학술논문
Riemannian classification analysis for model EEG intention speed patterns
Document Type
Conference
Source
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) Engineering in Medicine & Biology Society (EMBC), 2022 44th Annual International Conference of the IEEE. :402-405 Jul, 2022
Subject
Language
ISSN
2694-0604
Abstract
In this paper, the paradigm of the intention of speed changes from EEG signals with Riemannian classifiers methods is studied in 10 subjects. In addition, the best frequency band and how different electrode configurations affect the accuracy of the model are analyzed. In the prediction of the intention to change speed, results of 68.6% were obtained, in the one of only Increase, results of 64.41 % were obtained, and in the one of only Decrease, results of 71.5% were obtained.