3.eeg_recognation
EEGwithRaspberryPI
| 3.eeg_recognation | EEGwithRaspberryPI | |
|---|---|---|
| 2 | 44 | |
| 26 | 392 | |
| - | - | |
| 1.8 | 9.3 | |
| over 2 years ago | almost 2 years ago | |
| Python | Python | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 only |
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.
3.eeg_recognation
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.
What are some alternatives?
pywt - PyWavelets - Wavelet Transforms in Python
tio - A serial device I/O tool
brainflow - BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
ironbci - Open-Source Brain-Computer Interface, ADS1299 and STM32
fooof - Parameterizing neural power spectra into periodic & aperiodic components.
WaveDiff - Official Pytorch Implementation of the paper: Wavelet Diffusion Models are fast and scalable Image Generators (CVPR'23)
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.
EEG-BCI-signal-processing - Real-time EEG BCI signal processing by Python
muse-lsl - Python script to stream EEG data from the muse 2016 headset