Open Source · v3.0

Open Source
Wearable EEG
for Everyone

WalkEEG is an open-source EEG, ECG and EMG platform — including hardware schematics, firmware, a Flutter app for both iOS and Android, and a cloud backend for data storage. Built for researchers, educators, and BCI enthusiasts.

View on GitHub Data Portal →

80–120 dB

CMRR

500–2 kHz

Live Sampling

2 Mbps

BLE 5.0 · 2M PHY

Open

MIT License

Primer

What are EEG, ECG and EMG?

Every living cell produces tiny electrical potentials. Those potentials are strong enough to be picked up from the body's surface, and each one tells a different story.

EEG Electroencephalography
  • Source — millions of cortical neurons firing together
  • Amplitude — 10 to 100 µV
  • Bandwidth — 0.5 to 100 Hz
  • Reads — sleep, attention, brain rhythms, BCI intent
ECG Electrocardiography
  • Source — the electrical sequence that paces every heartbeat
  • Amplitude — 0.5 to 5 mV
  • Bandwidth — 0.05 to 150 Hz
  • Reads — heart rate, rhythm, HRV, ischemic patterns
EMG Electromyography
  • Source — motor units firing to contract a muscle
  • Amplitude — 10 to 1000 µV
  • Bandwidth — 20 to 500 Hz
  • Reads — muscle force, gestures, prosthetics, fatigue
About WalkEEG

What is WalkEEG?

WalkEEG is a complete, open-source biosignal platform for EEG, ECG and EMG, built to make brain-computer interface technology accessible.

nRF52840 BLE 5.0 Zephyr / NCS Flutter WebSocket KiCad LabVIEW
Real ECG recording captured by the WalkEEG app: QRS complexes at 69 bpm on channel CH0, 500 Hz, 2 s window

Live ECG captured in the WalkEEG app · 69 bpm · QRS mode

Complete Stack

Everything You Need

From hardware to data processing — a fully open EEG pipeline.

🔧

Hardware Design

Full hardware schematics for the acquisition board. Analog front-end with instrumentation amplifiers, anti-aliasing filters, and high-precision ADC.

📡

Wireless Firmware

nRF52840 firmware on Zephyr with Nordic Connect SDK. BLE 5.0 with 2M PHY (2 Mbps raw), Data Length Extension (27−>251 byte payload) and a long ATT MTU, so multi-channel biosignals stream at 500 Hz without dropped frames.

📊

PC Oscilloscope

Real-time waveform visualization software (LabVIEW-based). Supports multi-channel EEG display, signal monitoring, and data logging. Available in English and Chinese.

🧪

Cloud Backend

Serverless AWS stack (SAM) with Cognito auth, direct S3 upload, and DynamoDB metadata. Record a session on the app, upload it, and retrieve it from any device.

📱

Mobile App

Flutter app for iOS and Android. Connects directly over BLE, displays live waveforms with QRS detection and HRV metrics, and can relay raw frames to a local server.

⚡

500 Hz Live Dashboard

Browser-based real-time viewer. The phone forwards 8-channel data over WebSocket at 500 samples/s; open a URL and watch the same signal live — no install, no disk writes.

Workflow

How It Works

From electrode to insight — five simple steps.

1

Acquire

EEG electrodes capture brain electrical activity. The analog front-end amplifies and filters the raw signal with precision instrumentation.

2

Transmit

The nRF52840 digitizes the signal and streams it wirelessly over BLE 5.4 to a phone or computer with low latency.

3

Visualize

See the signal live — in the Flutter app on your phone, the 500 Hz browser dashboard, or the desktop oscilloscope. Adjust gain and timebase, and record sessions.

4

Store

Upload recorded sessions to the cloud backend, where they are stored securely and can be pulled back down on any device for later review.

5

Share

The mobile app streams live frames to a WebSocket relay, so anyone on the network can watch the same 500 Hz signal in a browser — or upload sessions to the Data Portal.

100% Open Source

Built in the Open

WalkEEG is free and open-source. Contribute, fork, or build upon it.

📦 Hardware · KiCad Schematics ⚙️ Firmware · nRF52840 / Zephyr 📱 App · Flutter 🖥️ Software · Live Web + LabVIEW ☁️ Backend · AWS SAM
Star on GitHub
KiCad nRF52840 BLE 5.4 Zephyr Flutter WebSocket LabVIEW C

Ready to Get Started?

Download the source, build your own EEG, and start exploring brain activity today.

Get the Source Read the Docs Upload Your Data