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Specifically, EEG signals analysis is considered here for the challenging task of cognitive fatigue detection. This work utilizes the topological attributes ...
Analysis indicates that all topological features derived from EEG signals contribute to the best performing subset, which also increases the overall accuracy.
EEG. Conference Paper. Cognitive Fatigue Detection from EEG Signals using Topological Signal Processing. January 2021. DOI:10.23919/Eusipco47968.2020.9287418.
Cognitive Fatigue Detection from EEG Signals using Topological Signal Processing. A. Das, K. Kumar, R. Gavas, D. Jaiswal, D. Chatterjee, R. Ramakrishnan, ...
This work aims to achieve a highly accurate and straightforward process to detect driving fatigue by using EEG signals.
This paper proposes a brain functional network construction method based on a phase locking value (PLV) and phase lag index (PLI), studies the relationship ...
In this paper, Electroencephalogram (EEG) based driving fatigue detection by using the Topological Data Analysis (TDA) was presented.
Missing: Cognitive | Show results with:Cognitive
This paper designs new fatigue cognitive indicators for brain detection. ... This paper constructs global and local features to reflect fatigue comprehensively.
We propose a new scoring algorithm for detecting delirium from one-channel EEG, based on Topological Data Analysis. Numerical experiments demonstrated that ...
The objective of this study is to develop a novel real-time driving fatigue detection methodology based on dry Electroencephalographic (EEG) signals. The study ...