EEG, EMG, accelerometer and gyroscope data for a FES-mediated brain-computer interface (BCI) aiming to suppress neurological tremor

001FN03.mat_EEG.csv
EEG data of patient 001FN03. 15 EEG channels (Fs: 1000Hz) : FC3, FCz, FC4, C5, C3, C1, CZ, C2, C4, C6, CP3, CPZ, and CP4 (POz: ground; linked ear-lobes: reference). Each column represents the above channels in the cited order.

001FN03.mat_IMU.acce.csv
Accelerometer data of patient 001FN03. 3 channels (Fs: 1000Hz) : x, y, z. Those data are presented here as complementary information. Scroll down sheet to view values.

001FN03.mat_IMU.gyro.csv
Gyroscope data of patient 001FN03. 3 channels (Fs: 1000Hz) : x, y, z. This is used for the kinematic module. The first second (more or less 1000 records) is silent and corresponds to the difference in time made while turning on the different acquisition devices. Scroll down sheet to view values.

001FN03.mat_sEMG.biceps.csv
Biceps EMG data of patient 001FN03. 15 channels (Fs: 1000Hz) : Resampled EMG data. This is used in the cortico-muscular module. Crossed with EEG data, cortico-muscular coherence has been computed for all possible couples of EEG-EMG data.

001FN03.mat_sEMG.extensors.csv
Extensors EMG data of patient 001FN03. 15 channels (Fs: 1000Hz) : Resampled EMG data. This is used in the cortico-muscular module. Crossed with EEG data, cortico-muscular coherence has been computed for all possible couples of EEG-EMG data.

001FN03.mat_sEMG.flexors.csv
Flexors EMG data of patient 001FN03. 15 channels (Fs: 1000Hz) : Resampled EMG data. This is used in the cortico-muscular module. Crossed with EEG data, cortico-muscular coherence has been computed for all possible couples of EEG-EMG data.

001FN03.mat_sEMG.triceps.csv
Triceps EMG data of patient 001FN03. 15 channels (Fs: 1000Hz) : Resampled EMG data. This is used in the cortico-muscular module. Crossed with EEG data, cortico-muscular coherence has been computed for all possible couples of EEG-EMG data.

QPs.csv
Quality paramter vs threshold numerical values (simple ratio). This is to find exact values corresponding to what is observed on the (corresponding) figure of the article. Each column is a different threshold value.

QPsq.csv
Quality paramters vs threshold numerical values (squared ratio). This is to find exact values corresponding to what is observed on the (corresponding) figure. Each column is a different threshold value.

Ts.csv
Intermediate threshold results. This can be discarded.

Tsq.csv
Intermediate threshold results. This can be discarded.