by Starcat, LLC

8-32 channel TI ADS1299 Arduino shield for EEG, EMG, and EKG bio-signals acquisition

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Product Choices


HackEEG 8-channel Starter Kit

This level includes one HackEEG board, a ribbon cable, and a connector board with 10 DIN 42-802 touch-proof electrode connectors (8 inputs, 1 reference, 1 ground)


HackEEG 8-channel Deluxe Kit

This level includes one HackEEG, ribbon cable, electrode connector, Arduino Due, 10 silver chloride EEG electrodes, Ten20 conductive paste (2oz), NuPrep prep gel (4 oz).


HackEEG 32-channel Deluxe Kit

This level includes 4 x HackEEG, 4 x ribbon cable, 4 x electrode connector, 1 x Arduino Due, 40 silver chloride EEG electrodes, Ten20 conductive paste (4 x 2oz), NuPrep prep gel (4 x 4 oz)


HackEEG 8-Channel Basic Kit

Includes one HackEEG, ribbon cable, and electrode connector.


Recent Updates

As Featured In

If you want to digitize brainwaves and electroencephalograph (EEG) data, while interfacing with other Arduino hardware and software, this is the Arduino shield for you!

HackEEG is an affordable, high-performance, fully open source TI ADS1299 Arduino shield ideally suited for digitizing biosignals like EEG, EMG, and EKG. If you want to read your brainwaves, do brain-computer interfacing, or build high-performance lab instruments for neuroscience or biology, HackEEG is for you! We’ve spent the last few years partnering with major research institutions and pharmaceutical companies in the US and Europe and now we want to bring HackEEG to you!

HackEEG shield - angled

This shield is a field-proven, high-performance, open-source lab instrument. All hardware, drivers, and Python client software are completely open source and easily modified. HackEEG is ideally suited for neuroscience biosignals applications – EEG, EKG, EMG, and more.

Features and Specifications

  • Eight analog-digital conversion (ADC) channels, each with a 24x programmable-gain amplifier (PGA).
  • Up to four shields can be stacked on one Arduino Due, for a total of 32 EEG channels
  • DMA drivers can read and transfer eight channels of 24-bit resolution data at up to 16,000 samples per second (the maximum rate of the ADS1299 chip). 32 channels can be read at 4,000 samples per second.
  • USB 2.0 HS (480 Mbps) connectivity when using Arduino Due
  • Python client software and APIs provide easy interchange of real-time data to Lab Streaming Layer, pandas, numpy, and more.
  • Data can be streamed via Lab Streaming Layer at 16,000 samples per second from a laptop.
  • SPI EEPROM for storing configuration data
  • Jumpers for configuring most of the data and control lines to the Arduino
  • Jumpers for configuring on-board instrumentation power supplies to output -2.5 V to 2.5 V or 0 V to 5 V
  • Also compatible with the Arduino Mega 2560 but with reduced sampling speeds. 5 V to 3.3 V voltage-level shifters included on board.
  • Open Source Hardware certified


HackEEG allows you to access the entire range of the TI ADS1299 EEG system-on-a-chip‘s features and performance. The Arduino drivers and Python client software allow complete access to the ADS1299 registers, and can read 8 channels of 24-bit ADC data at the maximum rate of the chip, 16,000 samples per second.

On-board instrumentation power supplies can be configured for 2.5 V to -2.5 V or 5 V to 0 V. Single-ended and differential modes are both possible with P and N inputs available on the HackEEG’s electrode connector.

HackEEG, subject, and technician

8, 16, 24, or 32 channels

Up to four boards can be stacked on one Arduino Due for 8, 16, 24, or 32 channels.


Since this is an Arduino shield, you can stack it with existing shields, or add hardware of your own design. For example, we have users who added analog preamplifiers and custom image digitization synchronization hardware on their own custom shields.

All the software is completely open, so if you want to change it or add to it, you can! The HackEEG Arduino driver is text-mode, and has a JSON Lines protocol, so if you want to write client software in another language, you can. There is also a compact binary format that uses MessagePack that is used just for data streaming. Libraries for both JSON Lines and MessagePack data formats are available in many computer languages like C#, Javascript, C++, Ruby, Haskell, and others.

