Is it worth to build a 32 channel EEG headset?

Chinese developers have already developed the 32 channel BEATS device. All components of this headset are open source and available. It is similar as with the Pinephone keyboard. The Pinephone keyboard is not available anymore. But you can let fabricate it by yourself. But will you be able to make money out of it? Pine64 wasn’t and has pulled it from the market.

But there are more options for you 32 channel EEG headsets:

  • The 32 channel system based on the ADS1299 Ti demo kit. The daisy chain software for it is not open source and available. You have to code it yourself or by it from the Indonesian developers.
  • The 32 channel system based on on HackEEG. It is not available anymore, but the hardware is open source. You can let fabricate yourself if you want to.

You can also solder 32 TGAM modules together according to this instruction:

For having a 32 channel EEG device based on InfluxDB. But we expect that someone will build such a device sooner or later who is more skilled than we in soft- and hardware development. And we suppose also that it will start selling on Aliexpress with 32 TGAM modules designed for InfluxDB for around 700 USD. But the price could be also higher at the beginning as the example of the Empatica E4 has shown which is designed for real-time databases. The device has been discontinued. It was sold for 2500 USD. But will not someone build cheaper devices who thinks a g.tec medical headset with 32 channels for 50 000 USD is too expensive? Peter Gamma from www.petergamma.org:

will continue to write price comparison charts as this one:

Becauce he thinks this helps the most to make EEG devices more affordable. And until that Peter can live with a 16 channel EEG device, and exploit it to the peak. He thinks it is worth to test if we can repair the OpenBCI modules which are sold on eBay and Aliexpress.

Medical Computer Systems in Moscow, Russia have aleady shown us a wireless mobile 16-channel EEG System for researchers:

And Ramin Maragey, biophysicist and scientific researcher at the Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences has showed us an impressive guide for the the preparation of such an EEG heatset:

We count 21 EEG channels in Maragey’s EEG heatset. He uses an NVX 36 amplifier. NVX is a DC amplifier with 24, 32 or 48 monopolar EEG channels and 4 auxiliary bipolar channels for sensors:

https://mks.ru/en/products/nvx

But we can build a similar heatset with 16 channels buy ourselves from the components reviewed on www.petergamma.org, and we won t buy the heatset from Medical Computer Systems.

And for those who need a 32 or 64 EEG heatset right now, the can buy a SMARTING PRO X device from mBrainTrain in Serbia:

But we suppose boards with 32 TGAM modules for 32 EEG channels for around 700 USD and 64 TGAM modules for 64 EECG channels for around 1400 USD designed for InfluxDB will be available sooner or later on Aliexpress. The price for TGAM modules has remained stable over the last years, or even dropped slightly. But not the price for 32 channel EEG modules on Aliexpress based on the ADS1299 chip from Texas Instruments. The price for those increased from around 700 USD to around 5 0000 USD.

For us personally, devices based on InfluxDB are the future, since the hardware costs are low. The software for such boards is not yet available open source. We suppose that it will be difficult for mBrainTrain to make a lot of money from their EEG devices. Since who will buy expensive EEG devices from mBrainTrain in Serbia if InfluxDB boards and software will be available which are cheaper sooner or later?

EEGLAB developer Arnaud Delorme was also invited to Serbia to give talks about mobile EEG devices in Belgrad where mBrainTrain is located. But Delorme started now teaching Monday Meditation on YouTube. And the mBrainTrain crew can follow the example of Delorme if they want to, should they loose their jobs if devices based on InfluxDB will come onto the market which are cheaper than devices from mBrainTrain: