Dataset: The perils and pitfalls of block design for EEG classification experiments
- Citation Author(s):
-
Ren Li
(Purdue University, School of Electrical and Computer Engineering)
Jared S. Johansen
(Purdue University, School of Electrical and Computer Engineering)
Hamad Ahmed
(Purdue University, School of Electrical and Computer Engineering)
Thomas V. Ilyevsky
(Purdue University, School of Electrical and Computer Engineering)
Ronnie B. Wilbur
(Purdue University, Department of Speech, Language, and Hearing Sciences and Department of Linguistics)
Hari M. Bharadwaj
(Purdue University, Weldon School of Biomedical Engineering and Department of Speech, Language, and Hearing Sciences)
Jeffrey Mark Siskind
(Purdue University, School of Electrical and Computer Engineering)
- Submitted by:
- Jeffrey Siskind
- Last updated:
- DOI:
- 10.21227/x2gf-5324
- Data Format:
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- Categories:
- Keywords:
Abstract
Dataset asscociated with a paper in IEEE Transactions on Pattern Analysis and Machine Intelligence
"The perils and pitfalls of block design for EEG classification experiments"
DOI: 10.1109/TPAMI.2020.2973153
If you use this code or data, please cite the above paper.
Instructions:
See the paper "The perils and pitfalls of block design for EEG classification experiments" on IEEE Xplore.
DOI: 10.1109/TPAMI.2020.2973153
Code for analyzing the dataset is included in the online supplementary materials for the paper.
The code and the appendix from the online supplementary materials are also included here.
If you use this code or data, please cite the above paper.
Dataset Files
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