NeuroKit
EEG-with-JetsonNano
NeuroKit | EEG-with-JetsonNano | |
---|---|---|
1 | 5 | |
1,386 | 40 | |
3.6% | - | |
9.2 | 5.3 | |
about 1 month ago | 8 days ago | |
Python | C | |
MIT License | 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.
NeuroKit
-
Help in getting ECG waveforms or HR, HRV from PolarH10
I am aware of the official Polar support available here: https://github.com/polarofficial/polar-ble-sdk/issues. However, as it only provides support for Android and iOS, it doesn't fulfill my requirements. My task needs me to obtain these APIs on a Linux platform, as I intend to convert this data for use with the ROS publisher and subscriber later. I am also open to look for other feasible solution for Linux, and I'm open to exploring other reliable GitHub repositories that could help me capture ECG waveforms or directly obtain HR, HRV, and Respiration Rate values from the devices directly. I was hopeful about this one - https://github.com/neuropsychology/NeuroKit, but it turns out that it needs the ECG waveforms to be saved independently and later these signals would be processed offline. (Not real time). I also found this other repositories that I think would be useful but not too sure - https://github.com/kbre93/dont-hold-your-breath.
EEG-with-JetsonNano
-
Device JNEEG to convert Jetson Nano to brain-Computer interfaces. Short report
Artificial intelligence has made significant advances in recent years and this has had an impact on the field of neuroscience. As a result, different architectures have been implemented to extract features from EEG signals in real time. However, the use of such architectures requires a lot of computing power. As a result, EEG devices typically act only as transmitters of EEG data, with the actual data processing taking place in a third-party device. That's expensive and not compact. In this paper, we present a shield that allows a single-board computer, the Jetson Nano from Nvidia, to be converted into a brain-computer interface and, most importantly, the Jetson Nano's capabilities allow machine learning tools to be used directly on the data collection device. Here we present the test results of the developed device. https://github.com/HackerBCI/EEG-with-JetsonNano
- With deep learning to neuroscience world with shield for jetson nano – JNEEG
- Open-Source board for converting Jetson nano to Brain-computer interface
What are some alternatives?
pyVHR - Python framework for Virtual Heart Rate
JETGPIO - C library to manage the GPIO header of the Nvidia Jetson boards
BIOBSS - A package for processing signals recorded using wearable sensors, such as Electrocardiogram (ECG), Photoplethysmogram (PPG), Electrodermal activity (EDA) and 3-axis acceleration (ACC).
EEGwithRaspberryPI - Open-Source board for converting RaspberryPI to Brain-computer interface [Moved to: https://github.com/HackerBCI/EEGwithRaspberryPI]
fooof - Parameterizing neural power spectra into periodic & aperiodic components.
jetson-inference - Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
Pathfinder - Search Strategy analysis and more for spatial navigation data in rodents
ironbci - Open-Source Brain-Computer Interface, ADS1299 and STM32
polar-ble-sdk - Repository includes SDK and code examples. More info https://polar.com/en/developers
3.eeg_recognation - Machine learning for Anonymous detection of an alcoholic by EEG signals
PulseSensorPlayground - A PulseSensor library (for Arduino) that collects our most popular projects in one place.
dont-hold-your-breath - Breathing analysis with Polar H10 Heart Rate Monitor