Yu, Yinhu and Li, Junhua (2022) Feature Fusion-Based Capsule Network for Cross-Subject Mental Workload Classification. In: The 15th International Conference on Brain Informatics (BI2022), 2022-07-15 - 2022-07-17, Padova, Italy.
Yu, Yinhu and Li, Junhua (2022) Feature Fusion-Based Capsule Network for Cross-Subject Mental Workload Classification. In: The 15th International Conference on Brain Informatics (BI2022), 2022-07-15 - 2022-07-17, Padova, Italy.
Yu, Yinhu and Li, Junhua (2022) Feature Fusion-Based Capsule Network for Cross-Subject Mental Workload Classification. In: The 15th International Conference on Brain Informatics (BI2022), 2022-07-15 - 2022-07-17, Padova, Italy.
Abstract
In a complex human-computer interaction system, estimating mental workload based on electroencephalogram (EEG) plays a vital role in the system adaption in accordance with users’ mental state. Compared to within-subject classification, cross-subject classification is more challenging due to larger variation across subjects. In this paper, we targeted the cross-subject mental workload classification and attempted to improve the performance. A capsule network capturing structural relationships between features of power spectral density and brain connectivity was proposed. The comparison results showed that it achieved a cross-subject classification accuracy of 45.11%, which was superior to the compared methods (e.g., convolutional neural network and support vector machine). The results also demonstrated feature fusion positively contributed to the cross-subject workload classification. Our study could benefit the future development of a real-time workload detection system unspecific to subjects.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Uncontrolled Keywords: | Brain Connectivity; Capsule Network; Cross-Subject; EEG; Feature Fusion; Mantal Workload Classification; Power Spectral Density |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 11 Aug 2023 16:22 |
Last Modified: | 30 Oct 2024 15:50 |
URI: | http://repository.essex.ac.uk/id/eprint/33218 |
Available files
Filename: Feature Fusion-Based Capsule Network for Cross-Subject Mental Workload Classification.doc.pdf