Optimizing Mental Workload by Functional Near-Infrared Spectroscopy Based Dynamic Difficulty Adjustment.

Abstract

Gains of cognitive training may be eliminated due to mental fatigue. This paper reports the design and implementation of a functional near-infrared spectroscopy (fNIRS) - dynamic difficulty adjustment (DDA) system. A total of 25 healthy volunteers underwent two training sessions - one with fixed difficulty level of training (FDT) and one with neurofeedback training (NFT) using our fNIRS-DDA system. The workload in each training session was assessed using the National Aeronautics and Space Administration Task Load Index (NASA-TLX). Whilst sustaining mental task performance, the drop in oxygenation level observed in NFT subjects might indicate mental fatigue as they received higher NASA-TLX scores, especially in both mental demand and frustration subscales. In contrast, the oxygenation levels remained almost constant by NFT subjects throughout the experiment. This suggests that the proposed fNIRS-DDA system aided the participants in avoiding mental fatigue. Future studies will investigate if the system may prevent the progression of Alzheimer's disease.

• Authors: Wei Chun Ung, Fabrice Meriaudeau, Tong Boon Tang
• Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference (Annu Int Conf IEEE Eng Med Biol Soc) Vol. 2018 Pg. 1522-1525 (Jul 2018) ISSN: 2694-0604 [Electronic] United States
• PMID: 30440682 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)

Topics

• Humans
• Mental Fatigue
• Spectroscopy, Near-Infrared
• Task Performance and Analysis
• Workload