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MI-vs rest 5-fold cross-validation accuracy for each subject and session.

NIAID Data Ecosystem2026-03-10 收录

数据链接：

https://figshare.com/articles/dataset/MI-vs_rest_5-fold_cross-validation_accuracy_for_each_subject_and_session_/4479011 数据链接链接失效反馈

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资源简介：

The best accuracy for each session is in bold.

应用场景：

创建时间：

2016-12-17

脑机接口性能评估

神经信号解码

Mean and standard deviation of the correlation coefficient and the slope of the regression line fitted to the outputs of the sNN-BCI across all participants for each presentation rate.

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Accuracy and processing time of the BCI segment, CBI segment, and overall BBI communication for three sessions.

脑机接口性能评估

脑脑通信效率

Accuracy and processing time of the BCI segment, CBI segment, and overall BBI communication for three sessions.

NIAID Data Ecosystem40

EEG Features Extraction from Bands Delta, Theta, Alpha, Beta and Gamma.

运动想象脑电分类

脑电频段特征提取

The hypothesis that will allow us to show our data is to classify the EEG signals related to real movements of the left hand, right hand, both hands, both feet, and relaxation. Each of the different f

Mendeley Data20

Information transfer rate (ITR) in bits/min for each participant for the c-VEP and SSVEP system.

脑机接口性能评估

视觉诱发电位通信

Information transfer rate (ITR) in bits/min for each participant for the c-VEP and SSVEP system.

Figshare2019-06-13 更新40

Classification performance for all BCI conditions.

脑机接口性能评估

脑机接口(BCI)

For explanation of the various conditions see the Methods section. Classification (%) refers to the binary classification score on the artifact free dataset, i.e. the correct classification of individ

NIAID Data Ecosystem20

MI-vs rest 5-fold cross-validation accuracy for each subject and session.

资源简介：

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