Cognitive workload assessment based on temporal and spatial characteristics of electroencephalogram spectrum
WANG Yu-jia
JU Xiang-yu
YU Yang
LI Ming
Abstract：Accurate cognitive workload assessment is of great significance for enhancing human-machine coordination and improving the efficiency of human-machine integration systems.Due to the low spatial resolution and the temporal fluctuation of electroencephalogram(EEG)spectrum,commonly used EEG based methods for cognitive workload as-sessment are not effective in utilizing spatial and temporal information among the EEG spectrum.In this work,a novel cognitive workload assessment algorithm is proposed by fusing the spatial and temporal features of the EEG spectrum,which are extracted by a CapsNet and a long short term memory network.Test results based on public datasets show that the proposed algorithm achieves the optimal performance among SOTA algorithms,reaching 99.27％(data-dependent)and 95.16％(data-independent).The ablation experiments prove that the temporal and spatial feature extraction modules of the algorithm can effectively represent the corresponding features of EEG spectrum,and the proposed dual-stream network structure can accomplish the efficient fusion of temporal and spatial features.
Keywords：cognitive workload assessmentpower spectrum patterntemporal and spatial characteristicsdual-stream network for spatial and temporal representation
Publication Date：2025-01-27
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 50-58 )