Motor Imagery BCI Classification Based on Multivariate Variational ...
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Feb 16, 2022 · In this article, a novel computer-aided diagnosis framework is proposed for the classification of motor imagery (MI) electroencephalogram (EEG) signals.
In this article, a novel computer-aided diagnosis framework is proposed for the classification of motor imagery (MI) electroencephalogram (EEG) signals.
Abstract—In this article, a novel computer-aided diagnosis framework is proposed for the classification of motor imagery.
This work proposes a novel methodology for feature extraction and classification of motor imagery electroencephalogram signals.
May 1, 2023 · This work proposes a novel methodology for feature extraction and classification of motor imagery electroencephalogram signals. The proposed ...
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Classification of motor imagery BCI using multivariate empirical mode decomposition. IEEE Trans Neural Syst Rehabil Eng. 2013 Jan;21(1):10-22. doi: 10.1109 ...
Missing: Variational | Show results with:Variational
Apr 28, 2024 · ... To address this issue, one widely used method is multivariate mode decomposition (MEMD) and its noiseassisted version (NA-MEMD) (Rehman and ...
This paper presents a novel method for identifying right-hand and right-foot MI tasks. The method employs a single-channel adaptive decomposition and EEG ...
Jun 15, 2023 · This paper presents the unscented Kalman filter UKF to the BCI signal processing to classify the EEG-based motor imagery signals. UKF is applied ...
Deep CNN‐based classification of motor imagery tasks from EEG ...
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May 22, 2023 · After the MVMD algorithm has decomposed multichannel EEG signals in specific frequency bands, the resulting intrinsic modes have been combined ...