A lot of my previous projects have been around existing EEG tools, both open source and commercial products. I've been working on my own board that get's around some of the shortcomings I've found when looking at these with the goal of making something that is entry level and affordable but still good quality for EEG and similar biopotential projects.
The current design is single-channel and can be used to acquire and digitize EEG, EMG, EOG and ECG signals. It also includes a low-power, triple-axis accelerometer to track motion.
I'm working on a campaign for initial orders here:
This will help get more initial batches made ready for shipping in the new year.
The board features front-end filtering and user/device protection and is the same as what you'd find on things like the Mikroe EEG board I've reviewed before and OpenEEG but the amplification stages are different, with an initial fixed gain of around 50 at the instrumentation amp and an option to further increase this utpo 200x overall with the onboard ADC.
Because the board uses a high resolution delta-sigma type ADC, it means you don't need extreme amounts of gain. The high speed sampling rate (upto 1000Hz) also means that it has relaxed anti-aliasing requirements and can be used for a wide range of biopotential signals:
The instrumentation amp used on the module is the MAX4194 from Analog Devices. I've generally used common packages and a design that uses discreet components rather than all-in-one bio-amp chips to avoid chip shortage issues and high costs.
The board can be connected to pretty much any MCU that has the i2C prehipheral. It is also a solder-less design and connectivity to an MCU board is via a Stemma QT/Quiic cable. Sensors are connected using the onboard 3.5mm jack. Here is an example connected to an Adafruit Feather M0 Adalogger. The mounting holes on the breakout actually have the same spacing as Feather boards to make it easier to build a complete setup in a small space with these kinds of boards.
I've been using this breakout to track sleep, using another feather board, this time the STM32F405 Express and using gel snap eletctodes. Here's how my setup looks with the cover removed from the 3D printed enclosure. There is a battery mounted at the bottom and a power switch added to the Feather board. The advantage of the STM32 Feather is that is has a Stemma-QT connector mounted on it also for i2C so connectivty is simple with a male-to-male stemma cable:
To make things easier to start with, I've uploaded some example Arduino based firmware and also a python script that shows how to acquire an EEG signal and process it to show a spectrogram:
The functions used with the Arduino code should be universal and work on most Arduino platforms without issue. It can also be easily adapted to work for ECG and EMG etc.
Here is an example spectrogram from a sleep session using this and a hypnogram based on an AI model (note the AI model is not included in the example software):
The reason I've made this is because I don't think there are many options for modular, DIY projects, particularly for low-power and mobile based applications. At one end there are products from OpenBCI but the overall cost for a total system with these are quite expensive. At the more affordable end, there are products like EEG-SMT from Olimex and EEG-Click from Mikroe but again these are not great for modern applications as they run from a minimum of 5V and EEG-SMT is quite an old design by this point. Here is a comparison table to show some of the differences between this board listed at the top and other current options including cost and key attributes:
The board will come with relevant cables and a few disposable snap-electrodes to get started:
Silver-Chloride gel based snap electrodes are easy to find but the great thing with the cable is you can try other electrode types and materials to test what works best. These kind of comb style dry electrodes could work well through hair for example:
Example Electrode Layouts for ECG/EKG
Example Electrode Layouts for EEG
If you're interested in the project, the easiest way to track updates is on Indiegogo, it should be ready to launch in the next couple of weeks or so:
I will also update with news on here.
Feel free to message or comment for any questions.