Project for XAI606(Korea University). Contribute to High-East/XAI606-EEGNet development by creating an account on GitHub.
It is the task to classify BCI competition datasets (EEG signals) using EEGNet and DeepConvNet with different activation functions. You can get some detailed introduction and experimental results in the link below.https://github.com/secondlevel/EEG-classification/blob/main/Experiment%20Report.pdf ...
1. **约翰霍普金斯大学脑机接口工具包(JHU-BCI v3.2)** - **获取方式**:访问[GitHub仓库](https://github.com/JHUBCILAB/OpenBCI_Analysis_Toolkit) - **核心功能**: - 预置EEGNet的PyTorch优化实现(推理速度提升40%) - 提供抑郁症患者EEG数据集(n=214,含临床诊断金标准) - 支持跨模态数据同步(脑波+心...
实验结果表明EEGNet足够鲁棒,可以在一系列BCI任务中学习各种可解释的特征,这表明观察到的性能不是由于数据中的伪影或噪声源造成的。模型源码:https://github.com/vlawern/arl-eegmodels EEGNet EEGNet ,(1)可以应用于多种不同的BCI范式 ,(2)可以用非常有限的数据进行训练 ,(3)可以产生神经生理学上可解释的特征。
Our models can be found at: https:// github.com/vlawhern/arl-eegmodels.Vernon J LawhernHuman Research and Engineering DirectorateAmelia J SolonHuman Research and Engineering DirectorateNicholas R WaytowichHuman Research and Engineering Directorate...
To initiate EEG preprocessing, a custom database loader module (see https://github.com/UN-GCPDS/python-gcpds.databases, accessed on 8 April 2023) was utilized to load the recordings. Only EEG channels were considered, and the signals were scaled to 𝜇𝑉μV to ensure suitability for anal...
Brain computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given BCI paradigm, feature extractors and classifiers are tailored...
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Model details can be found at https://github.com/linbingru/am-eegnet.doi:10.1016/j.neucom.2024.127622Lin P.-J.Lab of Intelligent and Bio-mimetic Machinery Department of Mechanical Engineering Tsinghua UniversityLi W.Lab of Intelligent and Bio-mimetic Machinery Department of Mechanical Engineering ...
Source codes: Signal processing and classification framework—https://github.com/kolcs/bionic_apps; Paradigm handler—https://github.com/kolcs/GoPar. Datasets: Physionet—https://physionet.org/content/eegmmidb/1.0.0/; Giga—http://gigadb.org/dataset/100542; BCI Competition IV—https://www....