Lab Instrument

This is an actual lab instrument being used to do science in many research and pharmaceutical labs. It has high-resolution, high-bandwidth data acquisition capabilities with very low noise characteristics; even though it’s only $495.00, HackEEG matches the performance capabilities of closed-source amplifiers costing many thousands of dollars, and it can’t be beat for openness and programmability.

HackEEG has a wired interface so can be used directly connected to a laptop or desktop computer to do high-speed capture of biosignals. With the addition of a Raspberry Pi 4, it can send data wirelessly via Wi-Fi.

Lab Streaming Layer

HackEEG’s Python client software can stream data via the standard neuroscience software communication protocol Lab Streaming Layer either on a single laptop computer or via Wi-Fi. This means you can stream HackEEG directly to your favorite neuroscience software or Matlab running on your laptop or remote computers, record data streams, and integrate HackEEG data with other data streams.

HackEEG connected to a Raspberry Pi 4 sending Lab Streaming Layer data over WiFi

OpenBCI Compatible

Using our fork of OpenBCI, you can stream HackEEG to OpenBCI and visualize it there. (We hope to get our changes merged to mainline.)

OpenBCI Lab Streaming Layer datasource selection:

OpenBCI Lab Streaming Layer source selection

OpenBCI showing HackEEG data being streamed by Lab Streaming Layer:

OpenBCI showing HackEEG Lab Streaming Layer data


HackEEG is being successfully used for neuroscience research by these organizations:


HackEEGOpenBCI Cyton+DaisyEmotiv EPOC FlexCompumedics Neuroscan Grael LT
Open Source?Hardware + Software Hardware + SoftwareNoNo
EEG Channels8, 16, 24, 32 8, 163232
ADC resolution24 bits 24 bits22 bits22 bits
Samples per second4,000 (32 channels) - 16,000 (8 channels) 125 (Bluetooth); 1000 (WiFi)1252,048
Hardware Price$495-$2,090 $500 - $950$2,100$5,000
Software Price$0 $0$384-$3192/year$5,000/year
Can stack with other Arduino shields?Yes NoNoNo
InterfacesUSB 2.0 HS, WiFi (via Raspberry Pi 4) Bluetooth, WiFiBluetoothEthernet
API accessYes Yes$0-$99/month$100/month
Raw EEG data accessYes Yes$55-$99/month$100/month
Use as lab instrument?Yes via Bluetooth or WiFiNoNo
Lab Streaming LayerYes YesNoNo
Python APIYes YesNoNo
FDA approvedNo NoNoYes

Support and Documentation

All hardware, drivers, and software are open source and available on GitHub:


In some of the photos, the HackEEG DIN 42-802 electrode connector board has nine connectors: eight inputs, one ground. The production connector board will have ten DIN 42-802 connectors: eight inputs, one reference, one ground. The videos were shot with a variant of the connector board that had the reference electrode connector placed on the back of the board.

Important Warnings

Although HackEEG has some of the features of a medical device, it does NOT have any certifications (FDA, CE, IEC, etc.) and is NOT officially approved for medical or diagnostic use. It is your responsibility to ensure your safety when using the device. Furthermore, you should never power the device from a non-isolated power source.

This is not a device made for consumer home use. The internal electronics are exposed during normal operation to facilitate easy access by developers and professionals. As such, you must be aware of the hazards of operating exposed electronics, and are familiar with standard anti-static procedures for handling bare electrical components, or be prepared to make your own case.

There is no patient isolation circuitry on the device, so you will need to be sure to operate the HackEEG and all connected devices from battery power.


Starcat, LLC

Adam is an experienced high-tech entrepreneur, electronic engineer, and software developer. Outside of work he practices meditation and yoga, volunteers, juggles, and hikes. He loves cooking Indian food, baking apple pies and spending time with his family.

Adam Feuer


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