GitHub - Quixotte/bci_practical_heyni_boorn

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Name		Name	Last commit message	Last commit date
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buffer_bci-master		buffer_bci-master
eegmmidb/S001/jf_prep		eegmmidb/S001/jf_prep
images		images
presentation		presentation
report		report
.gitignore		.gitignore
ClassDecider.asv		ClassDecider.asv
ClassDecider.m		ClassDecider.m
Data.mat		Data.mat
EM_Gaussian.m		EM_Gaussian.m
Gaussian.m		Gaussian.m
GaussianEM.m		GaussianEM.m
KMeans.asv		KMeans.asv
KMeans.m		KMeans.m
RunExperiment.m		RunExperiment.m
bars.png		bars.png
baselineFileGenerator.m		baselineFileGenerator.m
brainracer.m		brainracer.m
classifier.mat		classifier.mat
classifier_Hector.mat		classifier_Hector.mat
classifier_Thomas.mat		classifier_Thomas.mat
classifier_base_on_stef_thomas.mat		classifier_base_on_stef_thomas.mat
classifyEpoch.m		classifyEpoch.m
createDatasets.m		createDatasets.m
create_train_test.m		create_train_test.m
create_train_test_raw.m		create_train_test_raw.m
crossValidation.asv		crossValidation.asv
crossValidation.m		crossValidation.m
distinction.png		distinction.png
edfread.m		edfread.m
feature_extraction.asv		feature_extraction.asv
feature_extraction.m		feature_extraction.m
getClassificationResults.asv		getClassificationResults.asv
getClassificationResults.m		getClassificationResults.m
getRandomSeries.asv		getRandomSeries.asv
getRandomSeries.m		getRandomSeries.m
getSet.m		getSet.m
label.txt		label.txt
new_data.m		new_data.m
readme.txt		readme.txt
res_train.mat		res_train.mat
sendClass.m		sendClass.m
sendTest.m		sendTest.m
test.m		test.m
testAccuracy.asv		testAccuracy.asv
testAccuracy.m		testAccuracy.m
testFunction.m		testFunction.m
test_decider.asv		test_decider.asv
test_decider.m		test_decider.m
test_glm.asv		test_glm.asv
test_glm.m		test_glm.m
test_kmeans.asv		test_kmeans.asv
test_kmeans.m		test_kmeans.m
test_preprocessing.m		test_preprocessing.m
this_cap_best_cap.txt		this_cap_best_cap.txt
train_classify.m		train_classify.m
train_preprocessing.m		train_preprocessing.m
train_preprocessing_ersp.m		train_preprocessing_ersp.m

Repository files navigation

The dataset we are using is:
http://physionet.org/pn4/eegmmidb/

File and their use:
Experimental run 1: Baseline eyes open
Experimental runs 3, 7 and 11: opening left and right fist.
Within an experiment, you have 3 annotations:
T0: rest
T1: left fist
T2: right fist

Data can be downloaded from:
https://drive.google.com/folderview?id=0B4vuyuswipHQelB4dE80aWt2OGM&usp=sharing

Data collected in the following format:
Data, incomming_car_position, trial_id, classified as