1. Greentek EEG Cap & sound card EEG devices:

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https://openbci.com/forum/index.php?p=/discussion/comment/12696#Comment_12696

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2. TGAM Modul

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https://de.aliexpress.com/item/32999922405.html?spm=a2g0o.productlist.0.0.1fab3457M9Lrgb&algo_pvid=3946cf89-920f-455f-976c-785c052fbe2e&algo_expid=3946cf89-920f-455f-976c-785c052fbe2e-0&btsid=0ab6fb8316000576624564074ea608&ws_ab_test=searchweb0_0,searchweb201602_,searchweb201603_

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3. Validation of TGAM modules:

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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6630628/

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4. TGAM modues with Bluetooth Android App and Bluesoleil "with this kit you can make a wear BCI device yourself":

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https://de.aliexpress.com/item/32606318948.html?spm=a2g0o.productlist.0.0.529214c9dFto0P&s=p&ad_pvid=20200913214957176422413807000004428579_1&algo_pvid=9f35bae7-c8c5-4490-a496-7ecc6070584b&algo_expid=9f35bae7-c8c5-4490-a496-7ecc6070584b-0&btsid=0ab6f83116000589967501667e9b62&ws_ab_test=searchweb0_0,searchweb201602_,searchweb201603_

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5. Bluesoleil Ubuntu (for instance for the Linux PinePhone):

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http://www.bluesoleil.com/support/Intro.aspx?topic=BlueSoleil_Ubuntu_help

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6. Alternative from Texas instruments for 8 - 32 Channels: ADS1299 Performance Demonstration Kit from Texas instruments:

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http://www.ti.com/tool/ADS1299EEGFE-PDK

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https://www.youtube.com/watch?v=_LY4hHeG-Hs

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For a 8 channels EEG Data Aquisition System:

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https://www.researchgate.net/publication/325635924_Design_of_EEG_Data_Acquisition_System_based_on_Raspberry_Pi_3_for_Acute_Ischemic_Stroke_Identification

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For 32 channels EEG Data Aquisition System :

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https://www.researchgate.net/publication/332321992_Development_of_Electroencephalography_EEG_Data_Acquisition_System_based_on_FPGA_PYNQ

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The ADS1299 Performance Demonstration Kit is low-cost, it has an easy-to-use evaluation software for Microsoft Windows, and it can be interfaced to MATLAB.

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7. EEG data acquisition system 32 channels based on Raspberry Pi with relative power ratio and brain symmetry index features:

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https://www.researchgate.net/publication/337896178_EEG_data_acquisition_system_32_channels_based_on_Raspberry_Pi_with_relative_power_ratio_and_brain_symmetry_index_features

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8. Use of the TI ADS1299 EEG Kit:

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https://e2e.ti.com/support/data-converters/f/73/p/940917/3476990#3476990

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9. Safety of the TI ADS1299 EEG board:

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https://www.eevblog.com/forum/testgear/how-to-solve-the-ti-ads1299-eeg-demo-kit-is-not-save-for-humans-problem/

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10. The ADS1299 Kit contains the TI ADS1299 chip. Therefore, the data of the paper "comparison of Cyton with medical grade g.tec devices" should also apply to the ADS1299 Kit:

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https://arxiv.org/pdf/1606.02438.pdf

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11. Muse headband lab streaming layer (LSL):

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https://mind-monitor.com/forums/viewtopic.php?f=15&t=840

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sccn/labstreaminglayer#30

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13. OpenBCI, Brainflow and Linux Pinephone?:

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https://openbci.com/forum/index.php?p=/discussion/2692/does-the-openbci-software-run-on-arm64-based-device#latest

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14. MUSE HEADBAND ALTERNATIVE:

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a). OpenBCI compatible EEG module:

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https://de.aliexpress.com/item/4000244594585.html?spm=a2g0s.9042311.0.0.27424c4d9gZnYN

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b) OpenBCI compatible EEG Headband:

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https://www.aliexpress.com/item/4000244979554.html?spm=a2g0s.9042311.0.0.27424c4d9gZnYN

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15. BCILAB on Octave?

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sccn/BCILAB#36

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16. How to Run MATLAB Code in Octave

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https://itstillworks.com/12562105/how-to-run-matlab-code-in-octave

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17. Live-stream of sensor data from Mind Monitor app to Python (scripts kindly made available by Mind Monitor developer James Clutterbuck):

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https://mind-monitor.com/forums/viewtopic.php?f=15&t=1597

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18. Mind Monitor Python OSC Examples:

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https://mind-monitor.com/forums/viewtopic.php?f=15&t=1600

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19 Collecting EEG Signals with a Raspberry PI and a MUSE 2 headset (Flavio Frohlich, PH.D, FROHLICH LAB) :

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http://www.flaviofrohlich.org/thoughts/collecting-eeg-signals-with-a-raspberry-pi-and-a-muse-2-headset

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20. muselsl list issue on Raspberry PI (Muse LSL- Alexandre barachant, PhD.)

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alexandrebarachant/muse-lsl#137

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21.Issue with EEG Stream on Raspberry PI 4 (Flavio Frohlich, PH.D)

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alexandrebarachant/muse-lsl#140

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22. Neurofeedbacklab: Stream EEG data in real time and process it using advanced analysis methods (Arnaud Delorme, PhD.)

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https://github.com/arnodelorme/neurofeedbacklab

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Hardware requirements for Neurofeedbacklab: Any EEG system supported by LSL (this includes BIOSEMI, EGI, Neuroscan, Brainproducts, Emotiv, Cognionics, Enobio, Muse etc...)

See the full list at:

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https://labstreaminglayer.readthedocs.io/info/supported_devices.html

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To connect to Neurofeedbacklab, LabStreamingLayer is required. For LabStreamingLayer support for the InteraXon Muse MU-01 - Muse - Released 2014, the Muse SDK is required. The Muse SDK is not freely available anymore, but only available for a selected group of people. This has been discussed here:

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sccn/labstreaminglayer#30

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23. Adafruit already published a blog about «Recording Brainwaves with a Raspberry PI" on May 28, 2018 AT 6:00 pm:

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https://blog.adafruit.com/2018/05/28/recording-brainwaves-with-a-raspberry-pi/

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24. This thread only contains readme files, and is discontinued. The rest of what could be found regarding this subject can be found on my blog page Peter Gamma:

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https://petergamma.org/