fooof
EEGwithRaspberryPI
| fooof | EEGwithRaspberryPI | |
|---|---|---|
| 1 | 44 | |
| 340 | 392 | |
| 2.1% | - | |
| 9.0 | 9.3 | |
| 12 days ago | almost 2 years ago | |
| Python | Python | |
| Apache License 2.0 | 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.
fooof
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Issues interpreting EEG data
If you have experience with Python, you can use the FOOOF (Fitting Oscillations & One Over F) toolbox to analyze your EEG data and find the highest peak in the theta band for each electrode.
EEGwithRaspberryPI
- PIEEG: Turn a Raspberry Pi into a Brain-Computer-Interface to Measure Biosignals
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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...
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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
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[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
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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?
python-meegkit - 🔧🧠 MEEGkit: MEG & EEG processing toolkit in Python
tio - A serial device I/O tool
Kilosort - Fast spike sorting with drift correction for up to a thousand channels
ironbci - Open-Source Brain-Computer Interface, ADS1299 and STM32
NeuroKit - NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
EEG-with-JetsonNano - Open-Source. With deep learning to neuroscience world with shield for jetson nano - JNEEG (In progress)
EEGwithRaspberryPI - Open-Source board for converting RaspberryPI to Brain-computer interface
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.
brainstorm3 - Brainstorm software: MEG, EEG, fNIRS, ECoG, sEEG and electrophysiology
3.eeg_recognation - Machine learning for Anonymous detection of an alcoholic by EEG signals
TS-TCC - [IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"
muse-lsl - Python script to stream EEG data from the muse 2016 headset