EEGwithRaspberryPI
muse-lsl
EEGwithRaspberryPI | muse-lsl | |
---|---|---|
44 | 3 | |
392 | 575 | |
- | - | |
9.3 | 3.7 | |
almost 2 years ago | 22 days ago | |
Python | Python | |
GNU General Public License v3.0 only | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
EEGwithRaspberryPI
- PIEEG: Turn a Raspberry Pi into a Brain-Computer-Interface to Measure Biosignals
-
Raspberry Pi Shield – For Measure EEG (Pieeg)
source here - https://github.com/Ildaron/EEGwithRaspberryPI
paper available here https://www.researchgate.net/publication/357698587_PIEEG_Tur...
-
Raspberry PI Shield - for measure EEG (PIEEG)
source here - https://github.com/Ildaron/EEGwithRaspberryPI
- hack you brain - Hack your Brain - DIY brain-computer interfaces have arrived
- Hack your Brain - DIY brain-computer interfaces have arrived
- DIY brain-computer interfaces have arrived – why that’s cool (and why it isn’t)
- Example – Single-board computers for control robotics with the power of thought
- Control robot by mind (blinking) via RaspberryPi and PiEEG
-
[2201.02228] PIEEG: Turn a Raspberry Pi into a Brain-Computer-Interface to measure biosignals
Code for https://arxiv.org/abs/2201.02228 found: https://github.com/Ildaron/EEGwithRaspberryPI
-
PIEEG: Turn a Raspberry Pi into a Brain-Computer-Interface to measure biosignals. arXiv:2201.02228
This paper presents an inexpensive, high-precision, but at the same time, easy-to-maintain PIEEG board to convert a RaspberryPI to a Brain-computer interface. This shield allows measuring and processing eight real-time EEG(Electroencephalography) signals. We used the most popular programming languages-C, C++ and Python to read the signals, recorded by the device. The process of reading EEG signals was demonstrated as completely and clearly as possible. This device can be easily used for machine learning enthusiasts to create projects for controlling robots and mechanical limbs using the power of thought. We will post use cases on GitHub (https://github.com/Ildaron/EEGwithRaspberryPI) for controlling a robotic machine, unmanned aerial vehicle, and more just using the power of thought.
muse-lsl
- Code recommendations for the MUSE 2 using Python
-
Turn a Raspberry Pi into a Brain-Computer-Interface to Measure Biosignals
If you want sleep tracking, you can use Muse S [0]. You can stream EEG readings in real-time using [1].
However it's really, really hard to get _useful_ data about one's sleep. The results computed by Muse are garbage. The only successful product I know is Dreem [2] but they've exited the consumer market.
At the moment, I think the easiest way is to get an ECG (yep, for the heart, not the head) and process the readings using z3score-hrv [3].
[0]: https://choosemuse.com/muse-s/
[1]: https://github.com/alexandrebarachant/muse-lsl
[2]: https://dreem.com/
[3]: https://medium.com/neurobit-technologies/clinical-grade-slee...
- A Soft, Wearable Brain–Machine Interface
What are some alternatives?
tio - A serial device I/O tool
labstreaminglayer - LabStreamingLayer super repository comprising submodules for LSL and associated apps.
ironbci - Open-Source Brain-Computer Interface, ADS1299 and STM32
brainflow - BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
fooof - Parameterizing neural power spectra into periodic & aperiodic components.
EEG-with-JetsonNano - Open-Source. With deep learning to neuroscience world with shield for jetson nano - JNEEG (In progress)
freeswitch - FreeSWITCH is a Software Defined Telecom Stack enabling the digital transformation from proprietary telecom switches to a versatile software implementation that runs on any commodity hardware. From a Raspberry PI to a multi-core server, FreeSWITCH can unlock the telecommunications potential of any device.
3.eeg_recognation - Machine learning for Anonymous detection of an alcoholic by EEG signals
VideoLAN Client (VLC) - VLC media player - All pull requests are ignored, please follow https://wiki.videolan.org/Sending_Patches_VLC/
EEG-BCI-signal-processing - Real-time EEG BCI signal processing by Python
cdogs-sdl - Classic overhead run-and-gun game
pico-mixer - Mix different sound ambiances with a Pimoroni Keypad and a Raspberry Pi Pico