Specification

MicroBCI shield

Hardware


Channels	8 biosignal inputs
Extra inputs	Reference (shared by all channels) and bias
Analog front end	Texas Instruments ADS1299
Resolution	24-bit, delta-sigma, all channels sampled at the same moment
Sample rate	250 SPS
Signals	EEG, EMG, ECG, EOG
Electrodes	Dry or wet Ag/AgCl, 2.54 mm header
Host	STMicroelectronics NUCLEO-WB55 (STM32WB55: Arm Cortex-M4 application core, Cortex-M0+ radio core)
Wireless	Bluetooth LE
Firmware	`Micro_BCI.hex` + STM32WB BLE stack, flashed with STM32CubeProgrammer
Power	5 V via the Nucleo's Micro-USB, from a small power bank
Isolation	None. Battery operation is required.

Software support

Software	Setting
Python SDK (opens in a new tab)	`bleak`, by address or name `EAREEG`
Android app (opens in a new tab)	Settings → 8 ch
PiEEG Cloud	PiEEG Devices → IronBCI
PiEEG Server	`--device ironbci8`

Bluetooth data format

The same protocol as IronBCI:


Advertised name	`EAREEG`
Data characteristic (notify)	`0000fe42-8e22-4541-9d4c-21edae82ed19`
Sample	8 channels × 3 bytes = 24 bytes, 24-bit big-endian two's complement. A notification can carry one or more samples.

Converting to microvolts

raw = (b[0] << 16) | (b[1] << 8) | b[2]
if raw & 0x800000:
    raw -= 16777214
uV = raw * 4.5 / 16777215 * 1e6        # about 0.268 µV per count

Minimal Python reader

import asyncio
from bleak import BleakClient
 
ADDRESS = "00:80:E1:XX:XX:XX"                      # your board
CHAR    = "0000fe42-8e22-4541-9d4c-21edae82ed19"
 
def to_uv(b0, b1, b2):
    raw = (b0 << 16) | (b1 << 8) | b2
    if raw & 0x800000:
        raw -= 16777214
    return raw * 4.5 / 16777215 * 1e6
 
def on_data(_, data):
    for s in range(len(data) // 24):
        sample = data[s*24:(s+1)*24]
        print([round(to_uv(*sample[3*i:3*i+3]), 1) for i in range(8)])
 
async def main():
    async with BleakClient(ADDRESS) as client:
        await client.start_notify(CHAR, on_data)
        await asyncio.sleep(10)
 
asyncio.run(main())

Raw values carry a large DC offset from the electrode contact. That is normal. Apply a band-pass filter (for example 1–40 Hz) before looking at EEG.

Documents

Firmware Troubleshooting