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

Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul:2018:1522-1525. doi: 10.1109/EMBC.2018.8512501.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

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