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Averaged accuracy of classifying the imagination test set.

NIAID Data Ecosystem2026-03-14 收录

脑机接口分类

运动想象识别

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https://figshare.com/articles/dataset/Averaged_accuracy_of_classifying_the_imagination_test_set_/21182014 数据链接链接失效反馈

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Averaged accuracy of classifying the imagination test set.

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创建时间：

2022-09-21

视觉诱发电位

脑机接口分类

A 12-class steady-state visual evoked potential (SSVEP) derivative dataset acquired from 9 healthy subjects using 8-channel EEG recorded at 256 Hz with joint frequency-phase modulation. This preproces

DataCite Commons2026-05-04 更新440

Average Rankings of the classification algorithms for binary and multi-class classification in synchronous datasets.

脑机接口分类

算法评估

The number of subjects in binary task was 12 and the number of subjects in multi-task BCIs was 9. The number in the parenthesis corresponds to the average rank of the algorithm among different subject

NIAID Data Ecosystem70

Open Access fNIRS Dataset for Classification of Unilateral Finger- and Foot-Tapping

运动意图解码

脑机接口分类

fNIRS dataset for ternary classification

Figshare2019-12-26 更新40

The results of 10-fold cross validation for the proposed method versus Tabassian’s method, SVM, LDA, and MLP over the dataset IIa of BCI competition IV.

脑机接口分类

脑机接口(BCI)

The results of 10-fold cross validation for the proposed method versus Tabassian’s method, SVM, LDA, and MLP over the dataset IIa of BCI competition IV.

NIAID Data Ecosystem90

BCI classification task

脑机接口分类

运动意图解码

Seven healthy volunteers (3 male and 4 female) participated in the study, all were right-handed and between the ages of 23 to 30 (mean age 28). All participants gave written, informed consent to parti

NIAID Data Ecosystem60

Averaged accuracy of classifying the imagination test set.

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