Residual one-dimensional convolutional neural network for neuromuscular disorder classification from needle electromyography signals with explainability.

[BibT_eX]

[DOI]

Jaesung Yoo

Ilhan Yoo

Comput. Methods Programs Biomed., 2022

2020

Complex Motor Imagery-based Brain-Computer Interface System: A Comparison Between Different Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

2019

Comparative analysis of features extracted from EEG spatial, spectral and temporal domains for binary and multiclass motor imagery classification.

[BibT_eX]

[DOI]

Inf. Sci., 2019

Classification of the Motion Artifacts in Near-infrared Spectroscopy Based on Wavelet Statistical Feature.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

Reduced Burden of Individual Calibration Process in Brain-Computer Interface by Clustering the Subjects based on Brain Activation.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

Recurrent convolutional neural network model based on temporal and spatial feature for motor imagery classification.

[BibT_eX]

[DOI]

Proceedings of the 7th International Winter Conference on Brain-Computer Interface, 2019

Exploring the Number of Repetitions in Trials for the Performance Convergence of Classification in Motor Imagery Task with Hand-Grasping.

[BibT_eX]

[DOI]

Proceedings of the 7th International Winter Conference on Brain-Computer Interface, 2019

2018

Automated artifact elimination of physiological signals using a deep belief network: An application for continuously measured arterial blood pressure waveforms.

[BibT_eX]

[DOI]

Inf. Sci., 2018

Robust arterial blood pressure onset detection method from signal artifacts.

[BibT_eX]