Multimodal Evaluation of Mental Workload Using a Hybrid EEGfNIRS Brain-Computer Interface System
Document Type
Conference Proceeding
Date of Original Version
5-16-2019
Abstract
Despite great advances in state-of-the-art braincomputer interfaces (BCIs), most BCIs do not consider users' cognitive status during operation, which might have a critical role in BCI performance. This study proposes a novel multimodal BCI to concurrently measure electrical and hemodynamic activities using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), and to quantify the neural correlates of mental arithmetic-induced workload at multiscale levels in two groups of old and young. We propose an oddball-based Math paradigm where the subjects performed a set of mental arithmetic operations at the target intensifications. Our analysis demonstrated an increase of EEG-delta and theta, a decrease of alpha, and an increase of fNIRS-oxyhemoglobin (HbO) level associated with mental workload, which were significantly observed in the elder group. The changes of EEG-delta, theta, and HbO were primarily found in the frontal and prefrontal areas while alpha was mainly seen in the parietal locations. The preliminary analyses suggest a set of functional brain processing, at multiscale levels, required by mental workload conditions that is more profound in the elder group.
Publication Title, e.g., Journal
International IEEE/EMBS Conference on Neural Engineering, NER
Volume
2019-March
Citation/Publisher Attribution
Borgheai, S. B., R. J. Deligani, J. McLinden, M. Abtahi, S. Ostadabbas, K. Mankodiya, and Y. Shahriari. "Multimodal Evaluation of Mental Workload Using a Hybrid EEGfNIRS Brain-Computer Interface System." International IEEE/EMBS Conference on Neural Engineering, NER 2019-March, (2019): 973-976. doi: 10.1109/NER.2019.8717118.