: 5.33.0
app_file: app.py
pinned: true
short_description: Client-side cardiac home monitoring 
tags:
  - track:backyard
  - sponsor:openbmb
  - achievement:offgrid
  - achievement:welltuned
  - achievement:offbrand
  - achievement:llama
  - achievment:field-notes
---

# Heartline 🫀

**Cardiac home monitoring that runs entirely in your browser.** No cloud. No data leaving your device. No GPU required.

Heartline lets patients log blood pressure readings, upload phonocardiogram audio from their phone, and generate a physician-ready clinical SOAP note — all processed locally using on-device AI.

Read the blogpost here, honestly its better than  the video or even the readme for explanations https://dev.to/pranay_narula_bdc02868409/huggingface-build-small-hackathon-my-first-health-sprint-39g5

---

## What it does

### 1. Blood pressure tracking
Log systolic, diastolic, and heart rate readings with timestamps and symptoms. A live trend chart and summary statistics (mean, SD, pulse pressure) update as you type.

### 2. ECG rhythm classification
Upload a  or  audio recording captured by pressing your phone microphone to the left sternal border (4th-5th intercostal space). A custom-trained 5-class classifier runs entirely in the browser via **ONNX Runtime Web** with WebGPU acceleration and WASM fallback. It classifies:
- Normal sinus rhythm (NSR)
- Tachycardia
- Bradycardia
- Atrial fibrillation (AFib)
- Premature ventricular contractions (PVC)

### 3. AI-generated SOAP note
A ** Finetuned Version of MiniCPM 1B Q4_K_M GGUF using constitutional finetuning with deepseek v4 pro based on soap clinical notes: https://huggingface.co/SlitherCode/heartline-soap

opensource on huggingface ** model runs in the browser via **wllama** (WebAssembly port of llama.cpp). It streams a physician-style Objective section incorporating all BP readings, heart rates, rhythm classifications, and patient history — tokens appear as they generate, no server involved.

---

## Tech stack

| Component | Technology |
|---|---|
| ECG classifier | Custom PyTorch model exported to ONNX, runs via onnxruntime-web (WebGPU + WASM fallback) |
| Clinical LLM | heartline-soap which is a finetuned version of MiniCPM 1B Q4_K_M GGUF via wllama v3.5.0 (WebAssembly llama.cpp) |
| Frontend | Vanilla JS, zero framework, fully custom UI |
| Backend | Gradio Server used as static file server only — zero backend inference |
| Audio | AudioContext.decodeAudioData() → mel spectrogram → classifier |

**Zero backend inference.** The Gradio server only serves index.html, heartline.onnx, and model_Q4_K_M.gguf. All AI runs client-side.

---

## Models used

- **ECG classifier**: Custom 5-class CNN trained on PhysioNet phonocardiogram data. ~94 MB ONNX.
- **Clinical summarizer**: MiniCPM 1B Q4_K_M quantized GGUF (~688 MB). Streams the SOAP Objective section directly in the browser via WebAssembly.

---

## Medical disclaimer

Heartline is a research prototype and has not been evaluated or cleared by the FDA. It is not a substitute for professional medical advice, diagnosis, or treatment. Cardiac rhythm classifications are automated and may be inaccurate. If you are experiencing a medical emergency, call 911 or your local emergency number immediately.

---

## Demo

> Demo video: https://youtu.be/xRb6cS7FfWY

> Social post: https://www.linkedin.com/feed/update/urn:li:activity:7472434733075869696/

---

## How to use

1. Fill in patient background (age, sex, conditions, medications)
2. Log blood pressure readings with heart rate
3. Upload a .wav audio recording from your phone (or use the provided synthetic samples)
4. Wait for the ECG classifier to run (a few seconds)
5. Generate the SOAP note — MiniCPM streams the clinical summary live in your browser

Built for the **Build Small Hackathon** — Backyard AI track