PIEEG / PLATFORMWS :1616 · UI :1617LOCAL / OPEN

PiEEG Server / signal infrastructure

Give every signalan address.

One Python server turns EEG, EMG, ECG, and EOG hardware into a live WebSocket stream, a browser dashboard, and an open endpoint for whatever you build next.

Route a signal View source

SERVER / BOOT ONLINE

01$ pip install pieeg-serverPACKAGE READY

02$ pieeg-serverHARDWARE DETECTED

03ws://raspberrypi.local:1616STREAM OPEN

InstallOne pip command

Stream250–500 Hz

ProtocolPlain JSON / WebSocket

DashboardBrowser / :1617

SystemsPi · Linux · macOS · Windows

01 / Platform position

The server is not the destination.

It is the transparent middle: hardware enters on one side, timestamped channel data leaves on the other. The format stays simple enough for a browser, Python script, XR environment, notebook, or real-time integration to understand.

02 / Signal router

Choose the instrument.
Choose where it goes.

Switch the source hardware and destination to see the exact local route PiEEG Server creates.

01 / Select input32 CH

02 / Select routeOUTPUT

LIVE ROUTE / CONFIGURATION READY

INPUTIronBCI-32USB Serial / 32 CH

PROCESSPiEEG ServerPYTHON / LOCAL

OUTPUTWebSocketJSON / :1616

CHANNEL FIELD32 ACTIVE

DEVICE COMMAND$ pieeg-server --device ironbci32 --serial-port /dev/ttyACM0

DESTINATIONLanguage-agnostic stream

High-density USB serial acquisition

03 / Launch sequence

Three moves from hardware to live data.

Install

$ pip install pieeg-serverPython 3.10+ · hardware auto-detection

Stream

$ pieeg-serverWebSocket :1616 · dashboard :1617

Open

$ http://raspberrypi.local:1617Inspect the live stream in any browser

04 / Observable system

If the signal changes, you should see it.

The PiEEG Server dashboard keeps the live acquisition, frequency structure, and signal quality visible in the browser.

PIEEG SERVER / LIVE DASHBOARDHTTP :1617

PiEEG Server dashboard showing live multichannel waveforms, spectrograms, and signal information

LIVE WAVEFORMSFREQUENCY VIEWSIGNAL QUALITY

Live waveforms

Inspect every active channel as the stream moves through the server.

FFT and spectrograms

Move between time-domain signals and their frequency structure.

Signal quality

Monitor the acquisition before building decisions on top of it.

Record and replay

Capture annotated CSV sessions and replay them at 0.5×–2× speed.

05 / WebSocket contract

Plain JSON.
No private language.

Every frame carries a timestamp, a monotonic sample number, and an array of channel values. Any language with WebSocket support can listen.

t: Unix timestamp / seconds
n: Monotonic sample number
channels: Array of µV values

PYTHON / CLIENT

import asyncio, json, websockets

async def main():
    uri = "ws://raspberrypi.local:1616"
    async with websockets.connect(uri) as ws:
        async for message in ws:
            frame = json.loads(message)
            print(frame["n"], frame["channels"])

asyncio.run(main())

FRAME / JSON

{
  "t": 1711234567.123,
  "n": 42,
  "channels": [12.34, -5.67, ...]
}

06 / Routes outward

A stream becomes useful when it leaves the dashboard.

VRChat OSC

--osc

Stream band powers to avatar parameters

Lab Streaming Layer

--lsl

Connect with OpenViBE, MNE, and LabRecorder

Webhooks

JSON control

Create HTTP callbacks from EEG events

Jupyter

notebooks/

Load CSV or inspect a live stream

07 / Open the endpoint

Install the server.
Keep the signal open.
Build from there.

Try the live experience Open the repository Read documentation