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I am implementing your paper for EEG classification. The EEG data is of dimension 19x120000 where 19 is the number of electrodes and 120000 are the time points. I would like to understand how this dat…
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- [ ] [Connecting cortex to machines: recent advances in brain interfaces](https://www.nature.com/articles/nn947) (2002)
- [ ] [Visual P300 Mind-Speller Brain-Computer Interfaces: A Walk Through t…
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I'm not sure about the effect of EEG pretraining. I have directly train a shallow convolution network on `eeg_5_95_std.pth` as used in your paper. And the test accuracy according to max validation is …
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### Describe the feature or idea you want to propose
The HHT is a transform sometimes used with EEG and might be interesting for classification of EEG
https://en.wikipedia.org/wiki/Hilbert%E2%80%9…
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Hello @eeyhsong, I have some question as below when I have finished all steps according to Readme file. Now, i want to get the classification results as shown in Figure.3 in the paper, but when i ru…
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Celem zadania jest:
- preprocessing sygnału (filtracja częstotliwości);
- downsampling.
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Opisać i zadecydować o tym jak będziemy jak wyglądać nasza architektura CNN.
- [ ] różna długość próbek na wejście do CNN - rozwiązania:
a) przycięcie próbek,
b) podział sygnałów próbek na 'pod-p…
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/Users/apple/.conda/envs/EEG_classification/bin/python /Users/apple/PycharmProjects/deepsleepnet/prepare_physionet.py
Traceback (most recent call last):
File "/Users/apple/PycharmProjects/deepslee…
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Plik converter zawiera funkcje, które umożliwiają na szybką pracę na DataFrame'ach. Na ten moment jest to bardzo ograniczone ale na ten moment wystarczające dla naszych celów.
Flow pracy, które prz…
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The goal is to study DL method for BCI classification:
- [Deep learning with convolutional neural networks for EEG decoding and visualization](https://pubmed.ncbi.nlm.nih.gov/28782865/), 1744 citati…